Podcasts about ai strategy

The Transformation Ground Control podcast covers a number of topics important to digital and business transformation. This episode covers the following topics and interviews: Tech Hiring Landscape, Q&A (Darian Chwialkowski, Third Stage Consulting) Everything You Need to Know About Managing Careers in Technology & Consulting (Jonathan Whipple, CEO & Co-Founder of Lander Talent) 5 Lessons I Wish I Knew Before Starting My Consulting Career We also cover a number of other relevant topics related to digital and business transformation throughout the show.  

Workday CTO Peter Bailis talks with TITV Host Akash Pasricha about the company's $1.1 billion acquisition of Sana and their broader AI strategy. We also talk with The Information's Stephanie Palazzolo and Turing's Jonathan Siddharth about how labs are using "reinforcement learning gyms" to train AI models, and we get into the new era of consumer crypto and on-chain identity with Ty Haney of Try Your Best and Dave Morin from Offline Ventures. Lastly, we get an inside look at the IPO market with The Information's Katie Roof and Industry Ventures' Hans Swildens.Articles discussed on this episode: https://www.theinformation.com/articles/ventures-limited-partners-see-lifeline-ipo-wavehttps://www.theinformation.com/articles/anthropic-openai-developing-ai-co-workersTITV airs on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Subscribe to: - The Information on YouTube: https://www.youtube.com/@theinformation4080/?sub_confirmation=1- The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agenda

Welcome back to To the Point Cybersecurity Podcast! In this week's episode, hosts Rachael Lyon and Jonathan Knepher are joined by the brilliant Dr. Margaret Cunningham, Technical Director for Security and AI Strategy at Darktrace. With a PhD in Applied Experimental Psychology and multiple patents to her name, Dr. Cunningham is a leading voice in human-centered security, behavioral analytics, and the ever-evolving intersection of people and technology. Together, the trio dives into the fast-changing landscape of AI-driven threats—think voice cloning, deepfakes, and sophisticated social engineering attacks that challenge every notion of trust and identity. From the real-world dangers of phone scams using cloned voices, to high-profile incidents like the Coinbase insider threat and the rise of groups like Scattered Spider, you'll hear stories that illuminate both the risks and solutions shaping today's enterprise security. They explore the future (and limits) of authentication, the importance—and pitfalls—of data collection, and why behavioral analytics are more crucial than ever in spotting anomalies. Dr. Cunningham also shares insights on transparency, industry responses, and the human factors that make cybersecurity so complex and fascinating. For links and resources discussed in this episode, please visit our show notes at https://www.forcepoint.com/govpodcast/e350

Ist die Regulierung ein notwendiger Meilenstein für vertrauenswürdige KI oder doch ein Innovationshemmnis, das Europa ausbremst? Dazu haben wir in dieser Episode zwei absolute Top-Experten zu Gast. Dagmar Schuller, Professorin für Wirtschaftsinformatik & Digital Entrepreneurship an der Hochschule Landshut in Bayern, äußert sich kritisch zum EU-AI-Act. Dr. Philipp Hartmann, Director of AI Strategy bei der appliedAI Initiative, bewertet die EU-Vorgaben hingegen als Enabler für KI-Unternehmen.

1011: Build with AI. Lead with people. In this episode of Technovation, host Peter High speaks with Jennifer Charters, Executive Vice President and Chief Information Officer of Lincoln Financial. Jennifer shares how she's shaping the future of IT and innovation at the $18.5B insurer by investing in AI while doubling down on what makes transformation succeed: people. She discusses Lincoln's evolving enterprise AI strategy, why a model-agnostic approach matters, and how her team is redesigning workflows and talent models in parallel. From regulatory complexity to the rise of AI agents, Jennifer emphasizes the need to prepare rather than predict the future, and to keep human connection at the center of it. Key topics include: A 401(k)-style framework for IT budgeting and innovation How Lincoln's model-agnostic AI architecture supports agility AI use cases in development, cybersecurity, and customer experience Partnering with HR to future-proof skills and change readiness

Welcome to The Power Lounge, the platform where women shaping the digital landscape share their experiences. In "Your Edge in the Age of AI," host Amy Vaughan engages with Monica Froese, founder of Empowered Business and a leader in digital strategy and AI innovation. Monica discusses her personal journey—from overcoming a divorce and single motherhood to establishing a seven-figure business—while effectively utilizing AI to regain her time and mental focus.Many find the surge of AI both exciting and daunting. Monica illustrates her transformation from initially overlooking AI tools like ChatGPT to embedding them into her professional and personal routines. This adoption revolutionized aspects such as meal planning, email management, business operations, and parenting responsibilities. The discussion offers actionable strategies for women aiming to harness AI to save time, reduce decision fatigue, and enhance their influence without experiencing burnout.Whether you're managing a team, running your own enterprise, or balancing daily responsibilities, this conversation will reshape your perception of AI. Discover how to leverage AI as a strategic asset to work more efficiently and reclaim control over your time.Chapters:00:00 – Overwhelmed by ChatGPT Launch06:02 – From Google to ChatGPT Transition08:41 – AI as Accountability Partner10:43 – Personalized Writing Style Guide Creation14:29 – Choosing the Right LLM17:39 – Empowering Women in Corporate Tech21:03 – AI: The Small Business Equalizer24:15 – Business Efficiency via AI Team27:32 – AI as Collaborative Assistant30:58 – Building High-Converting Digital Products36:08 – Authenticity Lies Within the User37:04 – Human Connection in Digital Age42:07 – Multi-Channel Content Distribution44:34 – Conversational Prompting Effectiveness47:32 – Effective Prompting: Finding the Use Case51:18 – Empowering Women: AI's Evolving Role53:45 – AI Aiding Women in Divorce59:38 – Technology as Empowerment Tool01:00:25 – Keep Asking, Keep GrowingQuotes:"Let technology empower you. Start small, experiment, and reclaim your time."- Amy Vaughan"AI lightens your mental load, frees your time, and enables you to be your best self."- Monica FroeseKey Takeaways:Overcoming the OverwhelmAI: Your Mental Load BusterJust Start with One ToolTrain Your Digital “Mini-Mes”AI as the Ultimate EqualizerFrom Burnout to BoundariesAuthenticity Still ReignsAI for Everyday EmpowermentTry, Play, and GrowConnect with Monica Froese:LinkedIn: https://www.linkedin.com/in/monicafroese/Website:https://monicafroese.com/Connect with the host Amy Vaughan:LinkedIn: http://linkedin.com/in/amypvaughanPodcast:Power Lounge Podcast  - Together DigitalLearn more about Together Digital and consider joining the movement by visitingHome - Together DigitalSupport the show

40% of workers will need to reskill in the next three years due to AI and automation. Yet many companies still deprioritize frontline education. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Mark Suman is CoFounder of OpenSecret and Maple. OpenSecret is a platform for building private and secure apps and Maple is an AI tool built using OpenSecret. Maple offers users and developers an easy way to interact with popular open source AI models.Marks on Nostr: https://primal.net/marksMarks on X: https://x.com/marks_ftwMaple on Nostr: https://primal.net/mapleaiMaple on X: https://x.com/TryMapleAIMaple: https://trymaple.ai/OpenSecret: https://opensecret.cloud/EPISODE: 177BLOCK: 913963PRICE: 898 sats per dollar(00:01:38) Happy Bitcoin Tuesday(00:03:05) Marks and Maple AI(00:07:10) Apple's AI Strategy and Product Unveiling(00:11:40) Privacy and Security in AI with Maple(00:19:59) Open Source AI Models and Industry Trends(00:27:02) Freedom of Thought and AI's Influence(00:39:00) User Experience and Privacy in Maple AI(00:48:50) AI and Parenting(01:02:41) Maple AI Developer API and Proxy Feature(01:16:00) Open Secret and Maple AI: Company OverviewVideo: https://primal.net/e/nevent1qqsx7ypznejxgujpqdwnch5w6pzeh03pn9fvr5guqpry930e7w3yqycllz5kmmore info on the show: https://citadeldispatch.comlearn more about me: https://odell.xyz

The Transformation Ground Control podcast covers a number of topics important to digital and business transformation. This episode covers the following topics and interviews:   The Microsoft Study About Jobs Being At Risk From AI, Q&A (Darian Chwialkowski, Third Stage Consulting) How Microsoft is Approaching Enterprise Technology (Mason Whitaker, CEO of Volt Technologies) Metcash's ERP Failure   We also cover a number of other relevant topics related to digital and business transformation throughout the show.  

In this episode of Interlinks, I'm joined once again by Lisa Anderson, President of LMA Consulting Group and one of North America's foremost supply chain advisors. Lisa brings deep expertise across ERP systems, SIOP processes, and manufacturing transformation, and is widely recognized for her work helping manufacturers and distributors modernize operations and enhance customer responsiveness. With her pragmatic approach and clear-sighted industry perspective, Lisa is a valuable voice on how emerging technologies—particularly AI—are reshaping the operational landscape.Our conversation explores the strategic imperative of supply chain visibility in today's turbulent business environment, with a focus on how AI tools can deliver actionable insights. We discuss the foundational systems—such as ERP, MES, and CRM—that enable AI to function effectively, and how organizations of different sizes can adopt and scale visibility solutions. A key theme is the need to balance innovation with discipline: while large enterprises may have scale and systems, smaller firms often outperform through agility, experimentation, and faster decision-making cycles. Lisa also offers practical guidance on pilot projects, process transformation, and the role of human judgment in ensuring AI delivers real business value.Zooming out, the episode situates AI-powered visibility within the broader context of global supply chain transformation. As manufacturing and logistics networks become increasingly digitized and dynamic, visibility is no longer a luxury but a necessity. AI has the potential to move firms from reactive to predictive operating models, enabling smarter allocation of resources, faster customer response, and more resilient planning. But Lisa is clear: technology alone is not enough. The winners will be those who embed these tools within disciplined processes and informed decision-making cultures—where strategic intent meets operational execution. Hosted on Acast. See acast.com/privacy for more information.

In Episode 92 of the Digital Velocity Podcast, Erik Martinez talks with Timothy Peterson—an executive leader with 25+ years across retail, e‑commerce, data, and operations—about how to integrate artificial intelligence thoughtfully and profitably. Drawing on roles from Bloomingdale's and Pottery Barn to CPG business intelligence and today's fractional CEO work, Timothy shares a pragmatic, cross‑industry view of what it really takes to make AI create business value.  Timothy highlights hyper‑personalization at scale as the standout opportunity: using hundreds of relevant data sources to tailor experiences that deepen engagement and drive growth. But he cautions that rushing in can erode trust—especially when AI replaces human judgment in customer service or when proprietary content is scraped into training sets without authorization. The takeaway for brand leaders is clear: protect your data, protect your customers, and don't let AI tools redefine your value proposition without intent.  To prioritize investments, Peterson lays out a simple sequence: first upskill people (think weekly lunch‑and‑learns, practical workshops, and targeted certifications), then pilot tools to learn what really moves the needle, and only then fund larger infrastructure. He also introduces “governance as a service,” ensuring responsibility for privacy, compliance, and ethics is shared across legal, marketing, and operations—rather than bolted onto a single role within the company. Clear accountability and measured rollout beat shiny‑object adoption every time.  For direct‑to‑consumer marketing leaders, the playbook is refreshingly grounded: personalize to lift conversion and LTV, document and simplify processes so AI augments what already works, narrow your focus to the channels and products that matter, and measure the impact on sentiment, conversion, lead flow, and revenue. Above all, stay adaptable and keep learning—the real competitive advantage isn't any one model or tool, but a culture that can turn new capability into sustained customer value. 

Three leading ISV executives from Coveo, DTEX Systems and Honeycomb, reveal how companies with proprietary datasets are gaining unbeatable competitive advantages in the AI era and share real-world strategies how you have similar outcomes.Topics Include:Panel introduces three ISV leaders discussing data platform transformation for AIDTEX focuses on insider threats, Coveo on enterprise search, Honeycomb on observabilityCompanies with proprietary datasets gain strongest competitive advantage in AI transformationData gravity concept: LLMs learning from unique datasets create defensible business positionsCoveo maintains unified enterprise index with real-time content and access rights syncHoneycomb enables subsecond queries for analyzing logs, traces, and metrics at scaleMulti-tenant architectures balance shared infrastructure benefits with single-tenant data separationCoveo deployed 140,000 times last year using mostly multi-tenant, some single-tenant componentsDTEX scaled from thousands to hundreds of thousands endpoints after architectural transformationCapital One partnership taught DTEX how to break monolithic architecture into servicesApache Iceberg and open table formats enable interoperability without data duplicationHoneycomb built custom format following similar patterns with hot/cold storage tiersBusiness data catalogs become critical for AI agents understanding dataset contextMCP servers allow AI systems to leverage structured cybersecurity datasets effectivelyDTEX used Cursor with their data to identify North Korean threat actorsReal-time AI data needs balanced with costs using right models for jobsCaching strategies and precise context reduce expensive LLM inference calls unnecessarilySearch remains essential for enterprise AI to prevent hallucination and access informationROI measurement focuses on cost reduction, analyst efficiency, and measurable business outcomesKey takeaway: invest in data structure early, context is king, AI is just softwareParticipants:Sebastien Paquet - Vice President of AI Strategy, CoveoRajan Koo - CTO, DTEX SystemsPatrick King - Head of Data, Honeycomb.ioKP Bhat - Sr Solutions Architecture Leader- Analytics & AI, Amazon Web ServicesFurther Links:Coveo: Website – LinkedIn – AWS MarketplaceDTEX Systems: Website – LinkedIn – AWS MarketplaceHoneycomb.io: Website – LinkedIn – AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Too often, AI breaks in the wild. Why? CXOTalk 890 dissects the adversarial economy with Steven C. Daffron (fintech private equity leader) and Anthony Scriffignano (distinguished data scientist), hosted by Michael Krigsman. Discover the challenges of **ai implementation** and the strategies needed to navigate the **future of work** in an AI-driven world. Stay informed with expert insights on CXOTalk. What you'll learn:How AI enables and masks adversarial behaviorMisaligned incentives, data/model drift, and biasGovernance vs. regulation; resilient metrics and KPIsInvestor/CFO implications and talent/education needs 

AI growth with no rules? That's not bold. It's reckless.Everyone's racing to scale AI. More data, faster tools, flashier launches.But here's what no one's saying out loud:Growth without governance doesn't make you innovative. It makes you vulnerable.Ignore ethics, and you're building an empire on quicksand.In this episode, we're breaking down how to scale AI the right way—without wrecking trust, compliance, or your future.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Questions for Rajeev or Jordan? Go ask.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Balancing AI Innovation with Ethical GovernanceIntroduction of Rajeev Kapur and Eleven o Five MediaRajeev Kapur's Background in AICompanies Balancing AI Innovation and EthicsFormation of AI Ethics BoardData Management as Competitive AdvantagePrivacy and Ethics as Product FeaturesGovernance and Ethical Standards in AI UseImpact of Regulatory Changes on AI UseDeepfakes and Their ImplicationsEncouragement for Companies to Lead Ethically in AITimestamps:00:00 Navigating AI: Innovation vs. Risks04:00 "AI Startup's Spatial Audio Journey"06:49 AI Ethics Oversight & Governance10:04 Strategic AI Advisory Team Formation15:34 AI Strategy and Governance Essentials16:55 Global Standardization Needed for AI Policies22:47 AI Ethics: Innovation vs. Deepfakes25:48 "Regulate Deepfakes Like Nukes"27:17 Leadership Vision for Future SuccessKeywords:AI innovation, Ethical governance, Large language models, Data privacy, AI ethics board, AI governance, TDWI, Microsoft stack, Generative AI, AI algorithms, Spatial audio, Deep fakes, Data differentiation, Machine learning, Cyber security, Enterprise technology, Rajeev Kapur, 11:05 Media, AI safety, OpenAI, Data utilization, Ethical AI alignment, Regulatory aspect, AI models, Innovation vs. ethics, AI data privacy, Explainability, Data scientists, Third-party audits, Transparent AI usage, AI-driven growth, Monitoring feedback loops, Worst case testing, Smart regulations, Digital twins, Disinformation, AI bias mitigation, Data as new oil, Refining dataSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner

This discussion takes a closer look at what this shakeup signals about Meta's priorities. Hear our take on whether the restructuring sets Meta apart.Try AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle

Explore the big moves happening with what this shakeup signals about Meta's priorities. Tune in for insights into the company's bold strategy.Try AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle

Send in your questions to hrask.org Download all the key takeaways from this episode down below: https://tinyurl.com/bdf9v66d   Episode 342: We all have daily tasks that keep things running, but we're quickly approaching a time when AI can handle some of the everyday loads. Discover how YOU can lead more strategically by focusing on what truly needs a human touch and what doesn't. Phil and special guest Lauren Patel reveal a smarter way to prioritize using the Eisenhower Matrix, now enhanced with AI and automation. Timestamps:  0:00 – Welcome & AI Time-Saving Insights 1:21 – Meet Lauren Patel: AI Power User & Show Favorite 3:01 – Using AI in Everyday Life (Weeds, Trips, and Homework) 5:05 – AI vs. AI: Candidates vs. Recruiters 7:15 – Meet Amy Hart: Trusted AI for HR Professionals 9:30 – The No-AI Policy Dilemma in Organizations 14:01 – How HR Pros Can Start with AI: The Eisenhower Matrix 22:01 – Recruiting with AI: Job Ads, Resumes & Vendor Transparency 25:57 – AI in Crisis Management & HR Fires 32:10 – Insight on AI from Burt & Upcoming Events #AIinHR #EisenhowerMatrix #WorkSmarter #HRLeadership #HRStrategy #ProductivityTools #HRTech #AutomationInHR #TimeManagement #FutureOfWork #HumanResources #HRInnovation #AIProductivity #TaskManagement #LeadershipDevelopment #AAIM #AAIMEA #ThisWeekAtWork

The Transformation Ground Control podcast covers a number of topics important to digital and business transformation. This episode covers the following topics and interviews:   Behind the Scenes at Stratosphere Interviews with Jan Baan: Rappit, Stanislaw Karpinski: ANEGIS, Marcus Harris: Taft Law, Tiffany Canada & Tanya Gonzalez: Infor Stratosphere Vendor Panel   We also cover a number of other relevant topics related to digital and business transformation throughout the show.  

When boutique furniture brand Kouboo embraced AI search optimization, they didn’t just tweak their SEO—they reimagined it. In a focused 7-day test, Kouboo achieved an impressive 53% visibility in ChatGPT and Perplexity results for high-intent prompts, ranking #1 among all competing brands. This rapid rise in AI-driven visibility showed how a targeted AI strategy can…

We paused for the holiday, but the AI news didn't! In this episode of The Artificial Intelligence Show, Paul Roetzer and Mike Kaput explore how AI is already reshaping the job market, with new research showing sharp declines in entry-level roles. They unpack Silicon Valley's $100M super PAC aimed at blocking AI regulation, highlight Google's breakthrough “Nano Banana” image editor, Meta's AI team struggles, and more in our rapid-fire section. Show Notes: Access the show notes and show links here Timestamps:  00:00:00 — Intro 00:07:17 — AI Labor Market Signals 00:16:37 — AI Industry's Increasing Political Influence 00:28:33 — Google's Stunning “Nano Banana” Image Editor 00:34:26 — OpenAI Parental Controls and Support Features 00:38:23 — Anthropic Settles Authors' Copyright Lawsuit 00:42:44 — Meta's AI Strategy in Flux 00:46:06 — GenAI App Landscape Report 00:51:10 — OpenAI–Anthropic Joint Safety Evaluation 00:54:37 — Jensen Huang Suggests AI Will Create a Four-Day Workweek 01:00:11 — Microsoft's AI Excel Warning 01:03:17 — Claude in Classrooms 01:07:07 — AI Product and Funding Updates  This episode is brought to you by AI Academy by SmarterX. AI Academy is your gateway to personalized AI learning for professionals and teams. Discover our new on-demand courses, live classes, certifications, and a smarter way to master AI. Learn more here. This week's episode is brought to you by MAICON, our 6th annual Marketing AI Conference, happening in Cleveland, Oct. 14-16. The code POD100 saves $100 on all pass types. For more information on MAICON and to register for this year's conference, visit www.MAICON.ai. Visit our website Receive our weekly newsletter Join our community: Slack LinkedIn Twitter Instagram Facebook Looking for content and resources? Register for a free webinar Come to our next Marketing AI Conference Enroll in our AI Academy 

In this episode, Karen speaks with Cali Wood, Head of Data & AI Strategy & Culture at AXA UK, about what it really means to future-proof your career in a world where GenAI is reshaping the skills landscape. From the rise of AI agents and natural language as a “coding language” to the growing importance of human skills like communication, ethics, and business understanding, Cali shares her experience based view on how AI is changing our field. She delves into: Practical AI use cases at AXA and their impact on data democratisation, and on the data team How the skills landscape is shifting and provides practical advice for early- to mid-career data professionals — and the leaders guiding them. How to stay relevant, collaborate with AI instead of competing against it, and use new tools to work smarter, not just faster.  Cali also reveals why curiosity, boldness, and a willingness to challenge the status quo will be the superpowers of tomorrow's data workforce. If you've ever wondered where our industry was heading, or what your role might look like in the future — and how to make sure you're ready — this conversation is for you.

The Transformation Ground Control podcast covers a number of topics important to digital and business transformation. This episode covers the following topics and interviews:   How API's are the Key to Agentic AI, Q&A (Darian Chwialkowski, Third Stage Consulting) Surviving the Chaos of Digital Transformation (Darian Chwialkowski, Third Stage Consulting) How to Start an AI Tech Company   We also cover a number of other relevant topics related to digital and business transformation throughout the show.  

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss why enterprise generative AI projects often fail to reach production. You’ll learn why a high percentage of enterprise generative AI projects reportedly fail to make it out of pilot, uncovering the real reasons beyond just the technology. You’ll discover how crucial human factors like change management, user experience, and executive sponsorship are for successful AI implementation. You’ll explore the untapped potential of generative AI in back-office operations and process optimization, revealing how to bridge the critical implementation gap. You’ll also gain insights into the changing landscape for consultants and agencies, understanding how a strong AI strategy will secure your competitive advantage. Watch now to transform your approach to AI adoption and drive real business results! Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-why-enterprise-generative-ai-projects-fail.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 – 00:00 In this week’s In Ear Insights, the big headline everyone’s been talking about in the last week or two about generative AI is a study from MIT’s Nanda project that cited the big headline: 95% of enterprise generative AI projects never make it out of pilot. A lot of the commentary clearly shows that no one has actually read the study because the study is very good. It’s a very good study that walks through what the researchers are looking at and acknowledged the substantial limitations of the study, one of which was that it had a six-month observation period. Katie, you and I have both worked in enterprise organizations and we have had and do have enterprise clients. Some people can’t even buy a coffee machine in six months, much less route a generative AI project. Christopher S. Penn – 00:49 But what I wanted to talk about today was some of the study’s findings because they directly relate to AI strategy. So if you are not an AI ready strategist, we do have a course for that. Katie Robbert – 01:05 We do. As someone, I’ve been deep in the weeds of building this AI ready strategist course, which will be available on September 2. It’s actually up for pre-sale right now. You go to trust insights AI/AI strategy course. I just finished uploading everything this morning so hopefully I used all the correct edits and not the ones with the outtakes of me threatening to murder people if I couldn’t get the video done. Christopher S. Penn – 01:38 The bonus, actually, the director’s edition. Katie Robbert – 01:45 Oh yeah, not to get too off track, but there was a couple of times I was going through, I’m like, oops, don’t want to use that video. But back to the point, so obviously I saw the headline last week as well. I think the version that I saw was positioned as “95% of AI pilot projects fail.” Period. And so of course, as someone who’s working on trying to help people overcome that, I was curious. When I opened the article and started reading, I’m like, “Oh, well, this is misleading,” because, to be more specific, it’s not that people can’t figure out how to integrate AI into their organization, which is the problem that I help solve. Katie Robbert – 02:34 It’s that people building their own in-house tools are having a hard time getting them into production versus choosing a tool off the shelf and building process around it. That’s a very different headline. And to your point, Chris, the software development life cycle really varies and depends on the product that you’re building. So in an enterprise-sized company, the likelihood of them doing something start to finish in six months when it involves software is probably zero. Christopher S. Penn – 03:09 Exactly. When you dig into the study, particularly why pilots fail, I thought this was a super useful chart because it turns out—huge surprise—the technology is mostly not the problem. One of the concerns—model quality—is a concern. The rest of these have nothing to do with technology. The rest of these are challenging: Change management, lack of executive sponsorship, poor user experience, or unwillingness to adopt new tools. When we think about this chart, what first comes to mind is the 5 Ps, and 4 out of 5 are people. Katie Robbert – 03:48 It’s true. One of the things that we built into the new AI strategy course is a 5P readiness assessment. Because your pilot, your proof of concept, your integration—whatever it is you’re doing—is going to fail if your people are not ready for it. So you first need to assess whether or not people want to do this because that’s going to be the thing that keeps this from moving forward. One of the responses there was user experience. That’s still people. If people don’t feel they can use the thing, they’re not going to use it. If it’s not immediately intuitive, they’re not going to use it. We make those snap judgments within milliseconds. Katie Robbert – 04:39 We look at something and it’s either, “Okay, this is interesting,” or “Nope,” and then close it out. It is a technology problem, but that’s a symptom. The root is people. Christopher S. Penn – 04:52 Exactly. In the rest of the paper, in section 6, when it talks about where the wins were for companies that were successful, I thought this was interesting. Lead qualification, speed, customer retention. Sure, those are front office things, but the paper highlights that the back office is really where enterprises will win using generative AI. But no one’s investing it. People are putting all the investment up front in sales and marketing rather than in the back office. So the back office wins. Business process optimization. Elimination: $2 million to $10 million annually in customer service and document processing—especially document processing is an easy win. Agency spend reduction: 30% decrease in external, creative, and content costs. And then risk checks for financial services by doing internal risk management. Christopher S. Penn – 05:39 I thought this was super interesting, particularly for our many friends and colleagues who work at agencies, seeing that 30% decrease in agency spend is a big deal. Katie Robbert – 05:51 It’s a huge deal. And this is, if we dig into this specific line item, this is where you’re going to get a lot of those people challenges because we’re saying 30% decrease in external creative and content costs. We’re talking about our designers and our writers, and those are the two roles that have felt the most pressure of generative AI in terms of, “Will it take my job?” Because generative AI can create images and it can write content. Can it do it well? That’s pretty subjective. But can it do it? The answer is yes. Christopher S. Penn – 06:31 What I thought was interesting says these gains came without material workforce reduction. Tools accelerated work, but did not change team structures or budgets. Instead, ROI emerged from reduced external spend, limiting contracts, cutting agency fees, replacing expensive consultants with AI-powered internal capabilities. So that makes logical sense if you are spending X dollars on something, an agency that writes blog content for you. When we were back at our old PR agency, we had one firm that was spending $50,000 a month on having freelancers write content that when you and I reviewed, it was not that great. Machines would have done a better job properly prompted. Katie Robbert – 07:14 What I find interesting is it’s saying that these gains came without material workforce reduction, but that’s not totally true because you did have to cut your agency fees, which is people actually doing the work, and replacing expensive consultants with AI-powered internal capabilities. So no, you didn’t cut workforce reduction at your own company, but you cut it at someone else’s. Christopher S. Penn – 07:46 Exactly. So the red flag there for anyone who works in an agency environment or a consulting environment is how much risk are you at from AI taking your existing clients away from you? So you might not lose a client to another agency—you might lose a client to an internal AI project where if there isn’t a value add of human beings. If your agency is just cranking out templated press releases, yeah, you’re at risk. So I think one of the first things that I took away from this report is that every agency should be doing a very hard look at what value it provides and saying, “How easy is it for AI to replicate this?” Christopher S. Penn – 08:35 And if you’re an agency and you’re like, “Oh, well, we can just have AI write our blog posts and hand it off to the client.” There’s nothing stopping the client from doing that either and just getting rid of you entirely. Katie Robbert – 08:46 The other thing that sticks out to me is replacing expensive consultants with AI-powered internal capabilities. Technically, Chris, you and I are consultants, but we’re also the first ones to knock the consulting industry as a whole, because there’s a lot of smoke and mirrors in the consulting industry. There’s a lot of people who talk a big talk, have big ideas, but don’t actually do anything useful and productive. So I see this and I don’t immediately think, “Oh, we’re in trouble.” I think, “Oh, good, it’s going to clear out the rest of the noise in the industry and make way for the people who can actually do something.” Christopher S. Penn – 09:28 And that is the heart and soul, I think, for us. Obviously, we have our own vested interest in ensuring that we continue to add value to our clients. But I think you’re absolutely right that if you are good at the “why”—which is what a lot of consulting focuses on—that’s important. If you’re good at the “what”—which is more of the tactical stuff, “what are you going to do?”—that’s important. But what we see throughout this paper is the “how” is where people are getting tangled up: “How do we implement generative AI?” If you are just a navel-gazing ChatGPT expert, that “how” is going to bite you really hard really soon. Christopher S. Penn – 10:13 Because if you go and read through the rest of the paper, one of the things it talks about is the gap—the implementation gap between “here’s ChatGPT” and then for the enterprise it was like, “Well, here’s all of our data and all of our systems and all of our everything else that we want AI to talk to in a safe and secure way.” And this gap is gigantic between these two worlds. So tools like ChatGPT are being relegated to, “Let’s write more blog posts and write some press releases and stuff” instead of “help me actually get some work done with the things that I have to do in a prescribed way,” because that’s the enterprise. That gap is where consulting should be making a difference. Christopher S. Penn – 10:57 But to your point, with a lot of navel-gazing theorists, no one’s bridging that gap. Katie Robbert – 11:05 What I find interesting about the shift that we’ve seen with generative AI is we’ve almost in some ways regressed in the way that work is getting done. We’re looking at things as independent, isolated tasks versus fully baked, well-documented workflows. And we need to get back to those holistic 360-degree workflows to figure out where we can then insert something generative AI versus picking apart individual tasks and then just having AI do that. Now I do think that starting with a proof of concept on an individual task is a good idea because you need to demonstrate some kind of success. You need to show that it can do the thing, but then you need to go beyond that. It can’t just forever, to your point, be relegated to writing blog posts. Katie Robbert – 12:05 What does that look like as you start to expand it from project to program within your entire organization? Which, I don’t know if you know this, there’s a whole lesson about that in the AI strategy course. Just figured I would plug that. But all kidding aside, that’s one of the biggest challenges that I’m seeing with organizations that “disrupt” with AI is they’re still looking at individual tasks versus workflows as a whole. Christopher S. Penn – 12:45 Yep. One of the things that the paper highlighted was that the reason why a lot of these pilots fail is because either the vendor or the software doesn’t understand the actual workflow. It can do the miniature task, but it doesn’t understand the overall workflow. And we’ve actually had input calls with clients and potential clients where they’ve walked us through their workflow. And you realize AI can’t do all of it. There’s just some parts that just can’t be done by AI because in many cases it’s sneaker-net. It’s literally a human being who has to move stuff from one system to another. And there’s not an easy way to do that with generative AI. The other thing that really stood out for me in terms of bridging this divide is from a technological perspective. Christopher S. Penn – 13:35 The biggest hurdle from the technology side was cited as no memory. A tool like ChatGPT and stuff has no institutional memory. It can’t easily connect to your internal knowledge bases. And at an enterprise, that’s a really big deal. Obviously, at Trust Insights’ size—with five or four employees and a bunch of AI—we don’t have to synchronize and coordinate massive stores of institutional knowledge across the team. We all pretty much know what’s going on. When you are an IBM with 300,000 employees, that becomes a really big issue. And today’s tools, absent those connectors, don’t have that institutional memory. So they can’t unlock that value. And the good news is the technology to bridge that gap exists today. It exists today. Christopher S. Penn – 14:27 You have tools that have memory across an entire codebase, across a SharePoint instance. Et cetera. But where this breaks down is no one knows where that information is or how to connect it to these tools, and so that huge divide remains. And if you are a company that wants to unlock the value of gen AI, you have to figure out that memory problem from a platform perspective quickly. And the good news is there’s existing tools that do that. There’s vector databases and there’s a whole long list of acronyms and tongue twisters that will solve that problem for you. But the other four pieces need to be in place to do that because it requires a huge lift to get people to be willing to share their data, to do it in a secure way, and to have a measurable outcome. Katie Robbert – 15:23 It’s never a one-and-done. So who owns it? Who’s going to maintain it? What is the process to get the information in? What is the process to get the information out? But even backing up further, the purpose is why are we doing this in the first place? Are we an enterprise-sized company with so many employees that nobody knows the same information? Or am I a small solopreneur who just wants to have some protection in case something happens and I lose my memory or I want to onboard someone new and I want to do a knowledge-share? And so those are very different reasons to do it, which means that your approach is going to be slightly different as well. Katie Robbert – 16:08 But it also sounds like what you’re saying, Chris, is yes, the technology exists, but not in an easily accessible way that you could just pick up a memory stick off the shelf, plug it in, and say, “Boom, now we have memory. Go ahead and tell it everything.” Christopher S. Penn – 16:25 The paper highlights in section 6.5 where things need to go right, which is Agentic AI. In this case, Agentic AI is just fancy for, “Hey, we need to connect it to the rest of our systems.” It’s an expensive consulting word and it sounds cool. Agentic AI and agentic workflows and stuff, it really just means, “Hey, you’ve got this AI engine, but it’s not—you’re missing the rest of the car, and you need the rest of the car.” Again, the good news is the technology exists today for these tools to have access to that. But you’re blocking obstacles, not the technology. Christopher S. Penn – 17:05 Your governance is knowing where your data lives and having people who have the skills and knowledge to bring knowledge management practices into a gen AI world because it is different. It is not the same as previous knowledge management initiatives. We remember all the “in” with knowledge management was all the rage in the 90s and early 2000s with knowledge management systems and wikis and internal things and SharePoint and all that stuff, and no one ever kept it up to date. Today, Agentic can solve some of those problems, but you need to have all the other human being stuff in place. The machines can’t do it by themselves. Katie Robbert – 17:51 So yes, on paper it can solve all those problems. But no, it’s not going to. Because if we couldn’t get people to do it in a more analog way where it was really simple and literally just upload the latest document to the server or add 2 lines of detail to your code in terms of what this thing is about, adding more technology isn’t suddenly going to change that. It’s just adding another layer of something people aren’t going to do. I’m very skeptical always, and I just feel this is what’s going to mislead people. They’re like, “Oh, now I don’t have to really think about anything because the machine is just going to know what I know.” But it’s that initial setup and maintenance that people are going to skip. Katie Robbert – 18:47 So the machine’s going to know what it came out of the box with. It’s never going to know what you know because you’ve never interacted with it, you’ve never configured with it, you’ve never updated it, you’ve never given it to other people to use. It’s actually just going to become a piece of shelfware. Christopher S. Penn – 19:02 I will disagree with you there. For existing enterprise systems, specifically Copilot and Gemini. And here’s why. Those tools, assuming they’re set up properly, will have automatic access to the back-end. So they’ll have access to your document store, they’ll have access to your mail server, they’ll have access to those things so that even if people don’t—because you’re right, people ain’t going to do it. People ain’t going to document their code, they’re not going to write up detailed notes. But if the systems are properly configured—and that is a big if—it will have access to all of your Microsoft Teams transcripts, it will have access to all of your Google Meet transcripts and all that stuff. And on the back-end, without participation from the humans, it will at least have a greater scope of knowledge across your company properly configured. Christopher S. Penn – 19:50 That’s the big asterisk that will give those tools that institutional memory. Greater institutional memory than you have now, which at the average large enterprise is really siloed. Marketing has no idea what sales is doing. Sales has no idea what customer service is doing. But if you have a decent gen AI tool and a properly configured back-end infrastructure where the machines are already logging all your documents and all your spreadsheets and all this stuff, without you, the human, needing to do any work, it will generate better results because it will have access to the institutional data source. Katie Robbert – 20:30 Someone still has to set it up and maintain it. Christopher S. Penn – 20:32 Correct. Which is the whole properly configured part. Katie Robbert – 20:36 It’s funny, as you’re going through listing all of the things that it can access, my first thought is most of those transcripts aren’t going to be useful because people are going to hop on a call and instead of getting things done, they’re just going to complain about whatever their boss is asking them to do. And so the institutional knowledge is really, it’s only as good as the data you give it. And I would bet you, what is it that you like to say? A small pastry with the value of less than $5 or whatever it is. Basically, I’ll bet you a cookie that the majority of data that gets into those systems with spreadsheets and transcripts and documents and we’re saying all these things is still junk, is still unuseful. Katie Robbert – 21:23 And so you’re going to have a lot of data in there that’s still garbage because if you’re just automatically uploading everything that’s available and not being picky and not cleaning it and not setting standards, you’re still going to have junk. Christopher S. Penn – 21:37 Yes, you’ll still have junk. Or the opposite is you’ll have issues. For example, maybe you are at a tech company and somebody asks the internal Copilot, “Hey, who’s going to the Coldplay concert this weekend?” So yes, data security and stuff is going to be an equally important part of that to know that these systems have access that is provisioned well and that has granular access control. So that, say, someone can’t ask the internal Copilot, “Hey, what does the CEO get paid anyway?” Katie Robbert – 22:13 So that is definitely the other side of this. And so that gets into the other topic, which is data privacy. I remember being at the agency and our team used Slack, and we could see as admins the stats and the amount of DMs that were happening versus people talking in public channels. The ratios were all wrong because you knew everybody was back-channeling everything. And we never took the time to extract that data. But what was well-known but not really thought of is that we could have read those messages at any given time. And I think that’s something that a lot of companies take for granted is that, “Oh, well, I’m DMing someone or I’m IMing someone or I’m chatting someone, so that must be private.” Christopher S. Penn – 23:14 It’s not. All of that data is going to get used and pulled. I think we talked about this on last week’s podcast. We need to do an updated conversation and episode about data privacy. Because I think we were talking last week about bias and where these models are getting their data and what you need to be aware of in terms of the consumer giving away your data for free. Christopher S. Penn – 23:42 Yep. But equally important is having the internal data governance because “garbage in, garbage out”—that rule never changes. That is eternal. But equally true is, do the tools and the people using them have access to the appropriate data? So you need the right data to do your job. You also want to guard against having just a free-for-all, where someone can ask your internal Copilot, “Hey, what is the CEO and the HR manager doing at that Coldplay concert anyway?” Because that will be in your enterprise email, your enterprise IMs, and stuff like that. And if people are not thoughtful about what they put into work systems, you will see a lot of things. Christopher S. Penn – 24:21 I used to work at a credit union data center, and as an admin of the mail system, I had administrative rights to see the entire system. And because one of the things we had to do was scan every message for protected financial information. And boy, did I see a bunch of things that I didn’t want to see because people were using work systems for things that were not work-related. That’s not AI; it doesn’t fix that. Katie Robbert – 24:46 No. I used to work at a data-entry center for those financial systems. We were basically the company that sat on top of all those financial systems. We did the background checks, and our admin of the mail server very much abused his admin powers and would walk down the hall and say to one of the women, referencing an email that she had sent thinking it was private. So again, we’re kind of coming back to the point: these are all human issues machines are not going to fix. Katie Robbert – 25:22 Shady admins who are reading your emails or team members who are half-assing the documentation that goes into the system, or IT staff that are overloaded and don’t have time to configure this shiny new tool that you bought that’s going to suddenly solve your knowledge expertise issues. Christopher S. Penn – 25:44 Exactly. So to wrap up, the MIT study was decent. It was a decent study, and pretty much everybody misinterpreted all the results. It is worth reading, and if you’d like to read it yourself, you can. We actually posted a copy of the actual study in our Analytics for Marketers Slack group, where you and over 4,000 of the marketers are asking and answering each other’s questions every single day. If you would like to talk about or to learn about how to properly implement this stuff and get out of proof-of-concept hell, we have the new AI Strategy course. Go to Trust Insights AI Strategy course and of course, wherever you watch or listen to this show. Christopher S. Penn – 26:26 If there’s a challenge you’d rather have, go to trustinsights.ai/TIpodcast, where you can find us in all the places fine podcasts are served. Thanks for tuning in. We’ll talk to you on the next one. Katie Robbert – 26:41 Know More About 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. Trust Insights 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. Katie Robbert – 27:33 Trust Insights also offers expert guidance on social media analytics, marketing technology and 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 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 their focus on delivering actionable insights, not just raw data. Trust Insights is adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models, yet they excel at explaining complex concepts clearly through compelling narratives and visualizations. Katie Robbert – 28:39 Data Storytelling. This commitment to clarity and accessibility extends to Trust Insights’ 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’re 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.

Struggling to balance bold ideas with strategy in the AI era? Gain actionable ways to align marketing with business goals, harness AI for growth, and reshape your team for success.And don't forget! You can crush your marketing strategy with just a few minutes a week by signing up for the StrategyCast Newsletter. You'll receive weekly bursts of marketing tips, clips, resources, and a whole lot more. Visit https://strategycast.com/ for more details.==Let's Break It Down==05:48 Strategy: Definitions and Resource Allocation08:29 Clarity in Business Objectives12:31 Adaptive Three-Year Strategy Planning16:17 AI Talent Strategy in Sports Partnerships18:23 AI's Impact on Operational Changes20:29 Future-Proofing Workforce Strategies24:09 Focus on Deliverables and Partnerships27:58 "Predictive Sports Analysis Evolution"31:49 Live Sports Tech Demo34:11 Record-Breaking AI-Driven Engagement Event38:43 "Adapting to AI's Market Impact"==Where You Can Find Us==Website: https://strategycast.com/Instagram: https://www.instagram.com/strategy_cast/Facebook: https://www.facebook.com/strategycast==Leave a Review==Hey there, StrategyCast fans!If you've found our tips and tricks on marketing strategies helpful in growing your business, we'd be thrilled if you could take a moment to leave us a review on Apple Podcasts. Your feedback not only supports us but also helps others discover how they can elevate their business game!

1005: "Great innovations are painkillers, not vitamins." In this episode, Peter High speaks with Shez Partovi, Chief Innovation & Strategy Officer and Chief Business Leader of Enterprise Informatics at Royal Philips, a €18B global health technology leader. Shez shares how Philips is building people- and patient-centric innovation by partnering with healthcare providers, co-creating solutions, and scaling software and AI-driven insights to meet the growing demands of modern care delivery. A former AWS health exec and practicing neuroradiologist, Shez offers a unique lens on the convergence of tech and clinical practice. He outlines how Philips' software-first strategy is accelerating productivity, reducing clinician burnout, and expanding access to care while also navigating AI trust gaps and reshaping internal engineering practices. Key themes include: The strategy behind Philips' health tech transformation AI's role in automation, augmentation, and agility in care delivery Co-creation with health systems to drive scalable impact Philips' dual-speed innovation model (80% business-led, 20% moonshots)

Have you been wondering how AI fits into the world of therapy and private practice?  In this episode, I sit down with Dr. Stephanie Thrower—a psychologist, career coach, and AI educator—who's using tech to help therapists expand their impact, streamline their work, and step into new possibilities beyond one-on-one sessions. We're talking practical tools, smart marketing strategies, and how to use AI without losing your voice (or your sanity). Whether you're just getting curious or already experimenting with AI, you're going to walk away inspired and equipped. In this episode, you'll learn: How AI can save you time and energy in private practice What makes good marketing copy (and how AI can help you write it) How to use AI for content creation—without sounding robotic Why therapists should be involved in building the future of AI Resources Mentioned In This Episode  Watch on YouTube  Use the promo code “GORDON” to get 2 months of Therapy Notes free Consulting with Gordon The PsychCraft Network Meet Dr. Stephanie Thrower Stephanie Thrower is a psychologist and coach helping values-driven practitioners use AI tools to simplify marketing, scale income, and build meaningful, sustainable businesses. With a background in vocational psychology, mental health, performance psychology, and social justice, she guides clients through mindset, messaging, and system-building. Stephanie is also the creator of custom GPT tools that help therapists and coaches reclaim time, express their voice, and show up more consistently online—all while designing innovative, client-centered ways to teach and support growth in the online learning space. Website Growth Program Freebie Instagram Facebook Group

Dr. Shauna Overgaard is the Senior Director of AI Strategy & Frameworks at Mayo Clinic, where she focuses on applying AI and data science to healthcare. She also founded Clarity - Applied Intelligence and served as an Assistant Professor of Health Informatics and Information Management. She is active in several organizations like the Coalition for Health AI (CHAI) and the American Medical Informatics Association (AMIA), and is helping shape the future of AI in healthcare. With over 50 citations to her name, Dr. Overgaard has significantly contributed to AI model documentation, clinical decision support systems, and the ethical implementation of AI in healthcare. Our conversation took place in Fall 2024, and we're starting to see how a lot of these predictions played out!00:00 - Intro04:05 - From rural Canada to a Senior Director at Mayo Clinic06:30 - Innovation culture at Mayo09:22 - It takes 17 years for AI to get to the clinic?! 15:58 - Giving patients ownership over their data21:24 - Can paying patients for their data make ML models more equitable?28:55 - Is bias inescapable with AI?32:19 - Can we make AI more transparent without giving away intellectual property?35:15 - Worries about AI replacing healthcare workers36:52 - Silent Trials: beta-testing AI39:25 - So uh, how's Rochester?42:00 - What gives your life meaning?44:52 - Advice for navigating uncertain times and the AI revolutionDr. Overgaard: linkedin.com/in/shaunaovergaard/Host: Nathan KellerTwitter: @NathanKellerX Linkedin: linkedin.com/in/nathankeller1Producer: Saurin Kantesaria & Garima PuriLinkedIn: Saurin KantesariaLinkedin: linkedin.com/in/garimapuri/

AI is changing how we work. What does that mean for arts and culture? Jen Taylor, Capacity Interactive's Director of AI Strategy and Integration, shares what her research with over 100 arts leaders and administrators reveals about where the field really stands with AI: a mix of curiosity, caution, and untapped opportunity. In this episode, Jen and Monica unpack how AI can save time for under-resourced teams, how organizations can build policies that align with their missions, and why the technology should amplify—not replace—human creativity. This episode is your guide to embracing AI without losing sight of what makes the arts human. LINKS: Capacity Interactive | AI Services and The State of the Arts in 2025 Report Nonprofit Quarterly | How Nonprofits Can Create Ethical AI Policies Reuters | ChatGPT sets record for fastest-growing user base The Marketing AI Institute | 2024 State of Marketing AI Report Anthropic | AI Fluency Course Punchdrunk

The Transformation Ground Control podcast covers a number of topics important to digital and business transformation. This episode covers the following topics and interviews:   Intro to SI's, Q&A (Darian Chwialkowski, Third Stage Consulting) Everything You Need to Know about Selecting the Best Integrator (Bonnie Tinder, CEO & Founder of Raven Intel) How to Select and Implement the Right Systems Integrator   We also cover a number of other relevant topics related to digital and business transformation throughout the show.  

AI projects often fail not due to technology, but because organisations struggle with change. In this episode, we explore practical strategies for enterprise leaders to drive successful AI adoption through structured change management. Using the SHIFT framework, we cover aligning strategy with purpose, managing human emotions, integrating robust frameworks, fostering psychological safety, and turning resistance into momentum. Designed for managers, consultants, and transformation leaders, this episode provides actionable insights to accelerate adoption, build trust, and deliver measurable business impact. 

Professional services firms often face a growth ceiling — struggling to scale without losing client relationships or service quality. In this episode of the Measure Success Podcast, Carl J Cox sits down with Mohan Rao of KnownWell to discuss how AI can help break through that barrier. Mohan explains how their platform turns everyday communication data into actionable insights, helping firms identify client risks, spot expansion opportunities, and strengthen account management. We also explore the “Playing to Win” strategy framework and how it applies to service-based businesses. Tune in to learn how you can use AI to scale without sacrificing client experience.  

The United States and China are locked in a race for dominance in artificial intelligence, including its applications and diffusion. American and Chinese AI firms like OpenAI and DeepSeek respectively have captured global attention and major companies like Google and Microsoft have been actively investing in AI development. While the US currently boasts world-leading AI models, China is ahead in some areas of AI research and application. With the release of US and Chinese AI action plans in July, we may be on the cusp of a new phase in US-China AI competition.Why is AI so important for a country's global influence? What are the strengths of China's AI strategy? And what does China's new AI action plan tell us about its AI ambitions? To discuss these questions, we are joined by Owen Daniels. Owen is the Associate Director of Analysis at Georgetown's Center for Security and Emerging Technology and a Non-Resident Fellow at the Atlantic Council. His recently published article in Foreign Affairs co-authored with Hanna Dohmen -- titled China's Overlooked AI Strategy -- provides insights into how Beijing is utilizing AI to gain global dominance and what the US can and should do to sustain and bolster its lead.Timestamps[00:00] Start [02:05] US Policy Risks to Chinese AI Leadership [05:28] Deepseek and Kimi's Newest Models  [07:54] US vs. China's Approach to AI [10:42] Limitations to China's AI Strategy  [13:08] Using AI as a Soft Power Tool  [16:10] AI Action Plans  [19:34] Trump's Approach to AI Competition [22:30] Can China Lead Global AI Governance?  [25:10] Evolving US Policy for Open Models

The panel discusses Dropbox ending its password service, Sengled smart bulb Alexa support being pulled, and Apple joining other tech giants to digitize healthcare records. Chuck Joiner, David Ginsburg, Eric Bolden, Marty Jencius, Web Bixby, Brian Flanigan-Arthurs, Jim Rea, and Mark Fuccio debate interoperability challenges, Apple's evolving AI strategy and privacy trade-offs, celebrate 3 billion iPhones sold, and examine Apple's lawsuit against Apple Cinemas for trademark concerns after its San Francisco expansion.  Take Control Books brings you this edition of MacVoices. Get the answers you need now from leading experts. Show Notes: Chapters: [0:00] Introductions and Panel Banter[3:55] Public Service Announcements: Dropbox Passwords, Sengled Alexa Support[9:12] Apple Joins Push to Digitize Healthcare Records[22:15] Apple's AI Strategy and “Answers” Team Discussion[33:27] 3 Billion iPhones Sold: Milestone Reflections[38:49] Apple Lawsuit Against Apple Cinemas Expansion Links: Users left scrambling for a plan B as Dropbox drops Dropbox Passwordshttps://www.theregister.com/2025/07/30/dropbox_drops_dropbox_passwords/ Amazon yanks Sengled's Alexa skill after a series of service outageshttps://www.pcworld.com/article/2864586/amazon-yanks-sengleds-alexa-skill-after-a-series-of-service-outages.html Apple and others back government plan to digitize healthcare https://appleinsider.com/articles/25/07/30/apple-and-others-back-government-plan-to-digitize-healthcare XKCDhttps://xkcd.com/927/ Apple now looking to rival ChatGPT with a new in-house 'Answers' team: report https://9to5mac.com/2025/08/03/apple-rivaling-chatgpt-with-new-internal-team-report/ Tim Cook holds company-wide meeting to address Apple's AI woeshttps://9to5mac.com/2025/08/01/tim-cook-holds-company-wide-meeting-to-address-apples-ai-woes/ Tim Cook: Apple just sold its three-billionth iPhonehttps://9to5mac.com/2025/07/31/tim-cook-apple-just-sold-its-three-billionth-iphone/ Apple Files Lawsuit Against Owners of Apple Cinemas for Attempting to Capitalize on Its Name https://www.mactrast.com/2025/08/apple-files-lawsuit-against-owners-of-apple-cinemas-for-attempting-to-capitalize-on-its-name/ Guests: Web Bixby has been in the insurance business for 40 years and has been an Apple user for longer than that.You can catch up with him on Facebook, Twitter, and LinkedIn, but prefers Bluesky. Eric Bolden is into macOS, plants, sci-fi, food, and is a rural internet supporter. You can connect with him on Twitter, by email at embolden@mac.com, on Mastodon at @eabolden@techhub.social, on his blog, Trending At Work, and as co-host on The Vision ProFiles podcast. Brian Flanigan-Arthurs is an educator with a passion for providing results-driven, innovative learning strategies for all students, but particularly those who are at-risk. He is also a tech enthusiast who has a particular affinity for Apple since he first used the Apple IIGS as a student. You can contact Brian on twitter as @brian8944. He also recently opened a Mastodon account at @brian8944@mastodon.cloud. Mark Fuccio is actively involved in high tech startup companies, both as a principle at piqsure.com, or as a marketing advisor through his consulting practice Tactics Sells High Tech, Inc. Mark was a proud investor in Microsoft from the mid-1990's selling in mid 2000, and hopes one day that MSFT will be again an attractive investment. You can contact Mark through Twitter, LinkedIn, or on Mastodon. David Ginsburg is the host of the weekly podcast In Touch With iOS where he discusses all things iOS, iPhone, iPad, Apple TV, Apple Watch, and related technologies. He is an IT professional supporting Mac, iOS and Windows users. Visit his YouTube channel at https://youtube.com/daveg65 and find and follow him on Twitter @daveg65 and on Mastodon at @daveg65@mastodon.cloud. Dr. Marty Jencius has been an Associate Professor of Counseling at Kent State University since 2000. He has over 120 publications in books, chapters, journal articles, and others, along with 200 podcasts related to counseling, counselor education, and faculty life. His technology interest led him to develop the counseling profession ‘firsts,' including listservs, a web-based peer-reviewed journal, The Journal of Technology in Counseling, teaching and conferencing in virtual worlds as the founder of Counselor Education in Second Life, and podcast founder/producer of CounselorAudioSource.net and ThePodTalk.net. Currently, he produces a podcast about counseling and life questions, the Circular Firing Squad, and digital video interviews with legacies capturing the history of the counseling field. This is also co-host of The Vision ProFiles podcast. Generally, Marty is chasing the newest tech trends, which explains his interest in A.I. for teaching, research, and productivity. Marty is an active presenter and past president of the NorthEast Ohio Apple Corp (NEOAC). Jim Rea built his own computer from scratch in 1975, started programming in 1977, and has been an independent Mac developer continuously since 1984. He is the founder of ProVUE Development, and the author of Panorama X, ProVUE's ultra fast RAM based database software for the macOS platform. He's been a speaker at MacTech, MacWorld Expo and other industry conferences. Follow Jim at provue.com and via @provuejim@techhub.social on Mastodon. Support:      Become a MacVoices Patron on Patreon     http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:     http://macvoices.com      Twitter:     http://www.twitter.com/chuckjoiner     http://www.twitter.com/macvoices      Mastodon:     https://mastodon.cloud/@chuckjoiner      Facebook:     http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:     http://www.facebook.com/macvoices/      MacVoices Group on Facebook:     http://www.facebook.com/groups/macvoice      LinkedIn:     https://www.linkedin.com/in/chuckjoiner/      Instagram:     https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes     Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

Episode 254: What if the future of AI in customer experience is built not by giant platforms but by small, reusable, open source AI agents? Gurdeep Pall, President of AI Strategy at Qualtrics, believes open, modular AI agents will outmaneuver big tech's locked-down systems. In this conversation from the X4 Summit, Gurdeep argues that “experience agents”—task-specific bots that can plug into any stack—will give companies more control, better performance, and real freedom. Closed AI platforms promise convenience, but they trap businesses in rigid walled gardens. Gurdeep argues that modular architectures unlock something better: flexibility, reuse, and evolution. “Break down the agents to very specific functionality,” he says. “And those agents can be invoked by many different agents for different types of tasks.” This isn't just a tech choice. It's a business and philosophical stance. Qualtrics is partnering with LangChain and releasing open connectors to build an ecosystem of interoperable agents. The goal? Let companies mix, match, and scale customer-facing systems without depending on any one vendor. “This is one semantic level up,” he says, comparing today's agentic architectures to the launch of the web and mobile eras. “What agents are going to do for user experience—taking our digital game to the next level—is very exciting.” Guest: Gurdeep Pall, President of AI Strategy, Qualtrics Host: Rob Markey, Partner, Bain & Company Give Us Feedback: https://bit.ly/CCPodcastFeedback Time-Stamped Topics: (00:01) Why Qualtrics is going all-in on open agentic AI (00:04) An overview of the Qualtrics and LangChain partnership (00:06) The modular architecture of “experience agents” (00:08) Why one task might require seven agents (00:09) How specialization allows reuse and scale (00:10) Rejecting the walled garden model (00:11) Making open systems friction-free (00:12) A real-time use case from the X4 stage (00:14) Plug and play simplicity for complex integrations (00:15) Why this is a new digital paradigm Time-Stamped Quotes: [7:00]  “It's about how you break up the task. Like, when you call the human, the human didn't sit there and not do anything and the password got reset. The human went to a piece of software and they went and worked on it. So, what we are talking about here is the combination of software and the human, now organized most efficiently.” [8:00] “ If you're able to break down the agents to very specific functionality, then those agents can be invoked by many different agents for different types of tasks.”  [10:00] “ There is one example of a very small, open system called the Internet, which somehow, through open standards, became one of the most incredible innovations of human beings ever. So what we are trying to do is to take a stand and say, 'We believe in open systems and we want to let our customers know that this is a choice.'”

As AI becomes deeply embedded in every industry, building AI systems that are secure, responsible, and privacy-centric is more crucial than ever. But where do you begin? At the strategy level? Design? Or implementation? How do organizations tackle the challenges of AI risks, data governance, and compliance while keeping pace with innovation?Join us for an insightful conversation with Punit Bhatia and Santosh Kaveti, CEO of Pro Arch, as we explore the evolving landscape of responsible AI, key foundational steps, and the practical approaches to secure AI deployment.If you're looking to understand how to build AI systems that are not only innovative but also secure and trustworthy, this episode is for you!KEY CONVERSION 00:01:58 Responsible AI 00:04:30 AI Strategy 00:11:43 Role of standards and Approach 00:15:35 Good practices of Data Governance 00:19:55 AI Talent 00:23:10 Pro Arch Role in costumers 00:25:00 Contact Information of Santosh  ABOUT GUEST Santosh Kaveti is CEO & Founder at Proarch. With over 18 years of experience as a technologist, entrepreneur, investor, and advisor, Santosh Kaveti is the CEO and Founder of ProArch, a purpose-driven enterprise that accelerates value and increases resilience for its clients with consulting and technology services, enabled by cloud, guided by data, fueled by apps, and secured by design. Santosh's vision and leadership have propelled ProArch to become a dominant force in key industry verticals, such as Energy, Healthcare & Lifesciences, and Manufacturing, where he leverages his expertise in manufacturing process improvement, mentoring, and consulting. Operationalizing AI: From Strategy to Execution Navigating AI Risks: Ensuring Security and Compliance Prioritizing AI Initiatives: Aligning with Business Goals Attracting and Retaining Top AI Talent Integrating AI into Core Business Functions The Data Foundation: Governance, Quality, and Culture in AI  Santosh's journey is marked by resilience, ambition, and self-awareness, as he has learned from his successes and failures, and continuously evolved his skills and perspective. He has traveled across 23 countries, gaining insights into the global diversity and interconnectedness of human experiences. He is passionate about blending technology with a human-centric approach and making a meaningful societal impact through his support for initiatives that uplift underprivileged children, assist disadvantaged families, and promote social awareness.Santosh's ethos extends to his investments in and mentorship of promising startups, as well as his role as the Chairman of the Board at Enhops and iV4, two ProArch companies.  ABOUT HOST Punit Bhatia is one of the leading privacy experts who works independently and has worked with professionals in over 30 countries. Punit works with business and privacy leaders to create an organization culture with high privacy awareness and compliance as a business priority. Selectively, Punit is open to mentor and coach professionals.  Punit is the author of books “Be Ready for GDPR' which was rated as the best GDPR Book, “AI & Privacy – How to Find Balance”, “Intro To GDPR”, and “Be an Effective DPO”. Punit is a global speaker who has spoken at over 30 global events. Punit is the creator and host of the FIT4PRIVACY Podcast. This podcast has been featured amongst top GDPR and privacy podcasts.  As a person, Punit is an avid thinker and believes in thinking, believing, and acting in line with one's value to have joy in life. He has developed the philosophy named ‘ABC for joy of life' which passionately shares. Punit is based out of Belgium, the heart of Europe.  RESOURCES Websites www.fit4privacy.com,www.punitbhatia.com, https://www.linkedin.com/in/santoshkaveti/ , https://www.proarch.com/  Podcast https://www.fit4privacy.com/podcast Blog https://www.fit4privacy.com/blog YouTube http://youtube.com/fit4privacy   

As brands grow more digital, the threats grow more personal. Attackers impersonate executives, spin up fake websites, and leak sensitive data — hurting business reputations and breaking customer trust. How do you defend your organization's reputation and customers' trust? Santosh Nair, Co-Founder and CTO at Styx Intelligence, joins Business Security Weekly to discuss how to defend trust and reputation in the age of AI. Santosh will cover both the company and executive challenges of defending against the latest AI attacks, including: Impersonations and Deepfakes Employee Scams Financial Fraud Segment Resources: - https://styxintel.com/blog/what-is-brand-protection/ - https://styxintel.com/blog/brand-impersonation-hurts-business/ - https://styxintel.com/blog/social-engineering-tactics/ In the leadership and communications section, Mind the overconfidence gap: CISOs and staff don't see eye to eye on security posture, Your AI Strategy Needs More Than a Single Leader, Avoid These Communication Breakdowns When Launching Strategic Initiatives, and more! Visit https://www.securityweekly.com/bsw for all the latest episodes! Show Notes: https://securityweekly.com/bsw-408

In this episode, Laura Dyrda, Vice President and Editor-in-Chief at Becker's Healthcare, shares insights on the financial trends shaping hospitals, the growing role of AI in health systems, and strategies for advancing value-based care amid ongoing industry challenges.

The Transformation Ground Control podcast covers a number of topics important to digital and business transformation. This episode covers the following topics and interviews:   SAP's $1.5 Billion Bet on AI, Q&A (Darian Chwialkowski, Third Stage Consulting) Inside a Real World SAP Implementation (Justin Rauner, CTO at Kiewit) Shocking Whistleblower Claims about S/4HANA   We also cover a number of other relevant topics related to digital and business transformation throughout the show.