Podcasts about responsible ai

Why the most effective communicators help people see not just what's changing, but why it matters to them.For Sinéad Bovell, effective communication isn't just about explaining what's coming next—it's about giving people the confidence and agency to engage with it.Bovell is a futurist, founder of the tech education company WAYE, and an expert advisor to the United Nations AI Advisory Body. Known for making complex topics accessible to broad audiences, she has spent years helping leaders, organizations, and young people understand the implications of artificial intelligence and other transformative technologies. Her approach starts with a simple principle: meet people where they are and connect big ideas to what matters in their lives. “If you scare people too much, if you disempower them, [and] they do unsubscribe from the very activities you need them to lean into.”In this episode of Think Fast, Talk Smart, Bovell joins host Matt Abrahams to discuss how to communicate complexity without overwhelming people and why skills like adaptability and judgment are becoming more valuable in the age of AI. From making emerging technologies more accessible to building trust through relevance and empathy, they discuss what it takes to help audiences engage with change rather than fear it.To listen to the extended Deep Thinks version of this episode, please visit FasterSmarter.io/premium.Episode Reference Links:Sinéad BovellConnect:Premium Signup >>>> Think Fast Talk Smart PremiumEmail Questions & Feedback >>> hello@fastersmarter.ioEpisode Transcripts >>> Think Fast Talk Smart WebsiteNewsletter Signup + English Language Learning >>> FasterSmarter.ioThink Fast Talk Smart >>> LinkedIn, Instagram, YouTubeMatt Abrahams >>> LinkedIn Chapters:(00:00) - Introduction (01:00) - Explaining Complex Ideas (03:48) - The Future of Soft Skills (06:52) - Talking About AI Without Fear (10:33) - Storytelling for Young Audiences (12:46) - Reaching Young Audiences (15:01) - Career Pivots & Reinvention (16:53) - Becoming a Better Communicator (18:59) - The Final Three Questions (25:09) - Conclusion

Gugs Mhlungu speaks with Dr Mark Nasila, Chief Data and Analytics Officer at First National Bank Risk, about Anthropic’s new Claude Mythos 5 rollout and the public Claude Fable 5 model designed with safety restrictions to limit misuse and what this means for AI safety, cybersecurity, and the future of responsible AI use. Gugs Mhlungu gets you ready for the weekend each Saturday and Sunday morning on 702. She is your weekend wake-up companion, with all you need to know for your weekend. The topics Gugs covers range from lifestyle, family, health, and fitness to books, motoring, cooking, culture, and what is happening on the weekend in 702land. Thank you for listening to a podcast from 702 Weekend Breakfast with Gugs Mhlungu. Listen live on Primedia+ on Saturdays and Sundays from 06:00 and 10:00 (SA Time) to Weekend Breakfast with Gugs Mhlungu broadcast on 702 https://buff.ly/gk3y0Kj For more from the show go to https://buff.ly/u3Sf7Zy or find all the catch-up podcasts here https://buff.ly/BIXS7AL Subscribe to the 702 daily and weekly newsletters https://buff.ly/v5mfetc Follow us on social media: 702 on Facebook: https://www.facebook.com/TalkRadio702 702 on TikTok: https://www.tiktok.com/@talkradio702 702 on Instagram: https://www.instagram.com/talkradio702/ 702 on X: https://x.com/Radio702 702 on YouTube: https://www.youtube.com/@radio702See omnystudio.com/listener for privacy information.

LEXINGTON, Ky. (June 11, 2026) – [THIS IS AN ENCORE EPISODE.] Artificial intelligence is moving fast — and Kentucky lawmakers are working to make sure the state can take advantage of new tools without sacrificing transparency, privacy or public trust. On this episode of 'Behind the Blue', Kentucky State Senator Amanda Mays Bledsoe — a Lexington native and University of Kentucky alum — joins host Kody Kiser to talk about her path into public service, what she's hearing from constituents in Senate District 12, and how she views UK's land-grant mission of service to communities across the Commonwealth.  Bledsoe represents parts of Fayette County along with Woodford, Mercer and Boyle counties. In the conversation, she points to infrastructure — including roads and aging water and wastewater systems — as a major concern for the region, while also highlighting the role higher education, signature industries and health care play in central Kentucky's future.  The interview also explores Bledsoe's emerging leadership on technology policy, including Kentucky Senate Bill 4, which she describes as a framework for "responsible AI governance" within state government. Bledsoe explains that the goal is not to regulate every minor use of technology, but to establish guardrails for higher-risk, decision-making tools — including creating transparency around where and how AI is used, and building oversight to ensure accountability.  "AI is not spellcheck," Bledsoe said, emphasizing the need for stronger scrutiny when government systems generate new outputs or influence decisions. She also discusses concerns around deceptive AI-generated political content and the importance of ensuring voters can trust what they see — particularly in the final days leading up to an election.  Looking ahead, Bledsoe points to a wide range of challenges and opportunities — from consumer protection and privacy to safeguarding minors online — and says Kentucky will likely need to keep refining its approach as the technology evolves. She also describes how institutions like UK can help shape the state's AI future through research, workforce preparation and teaching students to be critical, responsible users of these tools. 'Behind the Blue' is available via a variety of podcast providers, including Apple Podcasts, YouTube and Spotify. Subscribe to receive new episodes each week, featuring UK's latest medical breakthroughs, research, artists, writers and the most important news impacting the university. 'Behind the Blue' is a production of the University of Kentucky. Transcripts for most episodes are now embedded in the audio file and can be accessed in many podcast apps during playback. Transcripts for older episodes remain available on the show's blog page.  To discover how the University of Kentucky is advancing our Commonwealth, click here. This interview has been edited for time and clarity.

Most home service companies don't have a lead problem. They have a follow-up problem. In this episode of Service Business Mastery, Tersh Blissett and Joshua Crouch sit down with Kevin Wu, founder of Leaping AI, to discuss how AI voice agents and automation are helping home service businesses solve some of their biggest call center challenges. From missed calls and slow follow-up times to after-hours booking and lead nurturing, Kevin shares how AI is being used as a practical tool to support customer service teams, improve speed-to-lead, and create better customer experiences without replacing people. The conversation also explores the future of AI-powered call centers, how contractors can automate repetitive tasks, and why business owners should focus on using AI to eliminate bottlenecks instead of simply cutting payroll. What You Will Learn in This Episode Why speed-to-lead is still one of the biggest challenges in home services How AI voice agents help capture missed opportunities The difference between replacing employees and supporting employees Why call centers struggle with consistency and process adherence How AI can improve appointment scheduling and follow-up The role of AI in call monitoring and quality control Why data quality inside your CRM matters more than ever How AI can help clean and organize customer databases The future of automated outbound campaigns The risks of AI abuse and spam calling How responsible AI adoption can improve customer experience Why contractors should start experimenting with AI today If you're looking for ways to improve call handling, increase booked appointments, and build a more efficient service business, this episode is packed with practical insights. Timestamps 00:00 Challenges with contractor responsiveness 03:11 Kevin introduces himself 08:58 Kids' interest in trade careers 09:45 Issues with Customer Support Responsiveness 14:00 AI improving call center efficiency 18:33 Solving data analysis with AI 20:55 Improving business metrics accuracy 25:37 Implementing EOS for business owners 29:31 Focusing on business priorities 32:00 AI for persistent customer follow-up 35:27 Responsible AI use in marketing 39:33 Data export issues in QuickBooks 40:45 Using AI to clean CRM data 43:35 Trying something new for 30 minutes Follow the Host and Guest Tersh Blissett: https://www.linkedin.com/in/tershblissett/ Joshua Crouch: https://www.linkedin.com/in/josh-crouch/ Kevin Wu: https://www.linkedin.com/in/kevin-wu-452a6393/ Connect with Us • LinkedIn - https://www.linkedin.com/company/service-business-mastery • TikTok - https://www.tiktok.com/@servicebusinessmasterypodcast • Facebook Group - https://www.facebook.com/groups/servicebusinessmasterypodcast • Instagram - https://www.instagram.com/servicebusinessmasterypodcast This episode is kindly powered by: UpFrog: upfrog.com  MarketStorm is an AI-powered advertising platform. Results vary by market, budget, and campaign configuration: https://marketstorm.ai/  Get Your 14-Day Free Trial with CallRail!: https://www.callrail.com/sbmpod CompanyCam: https://companycam.com/  Breezy: Capture 25-30% more clients with Breezy AI Agents. Use code 'SBM' to book a demo and get $500 on us: https://getbreezyapp.com/schedule-demo PhoneTAP: Your calls hold the key to growing your business. PhoneTAP gives you instant AI analysis, real customer lifetime value, and tools to coach your team. Learn more: phonetap.ai/demo   

Courtney Radsch reports on the political and economic impact of synthetic media and the stultifying consequences of our increasingly low-quality, high-fat media diet.  Courtney and Kimberly discuss the range of journalistic endeavors; synthetic media's entrée on the scene; disinformation vs. propaganda; competing with AI in the marketplace of ideas; content verification, labeling and trust; how synthetic media depends on and undermines journalism; information as a social, political and economic concern; embedded AI ideologies; equating regulation with censorship; information warfare; cognitive liberty in an age of corporate dominance; infrastructure and intent; the need for bright line protections, pluralism and independent oversight.Dr. Courtney Radsch, PhD is the Director of the Center for Media and Digital Governance (formerly CJL) and a non-resident Fellow at the Brookings Institution.  An award-winning journalist, scholar, diplomat, and human rights advocate, Courtney was recently named one of the 100 Brilliant Women in AI Ethics.Related Resources:Same Gatekeepers, New Tollbooths: Mapping the AI Content Licensing Market (CMDG Research Report)The Algorithm Loses Its Immunity (Article)The Pentagon Wants Its Panopticon (Article)The Battle for Cognitive Liberty in the Age of Corporate AI (Tech Policy Press)A transcript of this episode is here.

Nishat Mehta, CEO of Lexitas, joins Jennifer Simpson Carr to discuss how AI and technology-enabled litigation services are reshaping the legal industry. From deposition summaries and case triage to client pressure, access to justice, and the future of the billable hour, the conversation explores why law firms can not treat technology adoption as optional. Nishat offers law firm leaders a grounded and strategically honest look at where AI is creating real value. To our listeners: Audio issues during this recording impacted its sound quality, but we're publishing the episode because Nishat's insights are too valuable not to share.

Part two of the conversation with Natsue Ishida dives into the intricacies of governance in Japan and how you can come across opportunities to do pro bono work that expand your area of expertise. Don't miss the beautiful reading of a poem that has had a big impact on Natsue at the end of the episode. If you enjoyed this episode and it inspired you in some way, we'd love to hear about it and know your biggest takeaway. Head over to Apple Podcasts to leave a review and we'd love it if you would leave us a message here!In this episode you'll hear:The difference between Chief Legal Officer (CLO) and General Counsel (GC)Managing what's best for the company and respecting the founder Finding unique ways to contribute to the governance community in Japan and globallyWhat Natsue would say to her younger self Her favourite book and poemAbout NatsueNatsue is a seasoned General Counsel and senior executive with over 20 years of international experience advising senior management, Boards of Directors, and Audit Committees across Asia, North America, and Europe. She brings extensive expertise in legal strategy, IP, compliance, risk management, corporate governance, global subsidiary management, M&A, and data privacy.Her career spans highly regulated industries—including financial services, medical devices, automotive, and gaming—where she has consistently guided organisations through complex regulatory landscapes while shaping strong cultures of compliance and ethical leadership.Natsue is a widely recognised award winning thought leader, deeply committed to advancing excellence within the legal profession.On the weekends, she enjoys rock climbing (shower climbing in the summer). She would like to do more photography (medium format film photo printing), maybe when she retires, if the technology still exists!Connect with NatsueLinkedIn: https://www.linkedin.com/in/theflyingcat/ LinksPart 1: ⁠https://www.catherineoconnelllaw.com/podcast/season-12-ep2-natsue-ishida⁠  Global Council for Responsible AI https://gcrai.ai/ Connect with Catherine LinkedIn https://www.linkedin.com/in/oconnellcatherine/Instagram: https://www.instagram.com/lawyeronair

In this episode of The Buzz with ACT-IAC, we are in conversation with Ratima Kataria, VP of Health and IT Strategy at ICF. We talk about her career journey from satellite communications and semiconductors into federal health, including serving on the government side during COVID-19, and how high-stakes environments shaped her leadership values. Kataria explains ICF's work helping federal agencies modernize at the intersection of enterprise modernization, data strategy, and responsible AI adoption amid fragmented data, legacy platforms, and demand for AI-enabled services. She describes a “think big, start small” approach focused on mission-aligned tech strategy, data governance and interoperability, platform consolidation, and scaling trusted AI use cases.Become a Member | ACT-IAC Summary - A Hole in One with ACT-IACSubscribe on your favorite podcast platform to never miss an episode! For more from ACT-IAC, follow us on LinkedIn or visit http://www.actiac.org.Learn more about membership at https://www.actiac.org/join.Donate to ACT-IAC at https://actiac.org/donate. Intro/Outro Music: See a Brighter Day/Gloria TellsCourtesy of Epidemic Sound(Episodes 1-159: Intro/Outro Music: Focal Point/Young CommunityCourtesy of Epidemic Sound)

Most growing companies are held together by spreadsheets that nobody fully understands — built by someone who left three jobs ago, maintained by someone who doesn't know why it exists, and quietly critical to daily operations. In this episode, Jeff Mains sits down with Garrett Fritz, co-founder of MetaCTO, a fractional CTO firm that helps mid-market companies transform outdated operational processes into custom, scalable software.Garrett breaks down why so many organizations are trapped in the "if it ain't broke, don't fix it" mindset, how AI has lowered the barrier to custom software without eliminating the need for expertise, and when it actually makes sense to build your own tool versus buying off-the-shelf SaaS. He also shares how internal tools can evolve into white-labeled revenue generators — and the most common mistake founders make when they try to take that leap too fast.Whether you're drowning in manual processes, questioning your SaaS spend, or wondering how to implement AI responsibly, this episode delivers a practical, no-hype roadmap.Key Takeaways4:37 — **The #1 operational inefficiency Garrett sees:** Hundreds or thousands of employees running mission-critical operations on a spreadsheet built a decade ago by someone who's since been promoted — and nobody knows why it has the formulas it has. 6:15 — **What "turning spreadsheets into apps" actually means:** MetaCTO embeds in the business, decodes the spreadsheets, understands the workflows, and builds working software that can replace the internal process — or be taken to market as a SaaS product. 7:54 — **Profitable from day one:** Because Garrett and his partner came with a thick Rolodex from 15–20 years in tech leadership, MetaCTO launched with clients already lined up — no burning cash to find product-market fit. 13:27 — **70% of AI POCs never see the light of day:** The excitement dies when teams realize how much effort is involved. MetaCTO's focus is getting those 90%-done prototypes all the way to the finish line. 18:34 — **Build custom vs. buy SaaS — the real decision framework:** After 2–4 weeks embedded in a business, MetaCTO looks at licensing costs, actual feature utilization (often just 2% of the SaaS product), man-hours wasted, and growth trajectory to determine the ROI break-even point. 28:25 — **Niches win:** SaaS isn't dead — it's narrowing. The companies gaining ground are building hyper-specific tools for specific industries (think: Procore, but only for commercial plumbers) where the UI, reports, and workflows are built around exactly how that niche operates. 31:33 — **The #1 mistake when productizing internal software:** Not talking to the second customer. Your problems aren't always everyone else's problems. Validate outside your organization before building for market, or you risk six months of rework when the deltas turn out to be core to the platform. 33:40 — **How to actually quantify the ROI of custom software:** Bake usage analytics into every product from day one. Track utilization, time on platform, transactions processed, and revenue generated — then compare to the man-hour cost baseline captured during discovery. 39:14 — **Responsible AI implementation starts with one rule: Resist "Accept All."** Don't grant admin tokens to AI agents for convenience. Suffer through permissions early so you don't face irreparable reputation or business damage when a bad actor exploits an over-permissioned agent. 41:22 — **The smartest first step for any leader feeling stuck:** Use AI tools like Replit to build a prototype with fake data. Don't try to connect it to real systems — just use it to force yourself through the problem-solving process. Come to the conversation with a working wireframe and you'll skip weeks of expensive discovery.Tweetable QuotesAt the heart of it is some Excel spreadsheet that some employee made 10 years ago — and it is critical to the operation." — Garrett Fritz"70% of AI proof of concept projects have never seen the light of day. It's pretty common to get excited about something and then realize, oh, this is a lot more effort than we thought." — Garrett Fritz"You can't just give a layman a chainsaw and expect to be a carpenter. A little bit of finesse and experience goes a long way." — Garrett Fritz"The niches win. The companies gaining ground are building hyper-specific tools for specific industries — where the UI, reports, and workflows are built around exactly how that niche operates." — Garrett Fritz"We never build it and run away. And as you can imagine, anyone who's created a piece of software has never said 'I'm done' either." — Garrett Fritz"Resist 'Accept All.' Give the AI admin access for convenience, and you're one bad actor away from irreparable damage to your business." — Garrett Fritz"AI is most valuable when it's applied to real business friction — not just trendy experiments or chatbots. Nobody needs another one of those." — Jeff MainsSaaS Leadership Lessons1. Familiarity is the enemy of efficiency. The "if it ain't broke, don't fix it" mentality keeps organizations locked in spreadsheet-driven operations for years — sometimes decades. The pain point has to get big enough to justify change, but by then the cost of switching is enormous. Don't wait for a crisis to modernize.2. The barrier to custom software has dropped — but expertise still matters. AI tools like Replit and Lovable have made it possible for non-developers to prototype software. But there's a massive gap between a 90%-done prototype and a production-ready, secure, maintainable application. Knowing what you're doing still matters.3. Don't buy features you'll never use. Most enterprise SaaS customers use 2% of the product's functionality — but pay for 100% of the license. When your team is only using 2% of the product and only 50% of the people who should be using it actually are, you're compounding inefficiency at every layer.4. Build for the second customer before you build for the market. If you think your internal tool has market potential, validate it with people outside your organization before investing further. Your problems are not automatically everyone else's problems. The cost of discovering core delta requirements after six months of development is enormous.5. Measure everything from day one. Custom software that doesn't have baked-in usage analytics is a black box. You can't demonstrate ROI, you can't justify ongoing investment, and you can't make intelligent roadmap decisions. Instrument every product with utilization metrics, transaction data, and performance monitoring from the start.6. AI governance isn't optional — it's the first conversation. The most dangerous thing you can do is grant your AI agents broad permissions during development and never revisit it. Treat AI like a junior employee: define its scope, limit its access, and require human approval for anything with downstream consequences. Someone always has to be the final buck.Guest Resourcesgarrett@metacto.comhttps://metacto.com/https://www.linkedin.com/in/grfritz/https://www.linkedin.com/in/grfritz/Episode SponsorThe Futureproof Series - https://www.youtube.com/playlist?list=PLfkXKUPZ5xuOqMPR7_gzGybncTtavyR1NThe Captain's KeysSmall Fish, Big Pond – https://smallfishbigpond.com/ Use the promo code ‘SaaSFuel'Champion Leadership Group – https://championleadership.com/SaaS Fuel ResourcesWebsite - https://championleadership.com/Jeff Mains on LinkedIn - https://www.linkedin.com/in/jeffkmains/Twitter - https://twitter.com/jeffkmainsFacebook - https://www.facebook.com/thesaasguy/Instagram - https://instagram.com/jeffkmains

Episode #5 of Empathy in the Age of AI, a special 25-part series: https://tinyurl.com/exyw2nua AI is impacting every part of our lives—and we need to start paying more attention.Listen to this powerful conversation with Valentine Goddard, founder of the AI Impact Alliance, whose work sits at the intersection of Responsible AI, governance, art, and human rights.We discuss:How AI is reshaping culture and civic life and why we need responsible AI governanceThe need to protect human agency in a world increasingly influenced by machinesWhy art and civic engagement are essential to preserving our humanityWhat citizens need to know about political bias baked into AI systemsUNESCO's role in developing human-centered AI governanceWhy empathy and democracy are at risk in the age of AIIf you care about protecting democratic freedoms, human creativity, cultural knowledge, and our shared humanity — you don't want to miss this conversation.00:00 Preview00:46 Episode Introduction02:49 About Valentine Goddard05:49 Valentine's backstory12:49 About the AI Impact Alliance (AIIA)14:02 Why civic engagement is urgently needed to shape AI governance19:21 What does “human-centric AI” mean?23:35 How kids may lose their “cognitive freedom/agency” to AI28:53 The risks of AI companions and tutors33:34 How can art inform AI ethics and policy?37:12 Using art to reclaim agency in the age of AI43:28 Are there political biases in ChatGPT, Perplexity and Claude?45:16 The risks of “artificial intimacy” 49:17 What happens when AI starts shaping human thought?51:32 How does fake information on AI systems pose national security risks?01:00:12 UNESCO Report: Protecting cultural data in the age of AI01:10:50 Valentine Goddard's Purposeful Empathy storyCONNECT WITH VALENTINE✩ LinkedIn https://www.linkedin.com/in/valentine-goddard-a4123a1/✩ Website https://www.valentinegoddard.com/✩ AI Impact Alliance https://www.allianceimpact.org ✩ Instagram https://www.instagram.com/gabelle✩ X https://x.com/vavacolorCONNECT WITH ANITA✩ Email purposefulempathy@gmail.com ✩ Website https://www.anitanowak.com✩ Buy a copy of Purposeful Empathy http://tiny.cc/PurposefulEmpathyCA✩ LinkedIn https://www.linkedin.com/in/anitanowak/✩ Instagram https://tinyurl.com/anitanowakinstagram✩ Podcast Audio https://tinyurl.com/PurposefulEmpathyPodcast✩ Bluesky https://bsky.app/profile/anitanowak.bsky.socialSHOW NOTES✩ Algorithmic Frontiers https://www.algorithmicfrontiers.com/✩ Une Vie Intelligente https://duceppe.com/une-vie-intelligente/✩ Perplexity https://www.perplexity.ai/✩ Claude https://claude.ai/login✩ ChatGPT https://chatgpt.com ✩ Democratic Infrastructure for Creative Futures: Building the AI, IP & Culture Repository – UNESCO Report https://ai-update.co.uk/2026/05/01/democratic-infrastructure-for-creative-futures-building-the-ai-ip-culture-repository-unesco/?utm_source=chatgpt.comVideo edited by Jad Misri, Green Horizon Studio

Somewhere in your organization, an AI decision is sitting on someone's desk right now. Who owns it? In most mid-market companies, nobody does — or rather, it's landed on the IT leader who was already doing three other jobs.In this episode of The Catalyst, we follow Jeremy Wight, CTO of CareMessage — a patient engagement platform serving 22 million low-income patients across the US — who had to write his organization's AI policy himself. No committee. No playbook. Just the weight of getting it right for some of the most vulnerable people in the healthcare system.Alongside Jeremy, we hear from Reid Blackman, author of The Ethical Nightmare Challenge and founder of Virtue, who argues that the standard policy-first approach to AI governance is already broken — and offers a framework any team can implement in weeks, not years. Olivia Gambelin, AI ethicist and author of Responsible AI, reframes the vendor selection question entirely: it's not about auditing their product, it's about whether their values align with yours. And Anthony Vinci, former intelligence officer and author of The Fourth Intelligence Revolution, draws an unexpected parallel — between the integrity required of a spy with no rulebook, and the integrity required of an IT leader doing the same.====This episode is brought to you by HPE.From AI to data center and network modernization, HPE delivers a cloud-like experience right on your own infrastructure — the full portfolio, from one partner. softchoice.com/technology-partners/hewlett-packard-enterprise ====In this episode:Why the policy-first approach to AI governance is broken — and what to do insteadA practical three-question framework any team can implement this weekHow to evaluate AI vendors by values alignment, not just product capabilityWhat it actually looks like when one IT leader has to make these calls alone — with 22 million patients on the lineFeatured guests: Jeremy Wight (CTO, CareMessage) • Reid Blackman (Founder/CEO, Virtue) • Olivia Gambelin (AI Ethicist & Author) • Anthony Vinci (CEO, VICO) • Craig McQueen (VP Microsoft Practice, Softchoice)#AIEthics #ResponsibleAI #ITLeadership #AIGovernance #TheCatalyst #Softchoice #MidMarket #HPE===Show Notes & ResourcesGuestsJeremy Wight, CTO — CareMessage: caremessage.orgReid Blackman, Founder/CEO — Virtue: reidblackman.com • The Ethical Nightmare Challenge (book, April 2025) • Ethical Machines (HBR Press, 2022)Olivia Gambelin, AI Ethicist: oliviagambelin.com • Responsible AI: Implement an Ethical Approach in Your Organization • Values Canvas framework — free download at oliviagambelin.comAnthony Vinci, CEO — VICO: anthonyvinci.com • The Fourth Intelligence Revolution (Henry Holt, 2025) • VICO forecasting platform: vico.aiCraig McQueen, VP Microsoft Practice — Softchoice, a World Wide Technology CompanySponsorHPE via Softchoice: softchoice.com/technology-partners/hewlett-packard-enterpriseSoftchoice AI & Ethics resources: softchoice.com/EASThe Catalyst by Softchoice is the podcast dedicated to exploring the intersection of humans and technology. 

98% of patients welcome AI in their care — and still want a human in charge. That tension ran through the OECD and Spanish Ministry of Health conference on scaling AI in health (Madrid, late May 2026), and it frames this episode of Faces of Digital Health. Out of 38 OECD countries, only seven have a formal AI strategy and just over a tenth run workforce upskilling programmes — the ambition is outrunning the institutions meant to govern it. Host Tjaša Zajc brings together voices from across the conference to ask what actually has to change: regulation, trust, who gets a seat at the table, and the parts of the agenda nobody is funding. Featuring: - Eric Sutherland — Senior Economist, OECD - Aferdita Bytyqi — Executive Director & Founding Partner, Digital Transformations for Health Lab (DTH-Lab) - Erza Selmani — Research Fellow, DTH-Lab - Valentina Strammiello — Executive Director, European Patients Forum (EPF) - Dr Ricardo Baptista Leite — CEO, HealthAI (the Global Agency for Responsible AI in Health) - Dr Persephone Doupi — Senior Medical Officer, Finnish Institute for Health and Welfare; President, European Federation for Medical Informatics (EFMI) What the conversation covers: - Why trust — not capability — is the binding constraint on health AI adoption - The OECD readiness gap: AI strategies, HTA frameworks and workforce upskilling - How patients really feel about AI: consent forms, transparency, and keeping clinicians central - Why youth health and wellbeing keep getting left out of AI governance frameworks - Five recommendations to make the EU AI Act work for health and competitiveness - Coordinating the EU AI Act, MDR/IVDR and the European Health Data Space - Health technology assessment and reimbursement as the real barriers to scale - AI literacy and prevention: the most underweighted lever in the room Chapters: 0:10 — Welcome: AI in Health & the 2026 OECD Conference in Madrid 0:25 — Key Stats: Only 7 of 38 OECD Countries Have a Formal AI Strategy 2:10 — Eric Sutherland (OECD): We're Not Using Data as Effectively as We Could 3:11 — Afrodita & Erza (DTH Lab): Youth Health Is Missing from AI Governance Frameworks 5:12 — Valentina Stramello (EPF): 98% of Patients Are Positive About AI, But Trust Requires Transparency 7:14 — Dr. Ricardo Baptista Leite (Health AI): 5 Recommendations to Fix EU AI Policy for Health 10:53 — Persephone Doupi (EFMI): We Must Prioritize AI Literacy and Shift Healthcare Toward Prevention —

0:30 - Midterms 13:03 - Sheridan Gorman's parents at status hearing for their daughter's killer on sanctuary pols in IL 34:23 - Henry Nowak's father outside courthouse post-conviction of son's killer 51:47 - Menahem Merhavy, senior fellow at the Harry Truman Institute at the Hebrew University of Jerusalem, breaks down Why Iran’s regime did not collapse 01:04:29 - In-depth History with Frank from Arlington Heights 01:08:06 - Platner 01:20:47 - Pistols and Pilates 01:25:48 - Wirepoints founder Mark Glennon on what it would take to get a Spencer Pratt-like candidate in Chicago. 01:43:09 - Targeting speeders in NYC 02:06:29 - David Krueger, assistant professor in Robust, Reasoning, and Responsible AI at the University of Montreal and founder of Evitable, warns that the risks posed by artificial intelligence are real—and cannot be ignored. Follow David on X @DavidSKruegerSee omnystudio.com/listener for privacy information.

From McDonald's drive-thru meltdown to hiring and banking algorithms discriminating against women, AI failures are already happening in 2025.In this video, I break down how to implement Responsible AI that protects your brand, your customers, and your future.You'll learn: the real-world AI disasters and what caused them, how to build an AI governance framework that actually works, 4 critical steps every organization must take today, how to create transparency, accountability, and trust in your AI systems.Because Responsible AI isn't just a buzzword- it's your survival skill.Looking to go from chaos and unpredictability to resilience in the world of AI? Start here with The Predictability Factor newsletter at The Monica Talks Cyber (https://www.monicatalkscyber.com).

How do you stay in control of AI while still benefiting from everything it can do? As AI becomes more powerful, many leaders are focused on getting AI to do more work. But perhaps the better question is: How do you make AI more effective without letting it influence your thinking, your brand, or your business direction? In this episode of Grounding AI, Donna Peterson explores why leaders must remain the decision-makers while using AI as a tool to strengthen expertise, deepen customer relationships, and improve business outcomes. You'll learn why AI should enhance your knowledge rather than replace it, how to train AI around your company's goals and values, and the questions every leader should ask before using AI-generated recommendations. If you're responsible for marketing, sales, leadership, customer relationships, or business strategy, this episode offers practical guidance for maintaining control while leveraging AI effectively. In This Episode: Why AI naturally influences decisions and direction The difference between getting AI to do more and getting AI to be more effective How leaders can maintain ownership of their expertise Why your brand voice must remain stronger than AI suggestions The importance of building AI libraries and organizational knowledge Questions to ask before every AI prompt How to keep customer relationships at the center of AI adoption A simple test to determine if AI is helping or leading your business Key Takeaway Before every prompt, ask yourself: What am I trying to accomplish? Why does it matter to my audience? What action do I want people to take? Does this align with our company values and goals? The more direction you provide, the more valuable AI becomes. Connect With World Innovators // Website: www.worldinnovators.com Subscribe for weekly conversations on AI, leadership, trust-building, marketing strategy, and practical business growth. *** Reach out to dpeterson@worldinnovators.com if you'd like help building a marketing strategy that builds relationships and/or AI training for individuals or full teams.*** Visit www.worldinnovators.com for more resources on building stronger marketing and leadership strategies.*** Subscribe to the Grounding AI podcast for weekly insights into marketing, leadership, and the future of AI.

What does “responsible AI” look like in practice? In one of our most engaging episodes of the year, host Will Francis speaks with  Gordon Ryan, Senior Managing Consultant and Design Process Lead at Sopra Steria, about the growing impact of AI on work, business, and society, and the hidden trade-offs behind its adoption. From the future of design and marketing to productivity and identity, Gordon shares his perspective on where AI could take us next, and whether we're building the kind of future we want. Gordon's top 3 tips for responsible strategic use of AI: Reflect on what you value most in your work: Identify the parts of your role that feel meaningful and uniquely human Use AI intentionally: Focus on solving real problems instead of adopting tools simply because they're available Think beyond productivity: Consider how AI could improve wellbeing, relationships, creativity, and quality of life at work The Ahead of the Game podcast is brought to you by the Digital Marketing Institute and is available on YouTube, Apple Podcasts, Spotify, and all other podcast platforms. And if you enjoyed this episode, please leave a review so others can find us. If you have other feedback or would like to be a guest on the show, email the podcast team!  Timestamps: 0:01:57 – What systems-oriented design means 0:04:31 – UX design, digital experiences and systems thinking 0:05:10 – Will AI replace designers? 0:08:24 – Creativity, craft and the human side of design 0:09:24 – Are companies adopting AI without a clear strategy? 0:11:37 – The “Wild West” of AI inside organizations 0:14:41 – Gordon's most practical uses of AI today 0:16:00 – Using AI to analyze complex environmental and forestry data 0:18:36 – The human impact of automation and lost relationships 0:21:13 – What ethical AI really means beyond compliance 0:22:41 – Productivity, profit and the future of work 0:26:12 – Why business growth can't continue forever 0:30:18 – Is Gordon optimistic or skeptical about AI? 0:31:30 – AI, inequality and the environmental crisis 0:34:59 – Reconciling AI's benefits with its environmental impact 0:36:00 – Could AI enable shorter working weeks? 0:39:36 – The future of marketing and behavioral manipulation 0:45:50 – Marketing, persuasion and ethical responsibility 0:46:37 – How to use AI more mindfully 

What does it take to implement AI responsibly? In this episode of AI Now, host Bryony Evans is joined by Fernando Mourão, Head of Responsible AI at SEEK, alongside Mallesons partner Michael Swinson. Hear lessons from a leading organisation that has been building since 2019, including how to move beyond compliance-driven approaches and put people first in AI transformation.Key topicsMoving beyond compliance (6:30)Setting the right pace for AI adoption (11:20)Don't wait for regulation - focus on your AI systems (15:05)Guidance (including in Singapore and Australia) that can help (17:20)Inside SEEK's responsible AI journey (18:45)Lifting AI governance maturity and enabling innovation (20:40)

In this episode of the Healthy Wealthy & Smart Podcast, Dr. Karen Litzy, PT, DPT, welcomes Dr. Minal Patel and Brijraj Bhuptani of Spry Therapeutics. We explore how AI is transforming clinical workflows, documentation, and patient care in physical therapy. We cut through the hype to understand what responsible AI integration really means for clinicians and practice owners.   Key topics   The origins of Spry and the real-world problems AI aims to solve in healthcare How AI-powered documentation like Spry's Scribe tool works in practice The importance of transparency, data security, and reliability in healthcare AI Balancing customization and standardization with AI tools The role of AI in addressing clinician burnout and administrative burden Future pathways: AI's potential to standardize workflows while respecting individual practice styles Practical steps for clinicians and practice owners to start exploring AI in their clinics Evolving perceptions of AI's impact on human interaction and empathy in therapy   Timestamps   00:00 - Introduction to AI in clinics and why it matters 02:16 - The story behind Spry's inception and industry pain points 04:44 - How COVID accelerated the need for smarter workflows 09:11 - Overcoming practice ownership inertia toward new technology 12:06 - The role of AI-powered documentation and clinician workflows 18:15 - How Spry's AI listens and transcribes in real-time during therapy 24:09 - Protecting note integrity and avoiding homogenized documentation 27:51 - The impact of admin overload on clinician burnout and patient trust 36:17 - Building trust in AI with transparency and data access 40:48 - The future of AI: opportunities and responsibilities for practice owners 43:20 - Responsible AI and industry responsibility for ethical tech deployment 47:40 - Clarifying probabilistic AI and ensuring reliable clinical outputs 48:43 - Lightning round: quick takes on practice management and AI mindset 55:09 - How to connect with the experts and learn more about Spry   Resources & Links Spry Brij Bhutani - LinkedIn Dr Minal Patel - LinkedIn AI-powered documentation in healthcare: a look at Spry's approach   More About Dr. Patel: Dr. Minal Patel PT, DPT, OCS is a seasoned Physical Therapist with over 17 years of clinical and non-clinical expertise. She has held pivotal roles within rehab organizations including leadership and innovation for both in-person and digital services. Dr. Patel holds a Doctor of Physical Therapy from Midwestern University, and is an Orthopedic Certified Specialist. As Director of Clinical Solutions at SPRY, Dr. Patel leads the development and implementation of innovative care strategies that bridge the gap between clinical excellence and operational efficiency. With a deep background in physical therapy and healthcare operations, Dr. Patel brings a clinician-first perspective to building solutions that streamline workflows, optimize patient outcomes, and enhance revenue cycle performance. At SPRY, Dr. Patel works closely with product, engineering, and customer success teams to ensure the platform supports the real-world needs of outpatient therapy practices. Their work focuses on translating clinical insight into scalable technology—empowering providers to deliver high-quality care while navigating complex payer and compliance environments. Prior to joining SPRY, Dr. Patel held leadership roles in multi-site rehab networks and has been instrumental in driving clinical innovation, EMR optimization, and value-based care initiatives. She is passionate about elevating the role of therapists in the broader healthcare ecosystem through data-driven, patient-centered tools. More About Brijraj: Brijraj (Vaghani) Bhuptani is co-founder and chief executive officer of SPRY Therapeutics, Inc., inventor of rehab therapy's first fully integrated, AI-powered EMR. As CEO, Brij drives company and product strategy as he leads the organization in the commercialization of rehab therapy's only AI-first software platform. Before SPRY, Brij co-founded and served as chief executive officer of Birds Eye Systems, the creator of major mass transit platform Ridlr. This enterprise was acquired by Ola, one of the world's largest ride-hailing companies, where Brij then served as chief technology officer. Prior to Birds Eye Systems, Brij applied his engineering background to solving some of the most pressing technology concerns facing large media and wireless firms, including Qualcomm and Sears India. For more information on SPRY, visit www.sprypt.com, and follow the company on LinkedIn Jane Sponsorship Information: Book a one-on-one demo here Mention the code LITZY1MO for a free month   Follow Dr. Karen Litzy on Social Media: Karen's Instagram Karen's LinkedIn   Subscribe to Healthy, Wealthy & Smart: YouTube Website Apple Podcast Spotify SoundCloud Stitcher iHeart Radio

Companies are making the exact same mistake with AI that they made with cloud. FICO's CIO Mike Trkay breaks down why 95% of companies are failing at AI alignment, why "automating a bad process faster" is the #1 trap, and why regulated industries are already abandoning LLMs in favor of focused language models.   Key takeaways: • Only 5% of AI pilots make it to production — and MIT's research backs it up • The lift-and-shift parallel: cloud costs went up for the same reason AI ROI is missing • Why the LLM-to-focused-language-model shift mirrors cloud-native vs lift-and-shift • What "AI native" actually means (and why chatbots aren't it)   Chapters 00:00 The 5% Alignment Problem 01:09 Only 7% Even Measure If Their AI Works 02:15 "You're Just Doing a Bad Process Faster" 06:29 LLM Repatriation and the Rise of Focused Language Models -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Understand how to close the gap between AI experimentation and enterprise production. Shub Agarwal, Founder of the AI Trust Lab at USC and author of Successful AI Product Creation: A Nine-Step Framework, shares his AI product management framework for taking enterprise AI strategy from demo to production, drawing on two decades of product leadership at Amazon and Fortune 50 firms. He breaks down why experimentation must tie directly to business OKRs, the four mindset shifts leaders need to scale AI responsibly, and how the AI Trust Lab is building a benchmark evaluation framework for AI model trust and governance. Key Moments: Why 80% of AI Projects Never Reach Production (02:13): Shub traces the root cause of stalled AI programs to a missing system for moving from demo to deployment. Most teams have no repeatable path to production. Shub's Nine-Step Framework for Building AI Products (06:00): Most AI projects start with a cool model instead of a painful problem. Shub walks through the three phases of his framework: discovery, execution, and excellence. The Case Against "Fix Your Data First" (12:41): Conventional wisdom says clean your data before building AI. Shub challenges that, arguing modern LLMs offer far more flexibility with imperfect data. Four Mindset Shifts for Scaling Enterprise AI (16:35): Shub outlines the four shifts separating organizations that scale AI from those that stall, from measuring AI performance differently to embedding trust from day one. Inside Shub's AI Trust Lab at USC (23:54): Major foundation models are already being benchmarked on trust and safety. Shub explains the lab's mission to build a standardized evaluation framework for AI model governance. Why Enterprise AI Governance Needs Multiple Disciplines (28:36): AI models can be sycophantic, manipulative, or lack candor. Shub argues that building trustworthy AI demands an interdisciplinary approach. Key Quotes: “I think the fundamental problem that organizations are facing today… is not that they have a lack of experimentation in the demo aspect. The challenge is they don't know how to take those demos to production, and that is where I saw the gap.” - Shub Agarwal “I do think data is the fuel for AI… But I think today organizations are crippled by this ‘fix your data, and then we'll build AI', and they never build AI. They never build use cases that are adding value.” - Shub Agarwal “There's no FICO scores for models, so I decided to create one. I built this lab… bringing the computer scientists, the researchers, the applied AI researchers, the policy, and the communication people together to think of what is trust, define it, and ultimately measure and evaluate it.” - Shub Agarwal Mentions USC AI Trust Hub Successful AI Product Creation: A Nine-Step Framework by Shub Agarwal Four Steps to Epiphany: Successful Strategies for Products That Win by Steve Blank Masters of Scale podcast with Reid Hoffman Guest Bios  Shub Agarwal is an associate professor of professional practice at the University of Southern California, an industry executive, and an advisor to start-ups and academic institutions. He holds an MBA from the University of California, Los Angeles (UCLA), and an MS from Carnegie Mellon University (CMU). He is the author of two books: Solve Catch-22 of Product Management and Successful AI Product Creation: A 9-Step Framework. He has made significant contributions to the fields of artificial intelligence and machine learning, holding several U.S. and global patents for his work, and is also a published author of several technical research papers. With around two decades of extensive experience in product management and leadership, his journey has been marked by a relentless pursuit of leveraging AI technologies to create impactful products that redefine industry standards. His industry experience includes leadership roles at Amazon, Silicon Valley start-ups, and other Fortune 50 firms. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Olga Goriunova rejects digital abstractions as mirror images of ourselves and reflects on why we concern ourselves with representations that aren't concerned about us.  Olga and Kimberly discuss how cultural imagination is shaped by technology; digital subjects as unnatural constructs; the distance between individuals and their digital profiles; banal categorization and subjective truth; how statistics and ML changed the concept of the ideal; the limits of digital subjects; extreme individuation and aspiring to become our digital reflections; how current predictions create future realities; why the ideal digital subject isn't concerned with you; and thinking critically about what we desire and why. Olga Goriunova is a cultural theorist working at the intersection of technology, philosophy, and aesthetics. A Professor of Media Arts at Royal Holloway, University of London, Olga is the author of the critically acclaimed book Ideal Subjects: The Abstract People of AI. Additional Resources: Aksioma: Institute for Contemporary Art Book Lecture  Olga Goriunova Academic Profile  A transcript of this episode is here. 

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the critical definition and requirements for navigating Enterprise AI. You’ll learn how to distinguish between consumer-grade tools and the strict standards required in regulated industries. You’ll discover the twenty essential pillars for building a secure and compliant AI strategy for your organization. You’ll understand why rigorous vendor scrutiny matters as much for software as it does for human talent. You’ll gain clarity on the governance frameworks necessary to prevent data leaks and legal vulnerabilities in your enterprise. 00:00 – Introduction 03:15 – Defining Enterprise AI vs. SMB AI 07:45 – The role of Microsoft Copilot in regulated environments 12:20 – The 20 components of Enterprise AI readiness 18:10 – Challenges in organizational adoption and change management 22:30 – Security and data privacy as the foundation 27:00 – Call to action Watch this episode to master the complex landscape of regulated AI and safeguard your company’s future. Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-enterprise-ai-101.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week’s In Ear Insights, we are talking about Enterprise AI 101. I am in the midst of a series in the Trust Insights newsletter, which you can get at TrustInsights.ai/newsletter. Part one was last week on seven different aspects of enterprise AI. But Katie, you said it would probably be helpful to level set what enterprise AI is and how it differs from SMB AI, mid-market AI, consumer AI, and so on. Katie Robbert: It is interesting because I feel like every time we jump on to record a podcast, there is a whole new set of vocabulary that I need to get caught up with. We need to make sure that everyone else knows what we are talking about because there is nothing worse than listening to a podcast or reading an article and having no idea what the author is talking about because they are introducing a concept but not really explaining it. I wanted to take this episode to talk about what enterprise AI is. Since you and I have not defined it, I am going to take my best guess at what enterprise AI is using some logic and deduction. I could be wrong, and that is why I think it is worth covering. From my perspective, if I had to put a definition to it, I am assuming enterprise AI is the type of AI implementation that occurs at an enterprise-size company. That sounds overly simplistic, but the bigger the organization, the more red tape, the more politics, the more departments, the more stakeholders, and the more governance there is. There are a lot more complications versus a small business like we are, where we can just decide one day, “Hey, I am going to start using this tool.” There are no real hurdles to go through. Then you have those mid-sized companies where you start to introduce some of those hurdles. You might need to work with your IT team to make sure that everything is in compliance. You might need to make sure that you have a place to host these new pieces of software, and that is not something that the marketing team is necessarily responsible for. Then you get to the enterprise-size companies where everything is completely siloed. Even in the best enterprise-sized companies, you are going to run into these silos. Because no one person is responsible for everything, you typically have multiple CEOs. Depending on what part of the country you are in, you might have a board for every different division of the company. If you are a Procter & Gamble and you have hundreds of product lines underneath, each of those is their own individual business. Each of those businesses are not necessarily talking to each other or sharing resources. That is my logical guess at what enterprise AI is. Christopher S. Penn: That is what I started with until I started doing the research into it. I realized that is not what it is. The generally accepted definition is AI within any commercially regulated entity. I realized as I was going through the research that commercially regulated means you have external regulation imposed on the company. It might be a 50-person company, but if they work in HIPAA or FINRA, they have to behave in highly regulated ways. Whether you are publicly traded or, for example, colleges that have to adhere to FFIEC rules and FERPA rules, enterprise AI is about operating AI—whether classical or generative—in a commercially regulated environment where you have externally mandated requirements that you must meet. Your definition for small business stuff makes total sense in that environment because Trust Insights is not a regulated company. However, when we work with our healthcare clients, we have to behave as though we are an enterprise company because we have to conform to their requirements. Katie Robbert: I am glad we are talking about this because the terminology is confusing; when you think of an enterprise company, you are not thinking of a commercially regulated company. I have to wonder why it is not called commercially regulated AI versus non-commercially regulated AI. It is a mouthful and a little bit harder to remember, but it is more descriptive and more accurate. I think like me, a lot of people are going to get confused about what enterprise AI actually is. Christopher S. Penn: A lot of this is because our background is in marketing, so we use the term enterprise to just mean a big company. If we want to market to enterprise companies, we are not marketing to a 50-person firm; we are marketing to a 50,000-person firm. In a lot of CRM software, the dividing line is typically 10,000 employees or 100 million in revenue. This is especially relevant because you see a lot of AI companies like Anthropic and OpenAI in a fight with Microsoft to try and gain a foothold into those enterprises. Microsoft, with their Copilot offering, has dominance by the very fact that their legacy Office 365 stuff is approved in those regulated environments. Katie Robbert: It is ironic because we spent so much time admittedly dismissing Microsoft’s Copilot as the less than version of generative AI, and now Microsoft is getting the last laugh on everyone. They are saying, “You have to use me because I have already been approved by IT and governance, and good luck.” You are stuck with whatever I decide to give you. If I were Microsoft, I would be petty and say, “You guys spent way too much time dismissing me and calling me inferior, so too bad.” Christopher S. Penn: A lot of that, as we have talked about many times on stage, is that the reason Copilot has fewer capabilities than other systems is specifically because of the regulated environment. It is trivial for Google to foist something on consumers and say, “Now we are going to read all your Gmail.” That does not fly in a regulated industry. Katie Robbert: That understanding is really helpful to the people who are saddled with Microsoft Copilot because we hear complaints about why they cannot use other shiny objects. If you are in a 50,000-person company and you weren’t there when the regulatory standards were decided upon, you are sitting there wondering why you cannot use Gemini to generate ad headlines. Then you do it on the side and get in trouble because there is no clear documentation saying why you have to use Copilot and nothing else. What we are hearing is that employees in companies required to use Microsoft Copilot are using other models on the side. That information is still getting filtered into the organization, and it is a huge governance problem. Christopher S. Penn: Completely. In enterprise AI, there are 20 different components to being ready. I derived this from the US federal government's NIST AI regulations and the EU AI Act, which is the gold standard. Katie Robbert: I want to see if you can get all 20. Christopher S. Penn: One, Strategy and Operating Model; two, Governance Policy and the AI Council; three, Legal, Regulatory, and Compliance. Katie Robbert: Are you reading this off a screen? Christopher S. Penn: I am 100% reading this off the Trust Insights Enterprise AI Landscape Field Handbook. Katie Robbert: Fine, continue. Christopher S. Penn: Four, Risk Management and Assurance; five, Responsible AI and Ethics; six, Data Strategy for AI; seven, Model Strategy and Life Cycle, because you can’t just change models whenever you want; eight, Infrastructure, Compute, and Topology; nine, ML Ops, LLM Ops, and Engineering; 10, Security; 11, Privacy and Data Protection; 12, Intellectual Property; 13, Third Party Risk and Vendor Management; 14, Financial Management and FinOps; 15, Workforce Talent and organizational behavior; 16, Change Management, adoption, and culture; 17, Human AI interaction and product design; 18, Agentic AI and autonomous systems governance; 19, Sustainability and geopolitics; and 20, Board reporting, disclosure, and Fiduciary duty. Katie Robbert: I just heard a whole lot of new job opportunities listed. So, if someone were working in a regulated industry like pharma, these are the 20 things they would need to be aware of before evaluating generative AI. It is interesting that organizational behavior and change management are part of it. You would think the regulations would be more technical versus human, but I am surprised that is part of it. Christopher S. Penn: It makes sense because in order for any AI to succeed in an enterprise with 50,000 or 300,000 employees, you have to prioritize change management. Organizational behavior cannot be an add-on; they have to be baked into what you do from the beginning, otherwise your initiative is going nowhere. Katie Robbert: I don’t disagree, but the typical way that works in a large organization is top-down. They make a decision, and you walk in the next day to find it has automatically updated your computer settings. Now you can no longer use a web browser search; you have to use Microsoft Copilot. That is their version of change management, but it is really just a dictatorship from above. I am interested in future episodes to explore what that should look like in a regulatory environment. Christopher S. Penn: We have known for two years that adoption is the hardest part. Deployment is easy compared to adoption. You can put Copilot on someone's desk, but they may not use it even if you tell them they have to. It comes back to how you get them to see the benefits. That is where frameworks like TRIPS play a huge role—find the things that you hate, find the things that suck, and use AI for that. Get that one thing off your plate. Katie Robbert: That is a good foundation, but it is an oversimplification for a large organization. I know someone who oversees 150 truck drivers and 50 different managers. The layers are so deep. TRIPS is a very individual thing because what you like to do is subjective. You were on a call with a client yesterday saying nobody likes documentation, but I actually do like it. My scoring would look different than yours. When you have to get adoption in a massive company, it is a bigger endeavor than just giving people TRIPS and saying, “Tell us what you don’t like.” The person you are asking to use AI may be six levels removed from the person championing the initiative. Christopher S. Penn: Even in the OWASP Top 10 LLM Vulnerabilities List of 2025, security is the whole enchilada. Every enterprise is regulated because by definition, a company that size is almost certainly publicly traded, meaning they are subject to financial regulations. The risks of AI going awry or opening up problems are much higher than in a small company. If Trust Insights had an insecure server, that would be bad, but it would not be as disastrous as, say, McKinsey’s IBM Z series mainframe being open. Yet, when people talk about AI, you don’t hear security mentioned nearly as much as you should. Katie Robbert: It is true. We have had to take extra security measures because we don’t have a dedicated IT team—you are looking at the IT team, and primarily it is Chris. We don’t have any wiggle room to set things up haphazardly. We have to do it right from the start. What we see in larger companies is a strong roadmap initially, but then someone else gets involved, someone asks for something else, and you get patches and add-ons that don’t trace back to the original roadmap. By the end, you are wondering what the original goal was. The bigger the organization gets, the harder it is to maintain control. It becomes a snowball effect. Christopher S. Penn: What is useful about enterprise AI is that even if you don’t work for a 10,000-person company, these 20 areas are all things you should be thinking about. Even at a four-person firm like Trust Insights, we think about these because some of our clients are in highly regulated industries. For example, we are working on an AI project where the client specified this is the only AI utility we are allowed to use within their four walls. Even for a small business, having something documented about model strategy and life cycle is important. As of the day we are recording this, Google Gemini 3.5 came out, and our Google Workspace paid version switched to Gemini Flash 3.5. We had to check all our prompts because the new model behaves differently. Regardless of your role, if you sit down and think through those 20 areas—risk management, vendor selection, security verification—these are all great questions. Katie Robbert: There is a good starting place for this. You can find our downloads at TrustInsights.ai/StrategicToolkit. There is also a free version at TrustInsights.ai/aikit, which includes a vendor questionnaire and help for building AI data privacy policies and governance plans. We have already templated these things out. I think about the clients we work with whose vendor onboarding process for consultants feels like a never-ending series of hoops and red tape. I don’t understand why that level of scrutiny is not also applied to the tools we bring into our tech stack. We are renting space in those tools and freely giving them our data. Those companies now have our data and will use it for their own benefit. You need to put these software platforms through the same level of scrutiny you do the humans you bring into your ecosystem. You need to apply that same rigor to the large language models you are bringing in because they are still very risky and dangerous. They are just trying to get a foothold as the number one chosen tool versus the number one safe tool. Christopher S. Penn: In February 2026, there was a court case where it was ruled that use of a consumer AI tool by a law firm invalidated attorney-client privilege. The judge ruled that this is no longer privileged information. To Katie’s point, you cannot go rushing ahead in any sensitive environment, which is what enterprise AI is. You have to be doing your homework. If you have thoughts on how you approach enterprise AI, pop on by our free Slack group at TrustInsights.ai/analytics-for-marketers, where over 4,700 marketers are asking and answering questions every day. Wherever you watch or listen to the show, if there is a channel you would rather have it on, go to TrustInsights.ai/tipodcast. Thanks for tuning in; we will talk to you on the next one. Katie Robbert: Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Our services span the gamut from developing comprehensive data strategies and conducting deep-dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology, Martech selection and implementation, and high-level strategic consulting. Encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, DALL-E, Midjourney, Stable Diffusion, and Meta Llama, Trust Insights provides fractional team members such as a CMO or data scientists to augment existing teams. Beyond client work, Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the In-Ear Insights podcast, the Inbox Insights newsletter, the So What? livestream webinars, and keynote speaking. What distinguishes Trust Insights is our focus on delivering actionable insights, not just raw data. We are adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models, yet we excel at explaining complex concepts clearly through compelling narratives and data storytelling. This commitment to clarity and accessibility extends to our educational resources, which empower marketers to become more data-driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you are a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

City leaders are eager to deploy AI, but the real opportunity lies in preparation: building the right organizational structures, expertise, and culture first. Host Stephen Goldsmith speaks with Teddy Svoronos, senior lecturer in public policy at the Harvard Kennedy School, about how to structure your city government for Agentic AI, why small, empowered teams work better than broad rollouts, and what mental models and skills leaders actually need to manage this new relationship with AI tools. In this episode, you'll learn: Why creating a data-driven culture before AI deployment is the critical first step How to start with a small, driven team to stress-test AI capabilities in your organization What "cognitive debt" means and why managing it prevents costly AI mistakes Why domain-specific expertise becomes more important, not less, as AI gets more powerful How to balance the tension between AI utility and maintaining organizational control What guardrails, monitoring, and evaluation mechanisms cities need in place from the start Guest: Teddy Svoronos – Senior Lecturer in Public Policy, Harvard Kennedy School Listener Survey: bit.ly/datasmartpod Music credit: Summer-Man by Ketsa About Data-Smart City Solutions Data-Smart City Solutions, housed at the Bloomberg Center for Cities at Harvard University, is working to catalyze the adoption of data projects on the local government level by serving as a central resource for cities interested in this emerging field. We highlight best practices, top innovators, and promising case studies while also connecting leading industry, academic, and government officials. Our research focus is the intersection of government and data, ranging from open data and predictive analytics to civic engagement technology. We seek to promote the combination of integrated, cross-agency data with community data to better discover and preemptively address civic problems. To learn more visit us online and follow us on LinkedIn.

Sichere dir jetzt deinen Platz in unserem kostenlosen KI Spotlight “Mental Overload endlich adé” am 28. Mai um 11:00 Uhr! Wir stecken mitten in einer technologischen Disruption: Über 80% der Unternehmen weltweit nutzen bereits KI-Tools. Jetzt steht der nächste riesige Sprung kurz bevor: Agenten und Agentic AI.In dieser Folge mit unserer Dozentin und KI-Beraterin Zamina Ahmad erfährst du:Agentic AI: Was autonome KI-Agenten wirklich von einfachen Custom GPTs unterscheidet.Der Klarna-Effekt: Warum reine Automatisierung ohne Empathie scheitert und wie die perfekte hybride Zusammenarbeit aussieht.Rollenverschiebung: Warum du in Zukunft weniger selbst codierst oder textest, sondern zur strategischen Qualitätsprüferin wirst.Human in the Loop: Wie du durch klare Quality Gates und Feedback-Schleifen die Kontrolle über deine Governance behältst.Experimentierräume: Wie du als Führungskraft psychologische Sicherheit schaffst, um gemeinsam statt einsam mit KI zu lernen.Prozessliebe: Mit welcher einfachen Frage du deine tägliche Arbeit mithilfe von KI heute komplett neu erfinden kannst.Zamina teilt ihre Geheimtipps für KI im Alltag, erklärt, warum gerade Frauen jetzt die KI-Zukunft aktiv mitgestalten müssen und weshalb die Zukunft hybrid ist.Keywords: Agentic AI, KI-Agenten, Vibe Coding, Prozessautomatisierung, Künstliche Intelligenz 2026, Human in the Loop, Responsible AI, Governance, Experimentierkultur, Female Leadership, Vera Strauch, Zamina Ahmad.+++Alle Links und Details findest du hier.Du willst 2026 deine Karriere selbst erzählen? Dann melde dich jetzt bei der Female Leadership Academy 2026 an und gestalte deine Leadership Karriere mit uns.Du brauchst mehr Infos? Melde dich hier zum Newsletter an.+++ Hosted on Acast. See acast.com/privacy for more information.

What do the American people actually expect from companies deploying AI — and are corporate leaders listening?In this episode of One Vision Podcast, Theodora Lau sits down with longtime friend Tyler Spalding, Chief Marketing, Communications & Engagement Officer at JUST Capital, to unpack the organization's latest research on how the public, investors, and corporate executives view AI's impact on society, jobs, and the economy.They dig into the perception gap between public sentiment (66%) and corporate optimism (94% of investors and 90% of corporate leaders see AI as a net positive), and what that gap means for business leaders navigating workforce decisions, reskilling investments, and responsible AI deployment.The conversation also explores the tension between AI-driven efficiency gains and the human cost of disruption — from layoffs framed as AI transformation and the anxiety facing the next generation entering the workforce, as well as the importance of defining and incentivizing responsible AI through consistent, comparable standards guided by public expectations.

In this episode, we dive into what it truly means to use AI responsibly in the justice and public safety space. Joining us today are returning guest Paul Wormeli, Chair of the IJIS Technology and Architecture Committee, and first‑time guest James McGennis, Executive Director of the State of Connecticut's CJIS Governing Board.Together, Paul and James explore how Connecticut is thoughtfully implementing AI technologies—focusing on governance, accountability, and data privacy. They share real‑world use cases, practical lessons learned, and how public institutions can embrace innovation without compromising public trust.Listen in to learn how Connecticut is setting a responsible path forward for AI in justice and public safety.Resources:State of Connecticut AI responsible Use Policy - responsible AI framework february 1, 2024State of Connecticut AI Inventory (Executive Branch) Open Data Portal - Executive Branch Artificial Intelligence System Inventory | Connecticut Data

In this episode, we're joined by Ben Olsen, longtime AI and Faith expert and the founder of the Faith Family Technology Network. We dive into a fascinating conversation about the organization's mission and their role in navigating the defining political and social questions of our time—specifically, how the evolution of artificial intelligence is reshaping the lives of children and families.Meet the speakers: Views and opinions expressed by podcast guests are their own and do not necessarily reflect the view of AI and Faith or any of its leadership.Production: Penny YuenHost: Gilad Berenstein Guest: Benjamin OlsenEditing: Isabelle BraconnotMusic from #UppbeatLicense code: 1ZHLF7FMCNHU39

We are reckoning with truths that are a bit uncomfortable. AI is not just a tool, but something people are relating to - personally. For kids and teens, we're finding that that can be extremely dangerous.In this episode, Shannon Peavey speaks with Tracy Pizzo Frey, a veteran technology leader including 11 years at Google where she oversaw Responsible AI for Google Cloud. As a consultant, she worked with Common Sense Media to develop a system for assessing the risks of large language models and AGI, with a particular focus on kids and teens.Tracy brings deep technical experience and knowledge of how technology shapes behavior. Drawing on lessons from social media and emerging research, she explores what feels different about AI.For young people who are still developing social and emotional skills, these interactions may have unique implications. AI systems are responsive and engaging, but they do not challenge users or help them navigate real-world complexity in the same way humans do. Over time, that difference may influence how teens build coping skills, relationships, and a sense of self.Through her work with Common Sense Media, Tracy has evaluated leading AI systems and reached some important conclusions. Today's models are not designed to serve as mental health companions for kids or teens, even though many young people are already engaging with them in ways that resemble emotional support.Tracy shares how these assessments were created, what they measure, and what they reveal about the current state of AI safety. She offers a grounded perspective on building & using these technologies responsibly, especially when younger users are already deeply involved..00:20 AI's effect on kids 02:07 Why harms are specific to kids & teens 04:50 AI is not a search engine07:27 Kids & teachers are often earliest adopters 08:06 Tech companies know more than they let on 09:15 Common Sense Media's risk assessment project09:57 Let's not repeat mistakes 11:24 Tracy's involvement13:11 Set your charter 14:50 Bring diverse, multi-disciplinary teams 16:25 Why psychological safety is important 17:38 Distilling masses of information into risk assessments18:48 Why hype matters20:30 How the team looked at social media 23:20 Early assessment of potential harms25:10 Character.ai as precursor to interaction with LLMs26:00 ‘Everything in the whole wide world'27:13 Why kids are different32:18 The danger of so-called frictionless relationships33:02 The best way to test36:50 Some surprising findings39:08 How tech can reshape a worldview41:02 There are good people, but - business models43:30 Know the tradeoffs45:07 The fact-to-fiction scale46:30 Some positivity48:00 Books, lawsuits, and resources

In this episode of CharityVillage Connects, we explore what responsible AI adoption looks like for nonprofits. AI is reshaping nonprofit work, from fundraising to communications and everything in between. This shift raises urgent questions surrounding privacy, trust, equity, wellbeing, accountability, and mission alignment. Join us as sector experts provide practical advice on setting guardrails, building internal capacity, using AI thoughtfully, and keeping human judgment at the center of mission-driven work.Meet Our Guests in Order of Appearance Alexandra Samuel, AI & Digital Workplace ExpertAlain Mootoo, Chief Operating Officer, CAMH FoundationTina Crouse, AI Ethics & Strategy SpecialistDianne Clark, Founder and CEO of Trendspire and ProEdventures AcademyDeepa Chaudhary, CEO, Grantorb.comAbout your HostMary Barroll, president of CharityVillage, is an online business executive and lawyer with a background in media, technology and IP law. A former CBC journalist and independent TV producer, in 2013 she was appointed General Counsel & VP Media Affairs at CharityVillage.com, Canada's largest job portal for charities and not for profits in Canada, and then President in 2021. Mary is also President of sister company, TalentEgg.ca, Canada's No.1, award-winning job board and online career resource that connects top employers with top students and grads.Additional Resources from this EpisodeWe've gathered the resources from this episode into one helpful list:Assess Your AI Maturity (Info-Tech Research Group, 2023)Transform (Flourishing Systems / IslamicFamily, 2025)Grant Orb (Grant Orb, 2025)Learn more and listen to the full interviews with the guests here.This episode of CharityVillage Connects is brought to you by the WUSC. For more than 50 years, WUSC has been working alongside communities around the world to catalyze positive education and economic outcomes for young people. Now, Canadians have the chance to join us by volunteering internationally. As a WUSC volunteer, you'll collaborate with local organizations, share your experience, and help co-create initiatives that expand opportunities for young people. For more information about how you can use your expertise to improve economic opportunities for young people, visit volunteer.wusc.ca.#podcast #charity

What do the American people actually expect from companies deploying AI — and are corporate leaders listening?In this episode of One Vision Podcast, Theodora Lau sits down with longtime friend Tyler Spalding, Chief Marketing, Communications & Engagement Officer at JUST Capital, to unpack the organization's latest research on how the public, investors, and corporate executives view AI's impact on society, jobs, and the economy.They dig into the perception gap between public sentiment (66%) and corporate optimism (94% of investors and 90% of corporate leaders see AI as a net positive), and what that gap means for business leaders navigating workforce decisions, reskilling investments, and responsible AI deployment.The conversation also explores the tension between AI-driven efficiency gains and the human cost of disruption — from layoffs framed as AI transformation and the anxiety facing the next generation entering the workforce, as well as the importance of defining and incentivizing responsible AI through consistent, comparable standards guided by public expectations.

This episode recorded live at the Becker's Spring 2026 Payer Issues Roundtable features Ceci Connolly, President And Chief Executive Officer, ACHP, reflects on the growing financial and operational pressures facing health plans across all lines of business, and how nonprofit, community-based payers are navigating affordability while strengthening local relationships and care coordination.In collaboration with Hippocratic AI.

Kevin Werbach speaks with long-time responsible AI leader Rumman Chowdhury the current environment, in which substantive standards and oversight efforts for AI are taking shape amid a larger anti-regulation wave. Chowdhury distinguishes sharply between frontier labs, where the posture is largely "AI at all costs," and the non-tech enterprises she works with, who are wrestling with how to scale governance bodies that originally reviewed single AI implementations to hundreds of systems, third-party procurement questions, and agentic workloads. She describes the current evaluations market as immature on nearly every dimension, and explains why generic benchmarks rarely translate to enterprise contexts like insurance or auto manufacturing. The conversation then turns to AI's impact on work and education. Her concern is that companies pursuing short-term efficiency by cutting entry-level hiring will face what MIT researchers Caosun and Aral call the "augmentation trap," in which workers' cognitive skills atrophy while new workers never develop them. She offers "discernment" as her 2026 word of the year, discribing the skill -- more than just critical thinking -- we must cultivate and defend. Her new podcast and forthcoming book, Thinking About Thinking, argues that our notion of intelligence was built for an Industrial Revolution workforce we are now automating away. Dr. Rumman Chowdhury is the founder of Humane Intelligence PBC, building modular, tool-agnostic AI evaluation infrastructure for enterprise and real-world contexts. She co-founded the nonprofit Humane Intelligence in 2022 and served as its CEO until 2025. She previously was Director of the Machine Learning Ethics, Transparency, and Accountability team at Twitter, founder of the algorithmic audit platform Parity, and Global Lead of Responsible AI at Accenture, where she built one of the first enterprise-level bias detection tools. She has served as U.S. Science Envoy for AI and as a Responsible AI Fellow at Harvard's Berkman Klein Center, and holds a doctorate in political science from the University of California, San Diego. Transcript Virginia SB 384 / HB 797 — Independent Verification Organization legislation (Fathom) The Augmentation Trap: AI Productivity and the Cost of Cognitive Offloading Open to Debate: Will AI Make Work Obsolete? Why AI evals need to reflect the real world (Transformer)

In this episode, we're joined by Georgina Bulkeley, Director of Financial Services at Google Cloud, to unpack how AI is transforming banking and financial services. With over 25 years in financial institutions, she shares what it takes to innovate in a highly regulated industry and how concepts like agentic commerce are paving the way for autonomous money movement. We also explore how AI is shifting from a risk to a powerful tool for fraud prevention, risk management and personalized financial advice at scale, along with the balance between innovation and responsible AI. Georgina closes with her perspective on what the industry will look like in five years and the biggest misconceptions leaders still have about AI.

Mel Sellick readies for AI by going beyond literacy to address the psychological, cognitive, and relational capacities required to ensure AI works for humans.Mel and Kimberly discuss AI literacy vs. human readiness; the contours of human vulnerability; AI as a social actor; collective understanding and emotional regulation; instrumental AI dependency; the non-reciprocal nature of AI; the spectrum of relationality; human flourishing; attention, agency and alternate futures; positive friction in human systems; supportive social structures; cognitive offloading and debt; self-reflection and calibrating human needs.Mel Sellick is an applied psychologist specializing in Human-AI interaction. The Founder of the Future Human Lab, her Human Readiness Framework has shaped conversations in IEEE, UNESCO, Oxford, MIT, Harvard and beyond.Additional Resources:Future Human Lab: https://www.futurehumanlab.com/ IEEE Organizational Readiness for Human-AI Interaction (Chair, SA-P7023) https://standards.ieee.org/ieee/7023/12394/Oxford AI in Education Hub (AIEOU): https://aieou.web.ox.ac.uk/ Harvard AI for Human Flourishing Council: https://hfh.fas.harvard.edu/ai-human-flourishing A transcript of this episode is here.

Episode 144: This week, Kyle Van Pelt talks with Tim Gavin, Chief Strategy Officer & Chief Compliance Officer at MCF. Tim helps lead the firm's long-term strategic direction across operations, compliance, advisor support, technology, and growth initiatives. Kyle and Tim discuss what sustainable growth actually looks like inside a modern advisory firm. Tim explains why organic growth creates stronger long-term enterprise value, how firms should think about operational capacity before scaling, and why successful change management starts with team buy-in—not software purchases. They also explore AI adoption, technology fatigue, client experience design, and the growing divide between firms that strategically invest in technology and firms that fall behind. In this episode: (00:00) - Intro (01:26) - Tim's money moment (02:51) - Why compliance can become a strategic advantage (03:56) - MCF's acquisition of Wealth Planning Corporation (05:37) - Defining intentional growth (07:31) - Measuring operational efficiency and capacity (09:53) - Organic growth vs. inorganic growth (12:41) - The hidden operational risks of scaling too quickly (14:41) - Why change management is harder than buying technology (17:30) - Building a tech stack that actually supports growth (21:38) - AI adoption, due diligence, and compliance concerns (23:33) - Responsible AI use and protecting client trust (26:34) - Tim's outlook on the future of financial services (28:31) - Why client experience is the real product (29:42) - Tim's Milemarker Minute Key Takeaways Organic growth compounds differently than acquisition growth. Firms that build referral systems, operational consistency, and advisor enablement create more durable enterprise value over time. Scaling exposes operational weaknesses. Growth only works when firms proactively manage advisor capacity, workflows, onboarding systems, and internal communication. Technology should reinforce strategy—not dictate it. Tim emphasizes evaluating tools through the lens of client impact, operational fit, and long-term scalability rather than reacting to hype cycles. Great client experience extends beyond meetings. The real question is how clients feel between interactions—whether they trust the plan, understand what's happening, and feel connected to the firm even when they're not actively engaging. Quotes "We don't want to grow just to grow. It's about how many clients we can impact and provide real value to them." ~ Tim Gavin "Everybody wants to talk about acquiring a firm. But at the end of the day, to really say you have scale, it means having systems in place that can generate organic growth." ~ Tim Gavin "You have to revisit your processes very frequently because technology changes constantly." ~ Tim Gavin Links  Tim Gavin on LinkedIn MCF Advisors Salesforce  Power BI Think and Grow Rich Connect with our hosts Milemarker.co Kyle on LinkedIn Jud on LinkedIn Subscribe and stay in touch Apple Podcasts Spotify YouTube Produce game-changing content with Turncast Turncast helps your company grow by producing top-quality content and fostering transformative conversations. We specialize in content generation, podcasting, digital strategy, and audience growth for fintech and financial services companies. Learn more at Turncast.com.

What if the real power of AI in healthcare isn't the technology itself, but how we apply it responsibly and intentionally? In this episode, Ajoy Ranga, Chief Digital Officer of Healthcare at UST Global, and Ashok Chennuru, Chief Data & Digital AI Transformation Officer at the Digital Platforms and Artificial Intelligence Office at Elevance Health/Carelon, discuss how their partnership between UST and Elevance Health is leveraging AI, data, and digital transformation to improve healthcare outcomes and consumer experience. They emphasize that scaling AI responsibly requires strong governance, human oversight, and a clear stance against using AI to deny care. Both highlight that high-quality, actionable data is foundational, but must be practical, cost-effective, and usable even when imperfect. Ultimately, they stress that success in healthcare innovation comes from starting with user experience, rapidly prototyping solutions, and fostering a mindset of continuous learning and experimentation. Tune in to hear how Elevance Health and UST are balancing innovation with responsibility to unlock AI's true potential in healthcare! Resources: Connect with and follow Ajoy Ranga on LinkedIn. Follow UST Global on LinkedIn and visit their website! Connect with and follow Ashok Chennuru on LinkedIn. Follow Elevance Health on LinkedIn and visit their website!

Asha Shivaji is redefining what it means to innovate in marketing effectiveness and ad tech. As a woman of color and former Google executive, she co-founded SeeMe Index in 2023 to help brands and agencies unlock growth with untapped audiences. Powered by its proprietary Responsible AI, SeeMe is building the industry standard for identity measurement and provides data-driven insights, benchmarks, and certifications that connect representation to measurable business outcomes, from creative effectiveness to long-term brand loyalty.Before launching SeeMe, Asha led strategy for Google's global marketing services organization, where she co-developed global initiatives with the UN's Unstereotype Alliance to dismantle harmful stereotypes in media. Her career includes partnerships with iconic brands such as Apple, Disney, Moët Hennessy, Estée Lauder, and Johnson & Johnson, where she modernized marketing strategies and drove business impact.Asha is an honoree on Ad Age's Tech Power List, ADWEEK's Innovator 50, a Campaign US 2025 Inspiring Woman in the Championing Change category, and 2025 Advertising Week Future is Female Winner. She is a sought-after speaker and advisor and has shared her insights on AI, DEI, and the future of inclusive marketing at major forums, including Cannes Lions, Advertising Week, SXSW, Ad Age's AI Marketing Playbook, CEW's DEIB Forum, the World Women's Federation, and thinkLA's Diversity Summit. She continues to serve as a consultant for the United Nations Unstereotype Alliance and is a vocal advocate for building ethical technology that reflects the richness of human experience.Asha holds a BA in Economics and Political Science and an MBA from NYU Stern School of Business.

Send us Fan MailYour employees are already ahead of you on AI. The data is in and the question is no longer whether this is happening, but what leaders choose to do about it.That is one of the key findings from Microsoft's 2026 Work Trend Index, and it is the starting point for this week's special episode. PeopleReign CEO Dan Turchin sits down with Matt Firestone, General Manager at Microsoft leading product marketing for Microsoft 365 Copilot and Agents, to unpack what trillions of anonymized signals across the Microsoft 365 ecosystem reveal about how AI is actually changing work right now.What pairing telemetry with survey responses and in-house research reveals about the gap between where employees actually are and where their organizations think they are is striking. And the numbers on how organizations reward, or fail to reward, the people already doing this work will make most leaders uncomfortable. The bottleneck, it turns out, isn't where most people expect it.In this conversation, we discuss:Why the job of a leader has shifted from designing transformation strategy to changing systems and cultureHow the report reframes agentic AI collaboration, not as a threat to human agency, but as an expansion of itWhat "frontier firms" and "frontier professionals" actually means, and why it's a mental model and rallying cry, not a marketing termHow building in the open, leaders experimenting visibly and removing the stigma of getting things wrong, is one of the most quantifiably impactful things a manager can doWhy agent adoption on the Microsoft 365 ecosystem is growing at a rate that will surprise even the optimistsExplore this conversation:00:00 Intro01:14 Inside Microsoft's 2026 Work Trend Index02:22 Telemetry, Not Just Surveys: What the Data Reveal03:09 Employees Are Ahead of Their Managers on Agentic AI04:37 The Transformation Paradox and Broken Reward Systems06:15 More Agentic AI, More Human Agency: The 49% Finding09:28 How Leaders Should Respond: Build in the Open11:26 Safety, Trust, and Responsible AI at Microsoft Scale13:36 Building a Manager Equity Dashboard in 25 Minutes with Copilot17:31 What Frontier Firms and Frontier Professionals Actually Do20:04 AI, Toil, and the Fear of Becoming Obsolete22:52 The 1 Billion Agents Prediction and What Comes NextResourcesSubscribe to the AI & The Future of Work NewsletterConnect with Matt on LinkedInMicrosoft's 2026 Work Trend Index

In this episode, Cambria Allen-Ratzlaff, Interim CEO of the PRI, is joined by Michael Benedict Yamoah (Vice President, Stewardship Director, EOS at Federated Hermes), Chris Jurgens (Senior Director, Omidyar Network), and Oumou Ly (Non-resident Research Fellow, UC Berkeley Center for Long-Term Cybersecurity) to explore how investors should respond to AI.Building on Part 1, this episode moves from theory to practice, outlining how investors can assess AI governance, identify risks across portfolios, and begin engaging with companies in a fast-moving and uncertain landscape.Overview:AI is already reshaping portfolios, but most investors are still early in understanding how to manage the risks. This episode focuses on practical steps, from governance and engagement to tools, research, frameworks and real-world examples of leading practice.A key message is that there is no perfect framework yet. Instead, investors must start now, build capability over time, and engage continuously as the technology evolves.Detailed coverage:What good AI governance looks likeAt a minimum, companies must comply with regulation and establish clear internal policies. Strong governance goes further, embedding AI into enterprise risk management, assigning board-level responsibility, and ensuring oversight across the organisation.Beyond compliance: lifecycle thinkingInvestors are encouraged to assess the full lifecycle of AI systems, from development and deployment to real-world impacts, liabilities and societal consequences.AI risk is dynamicUnlike other technologies, AI systems evolve post-deployment. This requires continuous monitoring, disclosure and adaptation, rather than one-off assessments.Examples of leading practiceCompanies such as Anthropic and Microsoft are highlighted for transparency, investor engagement and responsible AI frameworks. Across the ecosystem, progress is being driven by collaboration between companies, investors and policymakers.The importance of infrastructure and ecosystemsAI is not just about software, it spans chips, data centres and energy systems. Managing its risks requires coordination across the full value chain.Practical starting points for investorsInvestors should map where AI sits in their portfolios, identify key use cases, and assess associated risks such as cybersecurity, compliance and liability.Tools, frameworks and collaborationA growing ecosystem of resources, from investor coalitions to research frameworks, is emerging to support engagement and analysis.A marathon, not a sprintAI governance is an ongoing process. Investors must build long-term capability, stay engaged in dialogue, and avoid waiting for perfect solutions before acting.Start now, signal intentEven simple engagement, asking basic governance questions, can send a strong signal to companies that responsible AI matters.Chapters:00:08 - Introduction: from AI risk to investor action01:00 - What good AI governance looks like03:05 - Internal policies, risk management and board oversight05:00 - Lifecycle thinking and real-world impacts08:17 - Examples of leading practice in AI governance10:30 - Defining and understanding AI risk13:15 - Mapping AI use cases across portfolios15:39 - Practical tools and investor resources19:44 - Why AI is a marathon, not a sprint22:24 - Final takeaways: start now and engageFurther reading: Anthropic labor market impacts, Microsoft transparency reportDisclaimer:This podcast and material referenced herein is provided for information only. It is not intended to be investment, legal, tax or other advice, nor is it intended to be relied upon in making an investment or other decision. PRI Association is not responsible for any decision made or action taken based on information on this podcast. Listeners retain sole discretion over whether and how to use the information contained herein. PRI Association is not responsible for and does not endorse third parties featured on in this podcast or any third-party comments, content or other resources that may be included or referenced herein. Unless otherwise stated, podcast content does not necessarily represent the views of signatories to the Principles for Responsible Investment. All information is provided “as is” with no guarantee of completeness, accuracy or timeliness, or of the results obtained from the use of this information, and without warranty of any kind, expressed or implied. PRI Association is committed to compliance with all applicable laws. Copyright © PRI Association 2026. All rights reserved. This content may not be reproduced, or used for any other purpose, without the prior written consent of PRI Association.

Watch the Q&A session: https://youtu.be/gj4d75_ClggIn this lecture, we look at proposals to limit AI powers and impacts, so bad outcomes are outweighed by social benefits from the technology. I'll explain design processes (such as Human-Centred AI and Responsible AI) and technological approaches for AI system qualities like trustworthiness, explainability and “human in the loop”.  We will explore how we, as individuals, can use AI based systems in discerning ways; and look at what governments can do to help their citizens thrive in an AI-future.This lecture was recorded by Professor Matt Jones on the 21st of April 2026 at Barnard's Inna Hall, LondonMatt Jones is a computer scientist at Swansea University - and a Fellow of the British Computer Society - who works alongside colleagues from many other disciplines and directly with everyday folk across the world to explore the future of digital technologies. Over the last 30-plus years, this human-centred approach has led to novel approaches for, amongst other things,  mobile phone-based information searching and browsing, pedestrian navigation, voice assistants and deformable displays.  Much of his work has been driven by intense and sustained engagements with “low resource” communities from informal settlements in India, South Africa, and Kenya. Through their generous and gracious participation, these extra-ordinary users with the fresh and diverse perspectives have stimulated insights into the future of digital technologies for everyone, globally. In all this work, Matt works as part of a long-standing collaborative team with Jen Pearson, Simon Robinson and Thomas Reitmaier (from Swansea) and colleagues in India (including Dani Raju) and South Africa (including Minah Radebe). His work has been supported by the UK's science funders (EPSRC and UKRI). Currently, this funding includes a Fellowship to explore the future of interactive AI and leadership roles in responsible AI and inclusive digital technologies. This funding has led to a series of impactful publications, talks and influences on people, policies, and practices. Matt has collaborated with private, public and third sector organisations, including Microsoft, the NHS, Google, IIT-B, the BBC and IBM. He is a member of the Foreign and Commonwealth Development Office's Research Advisory Group and Welsh Government's AI reviews.The transcript and downloadable versions of the lecture are available from the Gresham College website: https://www.gresham.ac.uk/watch-now/ai-tamingGresham College has offered free public lectures for over 400 years, thanks to the generosity of our supporters. There are currently over 2,500 lectures free to access. We believe that everyone should have the opportunity to learn from some of the greatest minds. To support Gresham's mission, please consider making a donation: https://gresham.ac.uk/support/Website:  https://gresham.ac.ukTwitter:  https://twitter.com/greshamcollegeFacebook: https://facebook.com/greshamcollegeInstagram: https://instagram.com/greshamcollegeSupport the show

In this episode, Cambria Allen-Ratzlaff, Interim CEO of the PRI, brings together Michael Benedict Yamoah, Vice President, Stewardship Director, EOS at Federated Hermes, Chris Jurgens, Senior Director, Omidyar Network, and Oumou Ly, Non-resident Research Fellow, UC Berkeley Centre for Long-Term Cybersecurity to explore why AI is emerging as a critical sustainability issue for investors.The first in a two-part series, this episode examines the scale and speed of AI adoption, its implications for climate, labour, security and long-term financial stability, and what it will take for investors to get ahead of a transition that is already underway.OverviewAI is rapidly reshaping the global economy, with unprecedented levels of capital investment, adoption and market impact. While much of the focus has been on AI as an investment opportunity, this episode reframes it as a system-wide issue with implications for climate, labour, security and long-term financial stability.The discussion highlights a growing gap between investor awareness and capability, as well as the need for stronger coordination, clearer frameworks and more robust governance to manage AI-related risks.Detailed coverageAI as a system-wide investment issueAI is not confined to the tech sector, it is a whole-economy force that will impact portfolios across industries, making it relevant for all long-term investors.The business case for responsible AIResponsible AI practices are increasingly linked to performance, helping companies build trust, avoid costly failures and strengthen long-term returns.Systemic risks: energy, labour and infrastructureAI is driving rapid growth in data centres and physical infrastructure, with significant implications for energy demand, emissions, water use and local communities.Security and regulatory riskAI is accelerating cyber threats while also becoming a focus for regulators globally. This creates new layers of compliance, liability and geopolitical risk for investors.The investor capability gapWhile interest in AI is growing, many investors lack the expertise, frameworks and internal capacity to assess and engage on AI-related risks effectively.From developers to deployersEngagement is currently focused on major AI developers, but risks and opportunities are increasingly concentrated in how AI is deployed across sectors.Governance as the central leverAcross all perspectives, governance emerges as the most critical tool, ensuring boards and management teams are equipped to navigate uncertainty, balance trade-offs and make long-term decisions.A transition moment for investorsAI represents a new phase of technological disruption, similar to past waves like telecoms and big data, but with broader and faster-reaching consequences.Looking aheadPart two will focus on the practical side, what investors can do, the tools and frameworks emerging, and where collective action can drive the most impact.DisclaimerThis podcast and material referenced herein is provided for information only. It is not intended to be investment, legal, tax or other advice, nor is it intended to be relied upon in making an investment or other decision. PRI Association is not responsible for any decision made or action taken based on information on this podcast. Listeners retain sole discretion over whether and how to use the information contained herein. PRI Association is not responsible for and does not endorse third parties featured on in this podcast or any third-party comments, content or other resources that may be included or referenced herein. Unless otherwise stated, podcast content does not necessarily represent the views of signatories to the Principles for Responsible Investment. All information is provided “as is” with no guarantee of completeness, accuracy or timeliness, or of the results obtained from the use of this information, and without warranty of any kind, expressed or implied. PRI Association is committed to compliance with all applicable laws. Copyright © PRI Association 2025. All rights reserved. This content may not be reproduced, or used for any other purpose, without the prior written consent of PRI Association.

On this episode of The Association Podcast, we welcome Jamie Atchison, MSMIT, Senior Director of Innovation and Strategy at the Association of Schools and Programs of Public Health (ASPPH). Jamie shares her unique journey from public health programming into technology leadership, highlighting how she bridges business needs and digital innovation within her organization.We explore ASPPH's groundbreaking AI chatbot, built in just eight weeks, and the intentional, human-centered approach behind it. Jamie dives into how associations can responsibly adopt AI, the importance of curated and trusted content, and how vertical AI models can combat misinformation in complex fields like public health.The conversation also covers leadership philosophy, including servant leadership, psychological safety, and building high-performing “one-pizza teams” that can move quickly without losing alignment. Jamie offers a forward-looking perspective on how AI and agentic AI will reshape associations, emphasizing augmentation over replacement and the need for strong critical thinking in an AI-driven world.00:00 Welcome and Introduction00:01 Rapid Fire Questions02:00 Jamie's Career Journey and Path into Technology05:00 Transition from Program Work to Digital Innovation Leadership07:00 Building High-Performing “One-Pizza Teams”09:00 Inside the AI Chatbot Project (8-Week Build)12:00 Team Structure, AWS Partnership, and Knowledge Transfer13:00 From Problem to Solution: Why a Chatbot?14:30 Responsible and Ethical AI in Public Health17:00 Guardrails, Curated Content, and Vertical AI Models18:00 Data Considerations and Content Strategy20:00 Member Feedback and Adoption of AI Tools21:30 Human-Centered Design vs. Over-Reliance on AI23:00 Broader AI Strategy and Task Force Initiatives26:00 Building a Digital Innovation Team in Associations29:00 Bridging Business Strategy and Technology Execution32:00 Future Trends: AI, Agentic AI, and Workforce Impact36:00 Servant Leadership and Building Trust in Teams39:00 Culture, Collaboration, and Crisis Response in Tech Teams40:00 AWTC Recognition and Team Success42:00 Aligning Personal Values with Organizational Mission44:00 Where to Learn More About ASPPH's AI Initiatives

Enterprise customers demand 99.9% availability, regardless of how the underlying software is built. In this episode, Murali Swaminathan (CTO @ Freshworks) discusses how enterprises actually win with AI! We explore the “Architecture of Predictability” – proactive architectural safeguards to scale “responsible AI by design” across a global organization serving 75,000 customers. Murali shares his leadership playbook for implementing the technical safeguards and product trust controls that empower hundreds of engineers to build safely. We also dive into the shift from deterministic flowcharts to “workflows with a brain” and why backend systems engineers are the secret bedrock of agentic products. Plus, Murali deconstructs the dual evolution required of modern leaders: mastering strategic thinking at the business level while cultivating systems thinking at the engineering level.   ABOUT MURALI SWAMINATHAN Murali Swaminathan joined Freshworks as Chief Technology Officer in September 2024. Murali is responsible for Freshworks' technology roadmap and strategy, leading the company's global engineering and architecture teams. With over 30 years of experience in software engineering, he has held leadership roles at ServiceNow, Recommind (now OpenText), and CA Technologies (now Broadcom), where he delivered scalable, secure solutions that enabled digital transformation and business agility. Murali holds a master's degree in Software Engineering Management from Carnegie Mellon University and a bachelor's degree in electronics and instrumentation from Annamalai University in India.   SHOW NOTES: Freshworks' operating context: Engineering for 75,000 global customers (2:09) Navigating the tension between rapid AI adoption and enterprise-grade reliability (4:58) Breaking the "Positive Scenario" Trap: Using AI to automate negative test cases and corner-case detection (6:40) Why Responsible AI is a competitive advantage: Building "kill switches" and trust gates (8:31) Responsible AI by Design: Moving from reactive compliance to proactive architectural safeguards (10:48) Technical safeguards: Leveraging hyperscaler frameworks for model compliance and data anonymization (13:39) Product Trust Controls: Demonstrating reliability through role-based access and thresholds (16:25) Why engineering leaders should experiment in small teams before global rollout (20:35) Simulating Chaos: Using Business Continuity Planning (BCP) to test AI system resilience (22:13) Workflows with a brain: Transitioning from deterministic flows to agentic runtime decisions (24:16) The AI Team Profile: Why backend system engineers, not just data scientists, are the bedrock of agentic products (29:25) Cultivating a mindset shift toward agentic system orchestration (32:10) The shift to systems thinking: How engineering roles evolve from "building pieces" to managing end-to-end system flows (33:38) How to approach strategic business thinking as an engineering leader (36:43) Rapid Fire Questions: Guy Kawasaki's "Think Remarkable" and the best way to predict the future (38:23)   LINKS AND RESOURCES Think Remarkable: 9 Paths to Transform Your Life and Make a Difference - Tech titan and creator of the Remarkable People podcast Guy Kawasaki delivers a practical, tactical, and sometimes radical discussion of how to make a difference in the world and live a fulfilling life.   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Think AI is about automating what you already do? That's the same mistake companies made moving to cloud, and FICO's Mike Trkay says you're about to waste millions proving it. Mike is Chief Information Officer (CIO) and Chief Customer Officer (CCO) at FICO, an analytics software company that processes billions of decisions per day and powers 80% of fraud detection. In this episode, Mike explains why 95% of AI projects never reach production, why companies are already repatriating workloads from large language models, and what really separates automation from transformation.   Chapters: 0:00 Introduction 1:23: Why FICO's CIO Is Also the Chief Customer Officer 4:52 The Office Space Problem: Why CIOs Are Really Translators   6:02 "Conduit in Chief" — The CIO's Real Job   6:45 How CIOs Accidentally Become Cost Centers 7:40 What FICO Actually Does (It's Not Just Credit Scores) 12:59 How Missile Guidance Tech Became Fraud Detection 17:59 When LLMs Can't Meet 150-Millisecond Latency 21:32 Why AI Strategy Is Harder Than It Looks 24:50 The Cloud Parallel: 5% Alignment and Why AI Projects Stall 27:08 "You're Just Doing a Bad Process Faster" 31:44 LLM Repatriation Is Already Happening 37:40 A FICO Score for AI Decisions 43:10 Global Regulation and Staying Ahead of Compliance 45:22 The Australian Banking Example: Focused Language Models in Practice 52:08 From Cost Center to Innovation Driver 54:40 What's Next: Agentic Architecture and Focused Sequence Models 57:49 "What's the Opportunity Today?" — The CIO Mindset Shift -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Drew Burdick designs AI systems to multiply human capacity, prioritizes great experiences, and values the serendipitous magic of human connection and collaboration.      Kimberly and Drew discuss building with badass teams; curiosity and innovation; building momentum with AI; human relationships and rapport; proprietary knowledge and expertise; long-term thinking; AI agents as teammates; pricing in human experiences; designing for humans vs. bots; regulation and accountability; societal guardrails; the mid-market squeeze; actions companies should take now; investing in people; and keeping community front and center.Drew Burdick is the founder of StealthX and the CLT Startup House. Drew parlays his deep background in design and solution development to help companies deliver exceptional experiences with AI.Additional Resources:Building Great Experiences (podcast): https://stealthx.co/resources/podcast CLT Startup House: https://cltstartuphouse.com/  A transcript of this episode is here.   

Unlocking the Power of Frontier Partnerships Subscribe to our Newsletter:https://theultimatepartner.com/ebook-subscribe/Check Out UPX:https://theultimatepartner.com/experience/ In this compelling discussion from the Ultimate Partners Winter Retreat, Microsoft GM Katharine Kennedy joins Vince Menzione to break down the operating models of “Frontier Firms.” Katharine shares her incredible journey of scaling the ServiceNow partnership from zero to $1 billion in TCV and reveals her current mission: building Adobe into the next great frontier firm for Microsoft. The conversation dives deep into the necessity of AI-led innovation, the critical importance of placing trust at the center of every technological stack, and why traditional quarterly business reviews are being replaced by real-time, constant connectivity. Whether you are an ISV, SDC, or channel partner, this session provides a roadmap for navigating the tectonic shifts in the AI ecosystem through organizational alignment and shared vision. Key Takeaways Frontier firms integrate AI up and down the UI, agent, and data layers while evolving their internal operating systems. Successful partnerships require a shared vision at the highest level that melds two mission statements into a single belief system. The traditional QBR is becoming outdated, replaced by real-time, constant communication across engineering and product teams. Trust must be the primary pillar of AI development, supported by core principles like fairness, reliability, and accountability. Leading with co-innovation and customer-centric data solutions is more effective than leading strictly with revenue goals. Strategic use of the Microsoft Marketplace remains a “hidden gem” for achieving scale and high-velocity growth. https://youtu.be/OU22MIfs-1A If you're ready to lead through change, elevate your business, and achieve extraordinary outcomes through the power of partnership—this is your community. At Ultimate Partner® we want leaders like you to join us in the Ultimate Partner Experience – where transformation begins. Key Tags: Frontier Firms, SDC, Microsoft GM, Adobe Partnership, ServiceNow, AI Operating Model, Responsible AI, Co-innovation, Partner Value Chain, Organizational Alignment, Microsoft Marketplace, TCV, Data Sovereignty, AI Agents, Adobe Firefly, Azure, Ecosystem Growth, Digital Transformation, AI Governance, Strategic Partnerships, Tech Leadership. Transcript: Katharine Kennedy Vince Menzione: [00:00:00] Honestly, it’s people. Yes, with agents. Um, and I know we hear that and it’s very like, oh, what does it mean? Are we really using it? I cannot tell you how many agents I use in a day. We just finished Ultimate Partners Winter Retreat here in beautiful Boca to a sold out crowd. Come join me now for a compelling discussion on the impacts of the tectonic shifts we’re all seeing. We, we’ve talked about MSP, we’ve talked about channel. We’ve talked about marketplace. We haven’t really dug deep into the SDC conversation, and I still, that doesn’t roll off my tongue. I still say ISV in my own mind, but the software development corporations, um, we’ve had several executives from that, from that world. Sandy Gupta has been. Um, many time guests, uh, at, at, at our events and we really wanted to double click. And I was so fortunate to meet Katherine Kennedy several months ago and learned about what [00:01:00] she’s doing and what the work that she’s driving. So I wanna invite her on stage ’cause we’re gonna have a very intimate conversation by Yeah, we call these so great to have you here. And, uh, you’re a GM at Microsoft, which is a big deal, by the way. A lot of people don’t know that. Thank you. And you’re running, uh, two of, I’d say two of the most significant partners within the Microsoft ecosystem. I would say obviously two. Now. Just one. Okay. We’re doubling down on focus. So nice to meet everybody. I, I wish there was a fire ’cause it did. What you Well come on. This goes off heat by the way. We get back off a little bit. This goes off our, so all good. So tell us, give us your, yeah. Give us your background and your role. Katharine Kennedy: Sure. So Catherine Kennedy. Nice to meet you all. Um, I’m a GM at Microsoft previously overseeing both the ServiceNow and the Adobe practice. Um, spent the last four years building ServiceNow too. What now our previous guests got to refer to as our REO, you know, exciting, uh, big growth [00:02:00] partnership. Um, so we took that from, for them from $0 in terms of shared revenue to a billion dollars in TCV. Um, and they have one of the largest Macs now with Microsoft. And we did that over the course of three years. So we’ll talk a little bit about. Um, the mindset, uh, and the operating models and things that we implemented with ServiceNow. Um, and then at the time, um, they asked me to take on Adobe as well. And when we saw the opportunity at Adobe, we said, wow, we really need to focus here. And so I have the privilege of being able to focus on Adobe this year. And, um. What I’m most excited about is the ecosystem and the ecosystem opportunity with Adobe as we build them into the next frontier firm or Microsoft. Vince Menzione: And of course we use the term spark, the ecosystem, so yes. Um, so let’s, let’s dive in [00:03:00] here. Use the term mindset. I was thinking about mindset. Market shift, frontier Firm, how do those things align together? Microsoft has been talking, I mean, Judson up on stage and Ignite talking about frontier firms. Nina’s talked about frontier firms. This is a shift in how organizations operate. Yes. In for some, yes. Uh, for others. I was thinking, what are you seeing across the SDC community specifically where you’ve managed before, where you’re managing now, but with ServiceNow and Adobe as an examples? What defines a company that’s truly making this leap? Katharine Kennedy: So as we’re looking at these frontier firms, uh, especially in the S-D-C-I-C spaces, we’re looking at, um, how do they implement AI up and down their stack, but then across the operating system, um, and. I refer to it in our business as the partnership value chain. ’cause we look at our SDCs and ISVs as partners. Um, and so the partner operating model between Microsoft and in this [00:04:00] case, Adobe or ServiceNow, has to be solely in lockstep and moving at warp speed. It’s as, as we’ve been talking about all day, it’s just moving so fast and so the tighter. We’re connected. The Cohesity across the company, um, is absolutely critical, but it’s AI up and down, AI across, um, and what I mean by that is, uh. That’s from the UI layer to the agent layer down to the data layer. So unlocking all of the layers of the stack. And then across the operating model, how are we empowering each executive to buy in on that North star or that strategy that we have jointly? And then how do we drive that operationally to execute at the field level? And that’s. Probably the biggest undertaking, um, I’ve ever done because it’s really you, your team becomes, uh, [00:05:00] these we’re like ants running between two giant companies. I mean, it’s just back and forth, back and forth, back and forth. And um, that’s really the art and the science of it is that honestly it’s people. Yes. Um, and I know we hear that and it’s very like, oh, what does it mean? Are we really using it? I cannot tell you how many agents I use in a day. It’s truly remarkable. Vince Menzione: You mentioned North Star, so I wanted to Yeah. Can I double click on it? Katharine Kennedy: Please do. Yes. Happy to. Vince Menzione: Yeah. I think about mission and purpose and all that tying into North Star. Are, are you implying that an organization needs to get its North Star, right? First and then how, how, and what, what are most of these organizations you’re seeing today, not the ones you manage, but other organizations in the SDC portfolio? Like where are they in terms of the continuum? How are, how are they moving along and what’s your guidance to them? Katharine Kennedy: It’s a good question. So I’ll start by saying my observation, my opinion is [00:06:00] as I’m looking across the companies that are successful and the ones who are yet to be successful, um, the key differentiator is that there is a shared vision at the highest level of the company that drives all the way down to the field. And what I mean by that is we’re taking two mission statements and we’re melding them together. Then we’re creating a belief system and it becomes a cultural shift across two companies versus, Hey, we’re gonna have all of these siloed, tactical, yeah. Operating units and they’re gonna do their own thing and maybe they’ll be successful over here. Maybe they’re doing something different over here, but we’re really. I think I heard Nina say this also, we’re pulling that red thread through the company. Yes. Um, which is critical. And I’ve seen so many companies just show up for the revenue. And yes, that’s an absolute outcome and it’s a [00:07:00] tremendous outcome if you do it right, but you have to do it right. You have to pull that red thread and you have to have every single part of the. Partner value chain buying into this strategy and this North Star, and if they don’t, if one piece of that chain is not bought in, you fail. Yeah. Vince Menzione: Organizational alignment is what you’re saying and what, what I’m hearing is in order, in terms of getting the AI Strat, the North Star aligned. Yes. You’ve gotta get the, I call the C-Suite aligned. Yes. You need to get all the functions of the organization aligned to the thread that you talked about. Yes. And then what does that look like? What does that North Star look like? What is it, what is the ideal example of what the North Star would look like? I’m, I’m a frontier firm. I brought in on ai, music agent ai. I’m doing all the things that we’ve talked about earlier. Katharine Kennedy: Yes. Um, so I think it, so operationally, um, it’s moving the operational rhythm from what used to be [00:08:00] qbr. Frankly, I think that’s outdated. Yes, it is. It is real time, constant communication. And yes, there will be checkpoints and they could be weekly, they could be monthly, they could be quarterly, but this is just real time constant communication because the pace of business, the pace of innovation is going so fast. We have to have that direct line of communication product to product team. We have to have that direct line of communication, engineering to engineering, because with everything going in on. Everything going on in the macroeconomic climate today, especially given concerns around sovereignty. Um, I run a global business, so we have customers saying, Hey, I don’t wanna host my data in a place where I don’t align with the values. That’s a real situation. That was actually a topic at Davos, as you mentioned, um, Nina. And so, um, we’re rapidly addressing these concerns with our customers and meeting our customers where they are. [00:09:00] Um, but it’s that real time constant connectivity. Um, and we’re frankly. We’re seeing it across the board. Um, but the operating model has to change. We have to look at more advanced, modern models, uh, for these partnership businesses to sustain in this next wave of transformation. Frankly, Vince Menzione: you know, it’s, so, you talked about values? Yes. This is, this leads into another conversation, right? When we talk about ai, we talk about, we talk about AI and the use, use cases. We skip over things like values and trust and governance. Katharine Kennedy: Oh, good segue. This is, this is my passion, please. Oh, I get so worked up about this. Good. So I, I had the privilege of, um, sitting, uh, with our SLC community a couple weeks ago, and, uh, they introduced, oh, here’s our amazing new, uh, pitch. We were just [00:10:00] speaking about it in the back actually. And, and it is, it’s amazing. And, uh, they said, do you have any feedback? And I was like, oh. And I waited and I saw everybody, every, you know, oh, we need to change this or tweak that. And I, and I waited. And then at the last moment I stood up. I was like, okay, I gotta say it. I was like, you say intelligence and trust. I, this is a small tweak, but trust has to be first, foremost, first, last, center, everything. Trust has to be everything. And, um, and I truly mean that. And I think, you know. Of all the companies I’ve worked for and I’ve worked for quite a few, um, Microsoft is the company that I believe in the most that can do the most good in society and in the global. Macroeconomic economy, a anything right in the world, in your communities. Um, and so one of the things that really struck me, and I keep coming back to with Microsoft and the, the topic of trust is how Microsoft, [00:11:00] um, was first to the table in this, in this, um, moment of ai. You know, introduction a few years ago to say, Hey, we need a set of core values and ethics and principles that we’re all gonna, we’re all gonna marshal around and I haven’t heard it as much recently, and now it’s coming back. And, uh, you know, the, the six core principles that Microsoft used is, I’m just gonna tell you right now, our fairness, reliability and safety, privacy and security, inclusivity, um, transparency and accountability. And it’s not. Just six principles that you see on a poster in the offices. These are embedded, again, back to the operating model across every single aspect of our business. So within our product, within our engineering, even just in our collaboration tools, you could be sending a teams message and you’ll get a notification, Hey, this is not aligned to the Microsoft. Core [00:12:00] values of ai. And so there are gates and governance and guardrails built into every layer of our technology stack and then across the company in our operating rhythms. And that is what gets me so excited and gets me up at, at out of bed in the morning. Um. I actually got a call from Sila. No one wants a call from Sila. Does anybody know Sila? Uh, yeah. Yes. Okay. That’s our legal, that’s our legal team. Legal affairs. Sila. Yeah. No one wants that call. Uh, I actually, I got so excited. I was like, are you calling about responsible ai? ’cause I was one of the first, um, I was one of the first to raise my hand to say. We will sign up. Was it Brad Smith calling you? Oh gosh. Oh, that would be a dream. I think he’s so, I’m, I love him. I think he’s so cool. Um, I love that you actually, sorry, side, I’m gonna take you on a side tour. Next slide. Um, my favorite thing to do is pull up the news and you’re seeing something from the Prime Minister in, you know, Germany and Brad [00:13:00] Smith’s in the foreground Yes. Of every photo. You’re just like, wow, we’re influencing at such a global. Um, base that I could just, it’s hard to wrap your head around sometimes, but, so anyways, going back, I’m gonna take us back to trust. Um, please. Vince Menzione: Well, I just think we need to apply it back to ai, right? Because it is so important. It is. It is. These agents are out there and if they’re not governed and if you don’t Yeah, yeah. Katharine Kennedy: I’m so, so, yeah, thank you. Keeping me on track. So, so why I am excited about it is, is because, um. As we’re going out into our communities, um, we’re here in the southeast and one of the biggest issues that comes up over and over again is, how do I trust that AI is not gonna learn off my data? How am I gonna trust that it’s telling me the right information? And so on and so forth. And that’s when I get to this great conversation about trust and our responsible AI pact and, um. This is, this is truly what I mean, that it can be a force [00:14:00] multiplier, but it can be a force for good. And if you don’t have those guardrails and that governance and those principles aligned across the companies. You fall down, right? You fall down with the customers, you fall down with the organizations you’re serving. And so going back to our North Star two, we align there, we align with the values and the ethics, and then we can start to really build a business together. And that’s how we were able to do it so fast. And so, um, at such scale, at such global scale, um, with. ServiceNow, but now we’re going to take a mature partner in Adobe and we’re gonna take them to the frontier in a way you haven’t seen before. So. Just a little commercial. Adobe is gonna be announcing their Adobe marketing agent. I love it as GA next month. So they are a frontier firm for us. Yes, very exciting round of applause for Adobe there. For Adobe. Yeah. And more to come. So we’ll be [00:15:00] having, uh, their firefly, uh, video models coming out on Azure and available through Marketplace as well, um, coming soon. So lots of exciting things happening. Vince Menzione: Sounds exciting. So let’s talk about those partner big wins that you’re saying. Give us some examples of those. Katharine Kennedy: Now are you talking about from a Microsoft and Adobe co-innovation perspective? Yes, from the co-innovation perspective. Okay. Yeah. Um, so from a co-innovation perspective, this is. This is a labor of love. Um, I approach it in a very disciplined manner. The way that we look at, um, these frontier firms is we’re leading with co-innovation versus leading with revenue. And it’s a, it’s, it’s a paradigm shift that takes everyone to buy in back to my earlier point, but also, um, the hardest part is. Teaching companies, um, to do things differently. Uh, so we start with [00:16:00] engineering and product. And actually before we get there, we start with customer and we sit with our customers. We understand what our customers are asking for. We’re understanding the value that they need unlocked, and typically it’s at the data data layer. And so what we’re doing is we’re seeing, okay, what are the data things? What are the data silos that need to be unlocked? And so we start to kind of build up from there, taking the customer perspective. Then we sit with engineering and product and we say, okay, what do we have on the truck today? How can we elevate this to an AI led AI first motion that meets our customers where they are in their AI journey? And delivers value and business outcomes day one versus, hey, we have to go through this laborous process. One of the other things we’re seeing is forward deployed engineers. Um, so thinking about, Hey, how do we sit with our customers and start architecting. What they need to address their business challenges today, um, because AI [00:17:00] can solve a lot of this, right? And so it’s a really interesting model shift that we’re seeing across the board within Microsoft, within our largest ISVs, and within our customer and our, um, ecosystem community with our GSIs, our sis, as well as our channel. Vince Menzione: So I know we were. You’ve had a lot. We, we had Jason up here talking about marketplace. Yes. And Jason Grey, Ja. Oh no, Jason. R Jason. R Jason. Yeah. We’ve had Jason Grey. He’s had Jason Grey. Yes. Well, we, um, you’re, you ServiceNow got called out in that last set session. I know. I was thinking about marketplace and co-selling. Yes. And then ecosystem. So I wanna like tie those three things together if that’s possible with you. Like what are you seeing from a best practice perspective. Obviously ServiceNow has been a top a top partner. We’re starting to see a lot of, well, channel D, channel [00:18:00] resellers, and the like. What are you seeing from a best practice perspective and is there yes. Central opportunities there? Katharine Kennedy: Yes, yes, yes, yes, yes, yes, yes. Okay. Three things. Um, one is AI led innovation. First and foremost, you gotta have the solution. You gotta have it. If you don’t have the solution, you don’t have something to sell. Second is a, um, AI led go to market hero motion. And what I mean by that, so in the, I’ll use ServiceNow as a, as a. Example ServiceNow. We created a, the first, uh, copilot plus, um, ServiceNow assist agent to agent go to market hero story. It landed really well with our customers and so we started to build off of that and we integrated across, um, up and down the stack. Like I mentioned, the data layer, the agent layer, and the ui. Um, and our customers were thrilled. They were like, wow. What else can we do with this? Can we unlock HR with this? Can we unlock. [00:19:00] What else can we do? Finance? Can we do finance? And so we started to see these, these moments in time where our customers were taking the technology and taking it to places we just hadn’t even thought about yet. Um, so I would say those two. And then the third would be, uh, making sure that we’re enabling the field. In a way that they know that story, they can tell that story, and then they have access to people to support that story. Um, and then wrap that in marketplace leverage micro, uh, marketplace as a scale motion. And now I know we still have opportunities to continue to improve around marketplace. Um, but we’ve come a long way and we’re seeing tremendous growth and scale out of this engine. So it’s, it’s definitely a hidden, um. I would say honestly, it’s still a hidden gem in the Microsoft. Uh. Bag, if you will. Vince Menzione: $300 billion in total.[00:20:00] Katharine Kennedy: Yeah, I seriously, yeah, but not anymore, I should say. Yes, I’ve been to Singing from the Rooftop. Yes. Vince Menzione: And you’re gonna be back this afternoon, right? Yes. A session with Ashley, so, oh, okay. I think, was it with Ash? Maybe? Oh know, maybe. I don’t know. Maybe. I’d be delighted it’ll be back the same. I’m happy to be back. I wanna make sure, I do wanna make sure, we’ll, we’ll cover some more of this there. Katharine Kennedy: And then the last thing, yeah. Shared KPIs. Yes. Shared KPIs. We gotta track it. We gotta be accountable. So get your vision aligned. Get your vision, get your organizations across all of the disciplines aligned. Yes. And then have a set of shared KPIs and owners for each of those KPIs. Yes. Right. And govern it. And govern it. Govern it, yeah. Report up to the CEO on a weekly basis, on a monthly basis, on a quarterly basis. I started reporting up to our CEO and he was like. What is she doing? He’s like, this business is going really, it’s growing fast. What is she doing? Can we do this somewhere else though? Um, it’s, you know, making sure people know the story, um, [00:21:00] and everyone’s buying in and they’re accountable. It’s, um, it’s a simple thing, but it’s powerful. Thank you for having me. Vince Menzione: Thank you so much. I really, yeah. Appreciate it. Thank you everyone. Alright, thanks. You don’t forget, ultimate Partner Live is coming soon, May 11th through the 13th in beautiful Bellevue, Washington. I hope to see you there.

AI is now everywhere, but trust is breaking down just as fast. As synthetic content floods our feeds and workflows, leaders face a new question: when does AI help, and when does it quietly undermine credibility? In this episode of ThinkCast, Gartner Senior Director Analyst Deepak Seth returns to explore a growing counter‑movement: the rise of "AI‑free" trust. From content labels that signal human creation to new expectations around AI governance, Deepak breaks down why trust — not capability — is becoming the defining challenge of the next AI era.   You'll learn: Why "AI‑free" could become the new organic label for content and brands How trust, provenance and context shape responsible AI use What recent high‑profile failures reveal about over‑automation risks How CIOs can build guardrails without stalling innovation Dig deeper: Watch the 7 Disruptions You Might Not See Coming Become a client to learn more about AI governance, trust and risk See why Gartner is the world authority on AI Try out AskGartner for more AI-powered insights  

This Week:  Responsible AI Adoption We continue our coverage of the 2026 Nonprofit Technology Conference (26NTC), with a panel that helps you find the low-hanging fruit for AI at your nonprofit. They share their 5-Step framework for deploying AI in … Continue reading →

Half of consumer question the authenticity of what they see online.