Podcasts about technology officer

Healthcare doesn’t lack data. The challenge is connecting it. In this episode of Technovation, Mouli Venkatesan, EVP and Chief Information & Technology Officer of the Blue Cross Blue Shield Association, joins Peter High to discuss how interoperability, AI, and shared technology foundations can help create a more connected healthcare system. Mouli explores how the Blue system balances national scale with local delivery, why longitudinal data matters to value-based care, and how BCBSA approaches AI through mindset, “heart set,” tool set, and skill set. He also explains why responsible AI begins with strong data governance and human involvement in clinical decisions. The conversation also covers AI workforce development, build-buy-partner decisions, process improvement, and leadership through influence across independent organizations. This episode is presented by ElevenLabs — Bringing technology to life. Learn more at elevenlabs.io This episode is also presented by Retool — Build internal software better, with AI. Learn more at retool.com

On a Friday, one of Miro's architects set his agents loose on the company's AI engine. Nobody asked him to. By Monday, he demoed a full refactor. Tuesday, it had a kickoff, and a few months later it was the headline of their user conference. Here's the twist. Miro has refused to rebuild its process around AI. They've kept the same three milestones they've always had...they just changed what happens around them. Our guest today is Jeff Chow, Miro's Chief Product & Technology Officer. He helps lead a company whose entire job is helping cross-functional teams work better together, which makes it an unusually good place to watch what AI is actually doing to how teams build. Jeff's take: AI hasn't moved the milestones — It's rewritten everything that happens between them. In this episode, he shares: The false confidence trap of building alongside an agent that tells you every idea is brilliant, and why that makes the moments where humans actually align more important than ever Why product "process barnacles" accrete on companies as they scale, and how that quietly turns a culture of invention to optimization at just the wrong time And why saying no is the next organizational crisis. Now that anyone can build almost anything, it's become clear that coding was never the hard part Links Jeff's LinkedIn: https://www.linkedin.com/in/jjchow/ Miro: https://miro.com/ Chapters 0:00 Introduction 2:20 Why Miro refused to rebuild its process around AI 5:20 What shows up at kickoffs and solutions reviews now 12:15 The false confidence trap: Say no to "yes-man" agents 14:30 From optimization culture to invention culture 18:20 How one IC's side project reshaped Miro's AI engine 22:30 Process barnacles and why saying no is the next crisis 27:30 Conclusion Follow LaunchPod on YouTube We have a new YouTube page! Watch full episodes of our interviews with PM leaders and subscribe! What does LogRocket do? LogRocket's Galileo AI watches user sessions for you and surfaces the technical and usability issues holding back your web and mobile apps. Understand where your users are struggling by trying it for free at LogRocket.com.Special Guest: Jeff Chow.

As AI inference costs have dropped by over 90%, enterprises are embedding data and intelligence at the core of their operating and business models, enabling always-on, global execution beyond human limits. How are these AI-first enterprises reorganizing around AI in practice, and under what conditions does this actually translate into long-term value for society? This is the full audio from a session at the Annual Meeting of the New Champions 2026 in Dalian, China on 23-25 June, 2026. Watch it here: https://www.weforum.org/meetings/annual-meeting-of-the-new-champions-2026/sessions/whats-the-intelligence-limit-for-ai-first-enterprises/ Speakers: Yuxiang Zhou, Chief Executive Officer, Black Lake Technologies, Michael Römer, Senior Partner and Global Co-Lead, Activate: Digital and Analytics, Kearney Joey Wat, Chief Executive Officer, Yum China Holdings, Inc. Sudip Roy, Co-Founder and Chief Technology Officer, Adaption Yang Yanqing, Director of Center for Education, Innovation and Sustainable Development, ShanghaiTech University Mehdi Ghissassi, Chief Product and Technology Officer, AI 71 Catch up on all the action from the World Economic Forum's Annual Meeting of the New Champions 2026 at wef.ch/amnc26 and across social media using the hashtag #AMNC26. Check out all our podcasts on wef.ch/podcasts:  YouTube: - https://www.youtube.com/@wef/podcasts Radio Davos - subscribe: https://pod.link/1504682164 Meet the Leader - subscribe: https://pod.link/1534915560 Agenda Dialogues - subscribe: https://pod.link/1574956552

What happens when AI gives healthcare workers more time to do the work only humans can do? Nathan Frank, Chief Digital and Technology Officer of Aetna, joins Peter High to discuss how Aetna is scaling AI across healthcare while keeping people at the center. Frank shares how AI-enabled workflows are giving care-management nurses 90 minutes back per day, reducing the administrative burden of navigating clinical notes and multiple systems. He also explains how Aetna is building on years of investment in enterprise data and clinical data infrastructure, applying responsible AI governance, and bringing employees directly into the product-development process. The conversation explores what it takes to move AI from experimentation to meaningful improvements for members, providers, and colleagues, and why Frank believes AI and humans together can create a better healthcare experience. This episode is presented by ElevenLabs — Bringing technology to life. Learn more at elevenlabs.io This episode is also presented by Retool — Build internal software better, with AI. Learn more at retool.com

What if the future of IT isn't about responding faster—but about knowing what's going to happen before it happens? David Raissipour, Chief Product & Technology Officer at ConnectWise joins us for a forward-looking conversation about how AI, agentic automation, and predictive intelligence are reshaping the managed services industry. David shares his perspective on the MSP inflection point, why traditional models of simply adding people, tools, and processes are reaching their limits, and how AI agents can help smaller MSPs compete on a more level playing field with larger organizations.    The conversation explores the evolution from reactive IT to predictive IT, where intelligent systems can identify issues, reason through problems, and execute tasks before they become customer-impacting events. David also emphasizes that this transformation is not an “anti-people” approach—it's a pro-success approach, giving technology professionals the opportunity to move beyond repetitive tasks and contribute at a higher, more strategic level. From the accelerating adoption of AI and dramatically changing response times to the importance of deciding when to buy versus build, David offers practical leadership insights for navigating this next chapter of technology. Plus, we look ahead to ConnectWise's exciting second half of the year and invite MSP and IT leaders to join the ConnectWise AI Agentic Roadshow and Executive Forum Series for conversations around AI, operational scale, and organizational performance. Follow David on LinkedIn and visit connectwise.com/executive-forum-series to participate in a city near you.  Timestamps: Inflection Point 9:20    AI Strategy 18:43 Launched Platform 27:19 Roadshow Series 37:44

Every enterprise leader has heard the numbers by now as billions poured into licences, seats and tokens, with productivity gains still trailing well behind the promise. On a recent episode of Tech Transformed, host Christina Stathopoulos sat down with Jay Richman, Chief Product and Technology Officer at Multiverse, to unpack why so many organisations remain stuck in what he calls "tinker mode" and what it actually takes to move past it.Richman's view is shaped by a career spent at the sharp end of three separate technology shifts. A decade at Spotify saw him build out the company's advertising business and early subscription platform from scratch. Roughly four years at Amazon followed, working on agentic AI systems within the advertising division, effectively rebuilding the old-fashioned creative agency model using specialised generative media tools. Four months ago, he relocated from New York to London to join Multiverse, drawn by a mission he sees as almost the reverse of his previous work. Rather than using people to make machines smarter, the task now is training machines to make people smarter. That framing sits at the centre of this conversation.The AI Adoption GapRichman suggests that the widely reported gap between AI spend and AI-driven output isn't really a technology failure; it's a human one. Tools sit unused, licences go unopened, and organisations struggle to move employees from curious onlookers to confident, habitual users. Multiverse's answer is what it calls the "adoption layer", which is a diagnostic approach that pinpoints where skill gaps actually sit across a workforce, builds tailored learning paths around them, then embeds coaching directly inside the tools people already use, whether that's Claude, Gemini or ChatGPT.Crucially, Richman distinguishes between what he wryly terms "token maxing" and value creation. Blunt incentives, leaderboards, usage dashboards and mandates to switch from manual coding to AI-assisted development. All this can help people over that first hurdle, and he admits to having used some of these tactics himself. But the real measure of success has to be defined customer by customer, tied to a specific business outcome, not simply how many prompts someone fired off in a week. As he puts it, the value of any given AI initiative can only be judged against what that particular organisation set out to solve in the first place.Human Skills AI Can't ReplaceOne of the most interesting parts of the discussion explores how generative and agentic AI are reshaping team structures. Richman describes a flattening of traditional boundaries: product managers writing code, designers contributing to technical documents, and engineers drafting strategy papers. Functions that were once tightly specialised, such as a dedicated user-research team and a standalone copywriting role, are increasingly being absorbed as skills within more generalist, multi-hatted employees. At the same time, he notes, the opposite is happening at the model layer, with AI agents becoming ever more specialised. The result, in his telling, is smaller teams working with far greater autonomy and considerably less coordination overhead than in years past.Asked what he prioritises when hiring now, Richman is candid that mastery of a single discipline matters to him less than certain behavioural traits: curiosity, high agency, sound judgment. He shares an interview technique he relies on, asking candidates how they spent their time during the pandemic lockdowns, as a rough proxy for whether someone tends to seize initiative or simply wait for circumstances to dictate their next move.Moving Fast Without Cutting CornersOn responsible deployment, Richman insists culture has to start at the top. Leaders, he argues, need to be visibly hands-on and honest about their own gaps in knowledge rather than issuing mandates from a distance. At Multiverse, that meant lifting caps on AI coding tools, resetting the expectation that new work should be AI-generated by default, and investing heavily in quality assurance and evaluation frameworks so that human reviewers still hold a meaningful checkpoint before anything reaches customers. He contrasts this with the slower, more cautious approach he sees at many other organisations — one he believes is not only less efficient but also less likely to stick once the initial push fades.Measuring What Actually MattersTying this back to the earlier point about value over volume, Richman suggests the real test of an AI initiative is how closely it maps to a business's own stated objective, not adoption figures in isolation. That means starting with what a customer or team is actually trying to achieve, building learning around the specific gaps standing in the way, and only then judging success by whether the resulting behaviour change shows up in the metrics that organisation already cares about.The conversation closes on a personal note, with Richman sharing the advice he'd give his own children as they weigh careers in a fast-shifting landscape: run towards disruption rather than away from it. Having entered the workforce at the tail end of the dot-com boom, he sees clear parallels with the present moment, a period, in his words, where nobody can credibly claim expertise, which makes it as good a time as any to jump in. For organisations still puzzling over why their AI investment hasn't translated into measurable returns, Richman's message is simple: the technology was never really the difficult part. If you would like to find out more, please visit multiverse.io or connect with Richman on LinkedIn.TakeawaysSuccessful AI adoption hinges on people, not just technology.The AI adoption layer helps bridge the gap between investment and productivity.High agency and curiosity are key traits of successful AI practitioners.Leadership must lead by example and foster a culture of experimentation.Rapid technological change requires teams to be flexible and multi-skilled.Chapters00:00 Introduction to AI transformation and people-centred approach00:54 Jay Richman's background at Spotify, Amazon, and Multiverse03:47 The challenge of AI adoption and pilot mode07:04 The concept of the AI adoption layer and its purpose12:54 Distinguishing token maxing from value maxing16:03 Impact of generative AI on product and engineering teams19:09 Building teams in the AI era: blurring roles and skills21:49 Qualities and skills for future AI teams25:49 Leading responsibly with AI and fostering a culture of experimentation

Executive Summary Insurance companies are moving fast on agentic AI, and Aetna is one of the clearest examples of what that looks like in production. In this episode, Nathan Frank, Chief Digital and Technology Officer at Aetna, the insurance business of CVS Health, explains how AI agents are cutting administrative burden for nurses, why Aetna refuses to use AI for care denials, and what it will take to give every member their own AI health agent within the year. Key Takeaways Aetna's AI agents pull data from multiple platforms, providers, and EHRs to prepare clinical notes automatically, giving the company's 12,000 care management nurses 90 minutes back per day. Aetna does not use AI to deny care. Nathan Frank draws a hard line here: AI supports auto-approvals and administrative work, but clinicians review any case with missing information. 84% of providers in Aetna's annual survey believe AI and agentic AI will lead to better outcomes, a signal the company is using to justify deeper investment in interoperability and clinical data exchange. An early version of an AI scheduling agent is already in production, handling the "homework" of booking appointments. Nathan expects a fully autonomous AI health agent for members within the next year. Model cost management is becoming a core discipline: Aetna is routing workflows to lower-cost models where possible instead of defaulting every task to frontier AI. Links and Resources Connect with Arundhati Parmar aparmar@medcitynews.com Arundhati Parmar (@aparmarbb) on X — https://twitter.com/aparmarbb?lang=en MedCity News — https://medcitynews.com/ Keywords agentic AI healthcare, Aetna AI, Nathan Frank Aetna, CVS Health AI, AI in health insurance, ambient listening healthcare, AI care management, administrative burden AI, health insurance AI trust, AI claims processing, AI appointment scheduling, health plan AI agents, payer AI strategy, CVS Health Ventures, AI model cost management, interoperability healthcare AI, AI care denials, MedCity Pivot podcast, healthcare AI startups, member experience AI Episode Highlights [00:03:00 - 00:04:00] How Aetna's AI agents pull data from multiple EHRs to prepare clinical notes for nurses before patient visits [00:04:00 - 00:04:30] The result: 90 minutes back per day for clinicians, redirected to patient care, not homework [00:06:00 - 00:07:00] Aetna's 10-plus years of AI and machine learning history, and its 3,000 data scientists [00:12:00 - 00:12:30] Nathan Frank's direct statement: Aetna does not use AI to deny care [00:13:00 - 00:13:30] The provider survey finding that 84% believe agentic AI will lead to better outcomes [00:16:00 - 00:17:00] How Aetna sorts signal from noise among healthcare AI startups [00:21:00 - 00:22:00] An early version of the AI scheduling agent is already live, with a fully autonomous member health agent expected within the year

PARTNERED Artificial Intelligence has moved far beyond chatbots. In this episode of Techcetra, in partnership with  @salesforce  Leslie D'monte speaks with Kapil Mahajan, Global Chief Information & Technology Officer at Allcargo Group, explains how AI agents are transforming one of the world's largest logistics industries—from automating freight quotations and invoice processing to managing global supply chains at scale. He argues that tomorrow's logistics companies will actually be technology companies delivering logistics as a service. The conversation explores how enterprises are deploying AI agents, why clean data is the foundation of successful AI adoption, the importance of human oversight, and how organisations can build guardrails to ensure AI remains secure, compliant and reliable. In this episode: Why logistics companies are becoming technology companies AI Agents vs Generative AI Building enterprise AI with clean data Automating global freight operations How Allcargo handles 40,000+ customer quotes every month AI governance, compliance and guardrails The future of autonomous enterprise workflows If you're interested in enterprise AI, digital transformation, logistics, supply chains or the future of automation, this conversation offers practical insights into AI adoption at scale. #AI #AIAgents #Logistics #SupplyChain #ArtificialIntelligence #EnterpriseAI #Automation #DigitalTransformation #Allcargo #Salesforce #Techcetra Learn more about your ad choices. Visit megaphone.fm/adchoices

What does it mean to balance old school values with the rapid advancements of technology? In this episode of Better Call Daddy, host Reena Friedman Watts welcomes tech expert Oshri Cohen, who delves into the importance of maintaining traditional values in a world increasingly dominated by AI and digital innovation. Oshri shares his journey from a young coder to a fractional CTO, discussing how his unconventional beginnings shaped his approach to technology and business. He emphasizes the significance of creativity in an age where AI is often seen as a replacement for human ingenuity. The conversation touches on the challenges of parenting in the digital age, particularly when it comes to navigating platforms like YouTube, and how his new product, Watchly Player, aims to create a safer viewing experience for children. Reena and Oshri explore the evolving role of a CTO, the pitfalls of corporate culture, and the necessity of kindness in leadership. Oshri's insights challenge listeners to rethink their relationship with technology and the impact of family dynamics on personal and professional growth.   Oshri Cohen is an AI-native Chief Product & Technology Officer who helps companies build software the way modern teams actually should. Over 25 years in software — 20 of them in technology leadership — he has made AI-native transformation his focus: rewiring how engineering organizations plan, build, and ship, not just bolting AI features onto old workflows. He leans on cloud-native architecture, DORA metrics, and GitOps to turn slow, siloed teams into fast, measurable product engines. His range is unusually broad. Since 2018 he has served as fractional and interim CTO to more than 30 companies, almost all US-based, and at his peak directed 12 engineering teams across seven countries. He has shipped more than ten digital products across healthtech, e-commerce, manufacturing, logistics, and finance. A McGill business grad who taught himself to code at 13, Oshri leads business-first — every technical decision starts at the P&L, never the other way around.

What prevents a successful AI experiment from becoming a dependable production system that delivers measurable business value? In this episode of Tech Talks Daily, I speak with Ed Macosky, Chief Product and Technology Officer at Boomi, about AI pilot purgatory, integration, governance, model selection, token costs, and the technical skills businesses may need as adoption grows. Ed leads Boomi's product and engineering teams while also using AI tools inside his own organization. That gives him a view from both sides: creating technology for enterprise customers and applying it within active product development workflows. He believes many AI pilots begin with the wrong question. Teams become interested in the latest model or feature before defining the business problem they want to solve. The experiment may work during a demonstration, then fail when it encounters real data, access controls, security policies, and production systems. Placing company information inside a data lake and adding a language model does not automatically create a business application. The system must access current data reliably, respect employee permissions, connect with existing applications, and operate within governance rules that security teams can approve. Ed recommends beginning with a defined business opportunity and establishing the access required to support it. Existing APIs can already provide authentication, permissions, and governance. MCP can offer another route into enterprise systems, but those connections still require security, monitoring, and management. Team alignment also matters. An AI center may be racing to test models while an integration center concentrates on a different set of priorities. When those groups fail to coordinate, the pilot lacks the connectivity and automation required to become part of a production workflow. The discussion then turns toward fragmentation. Every technology wave produces new vendors, frameworks, and specialist tools. Early experimentation benefits from variety, but mature companies can eventually find themselves maintaining a complicated collection of products held together with custom code and, occasionally, the digital equivalent of duct tape. Ed does not recommend placing every function with one provider. He does argue for enough consolidation and abstraction to prevent experimentation from creating years of technology debt. Governance and observability should also work horizontally across different environments, including platforms such as SAP, Salesforce, and several AI model providers. That becomes increasingly important as businesses introduce autonomous agents. Leaders need to know which agents exist, what systems they can access, what actions they can take, and how each decision is recorded. AI gateways and agent control towers can provide a wider view across otherwise separate technology environments. Ed also introduces the idea of the frontier engineer. A prompt engineer concentrates on communicating effectively with a model. A frontier engineer understands how the model works, including its logic, mathematics, algorithms, and suitability for different workloads. He does not believe every company needs a large team of these specialists. However, he argues that enterprises need at least one person capable of assessing vendor claims and deciding whether a frontier model, specialist model, or open weight model fits a particular workload. Cost creates another reason to examine model selection. Sending every employee request or agent task to the most capable frontier model can become expensive. Some repeatable workloads may run on open weight models inside the company's cloud or hardware environment, giving finance teams greater cost certainty. Boomi is developing Boomi Prompt to route requests according to their complexity and requirements. A simple factual request might go directly to an API. A forecasting task may use a smaller model. A difficult analytical request could be sent to a frontier model. Ed uses the weather as a helpful example. Retrieving next Tuesday's forecast does not require a language model when a public weather API can return the answer directly. Asking a model to perform every form of automation wastes tokens, computing power, energy, and money. The episode closes with practical advice for CIOs. Avoid starting with a broad objective such as agentifying the entire business. Choose a department, identify a small number of tasks, define the expected return, and work backward. Once the team proves value and understands the operating requirements, it can repeat the process elsewhere. Could intelligent routing, stronger integration, and clearer business outcomes finally move enterprise AI beyond pilot purgatory? Listen to the episode and share your thoughts with me.

The application software industry is facing a mega restructuring with the arrival of AI agents in enterprise workflows. On this episode of the Tech Disruptors podcast, HubSpot Chief Product and Technology Officer Duncan Lennox discusses AI's effect on marketing, sales and service applications. He joins Bloomberg Intelligence analyst Niraj Patel to explore how HubSpot is leveraging AI across its software portfolio for small and medium-sized businesses. Duncan dives into the company's proprietary data stack, the changing landscape for customer relationship management, AI's impact on software buying, managing LLM inference costs, HubSpot's new agent-builder solution and more.

Data innovation isn't about buying better tools. As Dallas and Cleveland show, it's about how leaders listen, support risk-taking, and work alongside agencies. The result? A culture where innovation thrives, and scales. Host Stephen Goldsmith speaks with Brita Andercheck, Chief Data Officer in Dallas, and Liz Crowe, Chief Innovation and Technology Officer in Cleveland, about how they drive transformative change across city governments. From reporting structures to how you listen to agencies to going out into the field yourself, they share the unglamorous work that actually drives transformation. In this episode, you'll learn: How to strike the balance between centralization and decentralization Why a problem-first approach beats technology-first Why data teams should measure their ROI The importance of collaboration and relationships How to create psychological safety so teams "fail smart" Guest: Dr. Brita Andercheck – Chief Data Officer and Director of the Office of Data Analytics and Business Intelligence, city of Dallas Dr. Liz Crowe – Chief Innovation and Technology Officer, city of Cleveland 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.

Discover the biggest announcements from XeroCon London 2026, including Xero Force, Partner Hub, Smart Document Capture, AI-powered automation, and what's next for accountants.   At XeroCon London 2026, Xero unveiled a wave of AI-powered innovations designed to help accountants and bookkeepers work more efficiently while supporting the needs of increasingly complex businesses. In this episode, Heather Smith speaks with Diya Jolly, Chief Product and Technology Officer at Xero, about the company's latest product announcements, the thinking behind its AI strategy, and how these developments will shape the future of the Xero ecosystem. XeroCon London 2026 highlights: Xero celebrates reaching five million subscribers and unveils major product announcements, including Xero Force, Xero Ultra and the new Xero Partner Hub. Smarter practice workflows: Learn how Book Health, Month End Readiness, Auto Bank Reconciliation and Smart Document Capture use AI to reduce manual work and improve bookkeeping accuracy. Building for larger businesses: Discover why Xero Ultra has been introduced and how Xero plans to support businesses as they grow without requiring a move to enterprise software. The future of AI at Xero: Diya explains Xero Force, AI agents, practical automation, and how AI is being embedded across the platform to help accountants deliver greater value. Lessons from the Australian outages: An open discussion about the AWS infrastructure incident, what happened behind the scenes, and how Xero is strengthening platform resilience. Whether you're an accountant, bookkeeper or Xero user, this conversation offers an inside look at the strategy, technology and product direction emerging from XeroCon London 2026. It provides valuable context behind the announcements and practical insights into how AI and automation are set to transform accounting workflows in the years ahead.   Apps & Tools Mentioned: Xero, Xero Partner Hub, Book Health, Month End Readiness, Auto Bank Reconciliation, Smart Document Capture, Hubdoc, Xero Files, Xero Force, Xero Ultra, Xero Payments, AWS, Amazon Web Services, OCR, JAX, AI Studio, Microsoft Copilot, ChatGPT   Episode resources and links: Diya Jolly Linkedin https://www.linkedin.com/in/diyajolly/ Xero https://www.xero.com/   If this episode helped you, the best way to support the show is to leave a review somewhere as it helps more people find us. And if you want to continue the conversation, come find me Heather Smith | Accountant and Storyteller on:   LinkedIn: https://www.linkedin.com/in/HeatherSmithAU/ Accounting Apps newsletter: http://accountingapps.io/ Accounting Apps Mastermind: https://www.facebook.com/groups/XeroMasterMind YouTube Channel: https://www.youtube.com/ANISEConsulting X: https://twitter.com/HeatherSmithAU

Her Peer Kept Misattributing Statements to Her Team. She Let It Slide Once. The Second Time She Confronted Her Directly. She had a verbal offer within four days. They were eager. Before she accepted, she called HR and said: "Before I accept, I want to speak with my manager's manager." That request could have cost her the role entirely. She had already weighed it: if they say no, that tells me everything I need to know about this culture. If they say yes, I make a more informed decision. Within 24 hours, the executive cleared his calendar during a conference lunch and took a 30-minute call. He opened with: "What questions do you have for me?" She asked everything. She took the job. Saadia is Global Chief Information and Technology Officer at Coverys, a medical liability company, with 20 years of IT experience across multiple Fortune 100 companies. In this episode, she walks through the specific moments in her career where courage was required — and exactly how she built it. You'll learn: Her peer kept misattributing statements to her and her team in leadership meetings. She let the first incident slide. The second time, she requested a direct conversation: "This is what I heard. You were named as having stated this. Can you explain why?" The peer was speechless. Saadia set a clear expectation for next time — and never had the problem again. How she built a two-year disagreement relationship with a boss who actually respected being challenged: listen first before responding, don't feel obligated to disagree on the spot, return with facts, and always explain your thought process rather than just your conclusion. The career pivot her mentor pushed her into: leave IT entirely — her entire professional identity — and take a business strategy role with a Chief Marketing Officer. She lost her direct reports and became an individual contributor. Her biggest fear: disrupt her tech trajectory and never get back. Her mentor's answer: "Try it. If you don't like it, come back." She did it for two years, returned to IT as an executive, and credits that pivot for how she now thinks about strategy, stakeholders, and technology implementation. Why she stopped procrastinating in meetings after watching male peers say her exact ideas out loud and get the credit. The mindset that unlocked it: "I am in this room for a reason, and so is everyone else. Equal footing." Think you're the smartest: you stop listening. Think you're the worst: you stop speaking. Find the middle. Her direct advice on bias: keep an eye on how your ideas and voice are treated from day one. You will know quickly whether biases exist. Your manager and your peers are the most critical variables. If your manager has bias toward you, it will not work. Find a leader who respects what you bring, not just who you are. Why she proves herself to herself rather than to others — and why she has watched other women leaders make flawed decisions every time they shifted into "proving to others" mode. The skip-level coffee chat practice she has run for four years: meets individual contributors without their managers, no script, asks what challenges they are facing, never names names when sharing themes upward. The trust it builds has changed how her organization speaks up. About Saadia: Global Chief Information and Technology Officer at Coverys, a medical liability company. Saadia has 20 years of IT leadership experience across multiple Fortune 100 companies and is a recognized voice on courage, leadership, and building speak-up cultures in technology organizations.

In This Episode For years, Banking as a Service (BaaS) was sold as a silver bullet for community banks to solve their deposit problems and grow non-interest income. Through its evolution, the industry has learned that it is not enough for BaaS to simply be programmable. For innovation in banking to flourish, without sacrificing the safety and security of the banking ecosystem, BaaS must also be governable. With the bankruptcy of Synapse and the resulting consent orders, sponsor banks have been forced to prove their control over outsourced operations. This week on Breaking Banks, Jason Mikula, who wrote the book on BaaS, literally!, and is publisher of FinTech Business Weekly; Ellen Linardi, Chief Product and Technology Officer at Synctera; and Reid Whiting, President of Lincoln Savings Bank join Jason Henrichs to talk about sponsor banking. Is it growing up or catching up? Interested in learning more? Check show notes for a link to a paper, a blueprint really, for the choices a bank that wants to play in sponsorship banking will need to make. White Paper Link: Orchestration, Control, and Observability: A New Framework for Sponsor Banking https://alloylabs.docsend.com/view/gs8925x8yeii5vxg

On the 69th episode of Enterprise AI Innovators, hosts Evan Reiser (CEO and co-founder, Abnormal AI) and Saam Motamedi (General Partner, Greylock Partners) are joined by Greg Meyers, Chief Digital and Technology Officer at Bristol Myers Squibb. Bristol Myers Squibb is one of the top ten pharmaceutical companies, with about 30,000 employees and roughly 45 billion dollars in annual revenue, making specialty medicines in oncology, immunology, and neurology. Greg shares how BMS puts commercially scalable AI products in front of doctors, why a science company had to start thinking like a data company, and how a small-team accelerator de-risks ambitious AI bets in a highly regulated industry.Quick Hits from Greg:On thinking like a data company: "to models, negative results matter as much as positive results."On running small experimental teams: "making them too small to fail in a public or embarrassing way was really important."On what really gates AI adoption: "psychology and sociology trump technology every time."Like what you hear? Leave us a review and subscribe to the show on Apple, Spotify, and YouTube.Enterprise AI Innovators is a show where top technology executives share specific ways AI changes how work gets done in the enterprise.Find more great insights from technology leaders and enterprise software experts at https://www.enterprisesoftware.blog/Enterprise AI Innovators is produced by Abnormal Studios.

In today's Tech3 from Moneycontrol, we explain why domestic mutual funds are steadily increasing their stakes in Swiggy and Eternal, and what it could mean for the companies' quick commerce ambitions. We also bring you Xpressbees co-founder Amitava Saha's response to Delhivery's view on the future of India's logistics sector, look at how India has become the world's largest retail GCC hub, and unpack PhonePe's latest leadership reshuffle with Srijon Biswas taking over as CTO and co-founder Rahul Chari moving into an expanded Chief Product and Technology Officer role.

In this closing panel from DX Annual, Rafe Colburn, Chief Product and Technology Officer at Etsy; Jesse Adametz, Senior Director of Engineering, Platform Engineering at Twilio; Eirini Kalliamvakou, Research Advisor at GitHub; Collin Green, Senior Staff UX Researcher at Google; and Brian Houck, Senior Principal Applied Scientist at Microsoft debate some of the biggest questions surrounding AI and engineering productivity.They discuss whether AI will reduce the need for engineers, how AI is affecting technical debt, the future role of software engineers in an agentic world, and whether organizations should mandate AI adoption. They also explore how bottlenecks are shifting across the software development lifecycle, the challenges facing junior engineers, and why learning, culture, and change management may ultimately matter more than the tools themselves.Where to find Rafe Colburn:• LinkedIn: https://www.linkedin.com/in/rafeco• Blog: https://rafe.codesWhere to find Eirini Kalliamvakou: • LinkedIn: https://www.linkedin.com/in/eirini-kalliamvakou-1016865• X: https://x.com/irina_kAlWhere to find Brian Houck: • LinkedIn: https://www.linkedin.com/in/brianhouckWhere to find Jesse Adametz: • LinkedIn: https://www.linkedin.com/in/jesseadametz • X: https://x.com/jesseadametz • Website: https://www.jesseadametz.com Where to find Collin Green: • LinkedIn: https://www.linkedin.com/in/collin-green-97720378In this episode, we cover:(00:00) Intro(01:16) Why an AI-first SDLC doesn't mean fewer engineers (03:09) The debate over AI and technical debt(07:40) AI-generated code and the future role of engineers(14:16) Why mandating AI use doesn't necessarily lead to better outcomes(20:43) Predictions for the future of junior engineers (23:22) Where the bottlenecks are in the SDLC now(28:25) How risk influences AI use (32:38) Why the human side is the biggest AI adoption challengeReferenced:• Etsy• GitHub• Microsoft• Twilio• Google • Stewart Reichling• What is the SPACE framework and when should you use it?

Elizabeth Stone, Chief Product and Technology Officer de Netflix, détaille la stratégie technologique du géant du streaming et sa vision du rôle de l'IA dans la création audiovisuelle.

A CMO Confidential Interview with Drew Pinto, EVP and Chief Revenue and Technology Officer of Marriott International. Drew discusses the concept that architecture and data should be viewed as a means to an end, methods for assessing legacy systems, and why tech is critical to customer experience.Key topics include: - Why he believes in "built to change”- Ways to assess your data- Why marketers shouldn't get "enamored by solutions- The idea of "buying commodities" vs. building everything yourselfTune in to hear a discussion about "data puddles," and why marketers should take their tech partners to dinner.⏱️ Chapters1:12 - Introduction and Guest Welcome2:32 -Defining Data Architecture5:00 - Evaluating Legacy Systems12:51 - Sponsor Message: Typeface ARC Agents13:55 - Built to Change vs. Built to Last17:15 - Tech Sourcing: Build vs. Buy21:11 - Customer Experience and Data Management27:54 - Common Mistakes and Advice for Marketers30:44 - Closing Remarks and Final ThoughtsThis episode is sponsored by Typeface - the agentic AI marketing platform that turns one idea into thousands of on-brand assets. Learn more: typeface.ai/cmo. Subscribe for weekly episodes featuring world-class marketing leaders, board members, and C-Suite executives.#CMOConfidential, #MarketingLeadership, #BrandStrategy, #CorporateActivism, #MarketingStrategy, #CMO, #AIinMarketing, #ExecutiveLeadership, #BrandReputation, #ConsumerTrust, #DigitalMarketing, #MarketingInsights, #ThoughtLeadership, #BusinessStrategy, #CustomerCentricSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

With 250,000 customers and $1.2B in revenue, Monday.com's CPTO explains why they threw out their roadmap and rebuilt everything around agentic AI.Topics Include:Daniel Lereya joined Monday.com when it had just 30 people and five engineers.He grew the R&D org from five engineers to roughly 900 over a decade.Three years ago Daniel became Monday.com's first ever CPTO.Monday.com initially approached AI by adding small features across the product.They called this early phase "sprinkling AI dust" — helpful but not transformative.A pivotal board meeting made Daniel realise AI hadn't changed Monday's core value.Monday.com decided to rethink its mission from first principles around AI.The new mission: AI agents that actually execute work, not just manage it.AI gives businesses an "infinite workforce" regardless of company size.Agents can now do hyper-personalised work at a scale humans simply cannot.Monday's platform puts agents at the centre, replacing boards and dashboards.Shared context and human-in-the-loop handoffs make their agents uniquely powerful.Monday ran an "AI month" — pausing the entire 900-person builder org to transform.The month rebuilt team mindset and energy, reminding staff of early startup days.Monday also ran an "agentic week" where every department built their own agents.Finance built agents to automatically match incoming payments to customer accounts.Scaling AI adoption internally remains the biggest challenge across businesses today.Monday introduced "effective AI" — balancing capability with cost efficiency.They acquired voice AI startup One AI to add specialised model capabilities.On pricing, Monday shifted to a hybrid seats-plus-AI-credits consumption model.Participants:Daniel Lereya – Chief Product and Technology Officer, Monday.comKamil Davidov – Sales Leader Israel ISV-BizApps, Amazon Web ServicesJohan Broman – EMEA ISV Head of Solutions Architecture, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

VivaTech 2026 confirme sa montée en puissance face au CES • L'IA entre dans une phase industrielle • Les pépites françaises de la deeptech et du quantique se font plus visibles • Microsoft accélère les startups IA avec son programme GenAI Studio • Arlequin AI traque désinformation et signaux faibles à grande échelle • Netflix défend une IA au service des créateurs • Une startup française crée des parfums personnalisés grâce à l'IA⭐️ Découvrez Frogans, l'innovation française qui réinvente le Web

In this Karma School of Business crossover episode, Sean Mooney is joined by Lloyd Metz, Managing Partner of ICV Partners; Doug McCormick, Managing Partner of Oridian Capital Partners; James Aylward, Chief Product and Technology Officer at BluWave; and Nathan Plummer, Co-Executive Director of Venture Café Global Institute. The group explains how AI moved from long-running concept to practical business tool, and what that means for private equity firms and portfolio company leaders right now. They cover agentic AI, data readiness, applied AI use cases, internal tooling, security concerns, and the leadership challenge of getting teams to adopt new ways of working. This is a practical conversation for business builders who want to move past AI hype and start creating real value—hit play. Episode Highlights 2:13 - James Aylward's path from Fidelity's AI incubator to BluWave's technology strategy 5:08 - Nathan Plummer on Venture Café's role in connecting startups, investors, and innovators 9:17 - Why ChatGPT marked a "Gutenberg moment" after decades of slower AI progress 13:10 - AI shifts from autocomplete and thought partnership to writing major chunks of code 18:06 - Applied AI moves beyond efficiency into biotech, robotics, imaging, and new product creation 23:28 - Why proprietary data may become the real moat for private equity-backed companies 35:42 - AI literacy, adoption, and the leadership work required to make tools stick 44:05 - BluWave's internal AI tool shows how company data can power faster decisions For information on Oridian Capital Partners, go to https://oridiancapital.com/ For information on ICV Partners, go to https://www.icvpartners.com For information on BluWave, go to https://www.bluwave.net

Most digital transformation stories begin with customer-facing technology. Chipotle’s began by redesigning operations. In this episode of Technovation, Peter High speaks with Curt Garner, President, Chief Strategy & Technology Officer at Chipotle Mexican Grill. Curt shares how Chipotle evolved from accepting fax orders in 2015 to operating a $5 billion digital commerce engine today. He explains why solving operational challenges before customer adoption proved critical to scaling digital growth and how cloud architecture, dedicated digital kitchens, rewards, personalization, and AI-enabled supply chain capabilities continue to drive innovation across the business. Key topics discussed include: Building a digital commerce platform capable of operating at web scale Scaling from 20% to 85% digital ordering during COVID Designing dedicated digital kitchens to eliminate fulfillment friction Using rewards and personalization to deepen customer engagement Applying AI to forecasting, inventory management, and supply chain operations Balancing technology innovation with human hospitality This episode is presented by Celonis — Give AI the context it needs. Learn more at celonis.com/technovation

Podcast: teissPodcast - Cracking Cyber Security (LS 31 · TOP 5% what is this?)Episode: teissTalk: Navigating cloud transformation and IT/OT convergence in CNIPub date: 2026-06-11Get Podcast Transcript →powered by Listen411 - fast audio-to-text and summarizationBalancing compliance, resilience, data sovereignty and uptime across IT and OT environments - whether a cloud-first strategy is viable in CNIHow the need to harness operations data for optimisation, innovation, risk management, and organisational resilience challenges legacy security modelsAdapting proven resilience models from IT cloud transformation to OT security in CNI and the importance of public-private partnerships in its success - Thom Langford, Host, #teissTalk- Amal Kotecha, Head of Technology, INEOS- Sarah Clarke, Head of Information, Strategic Command- Alex Holben, Strategy & Technology Officer, FortinetThe podcast and artwork embedded on this page are from TEISS, which is the property of its owner and not affiliated with or endorsed by Listen Notes, Inc.

What does it take to turn a struggling edtech platform into a mission-driven product powerhouse — in under a year? Vidya Dinamani and Heather Samarin sit down with Jared Harless, Chief Product and Technology Officer at BookNook, as he talks about his early days bootstrapping digital products inside a billion-dollar publishing company, to leading a turnaround that grew revenue 25% year over year and pulled customer retention from 27% to 70%...but the work is far from over. Jared gets real about the kind of conviction it takes to build before you have permission — and how going straight to the market before writing a line of code is still the most powerful move a product leader can make.

Balancing compliance, resilience, data sovereignty and uptime across IT and OT environments - whether a cloud-first strategy is viable in CNIHow the need to harness operations data for optimisation, innovation, risk management, and organisational resilience challenges legacy security modelsAdapting proven resilience models from IT cloud transformation to OT security in CNI and the importance of public-private partnerships in its success - Thom Langford, Host, #teissTalk- Amal Kotecha, Head of Technology, INEOS- Sarah Clarke, Head of Information, Strategic Command- Alex Holben, Strategy & Technology Officer, Fortinet

Forget everything you know about portable PC gaming! I sit down with Whitson Gordon, ASUS's head of content for ROG and senior manager of marketing content, to learn about the just-unveiled ASUS ROG Xbox Ally X20 bundle, which includes glasses that simulate a massive 171-inch display! I'm one of the first to test-drive the technology in TaipeiLove Tubi Of course you do. We unpack the origin story of this mega-popular video platform, why it's as popular as it is and what's coming next. I interview Mike Bidgoli, Chief Product & Technology Officer at TubiI'll also play an interview recorded at AWS re:Invent about ‘Sign Speak.' which provides AI-powered American Sign Language (ASL) tools to enhance communication between Deaf/Hard of Hearing and hearing individuals — built by the community, for the community. I chat with CEO Yami PayanoThank you to Visa, Norton, and SanDisk for your incredible support. Get a huge discount on Norton anti-malware at norton.com/techitout

In this episode of Manufacturing Unscripted, host Peter Parsons sits down with Anoop Mohan, Chief Product and Technology Officer at Augury, to talk about how AI is reshaping the factory floor. Anoop shares how Augury became a leader in machine health, what's fundamentally changed in AI over the last few years, and why the next wave isn't just about predicting machine failures, but giving every persona in a plant a smarter way to work. A great listen for anyone trying to figure out where AI actually fits in manufacturing. Sponsored by Promess Inc., the leading provider of fully electric servo presses for manufacturing.   Watch on Youtube: https://youtu.be/UTXeghqPO5o @Anoop Mohan  @Augury  @peter parsons    @promess   

About a quarter of global greenhouse gas emissions come from the food system, but the public conversation about food and climate keeps getting stuck at the two ends of the chain — what farmers grow on one side, what consumers buy on the other. The middle of that chain — processing, packaging, distribution, storage — is where most of the practical climate levers actually live, and it is the part you almost never see. Brendan Niemira, Chief Science and Technology Officer at the Institute of Food Technologists (IFT), wants us to look there. Brendan spent more than 25 years at the USDA Agricultural Research Service leading a team of 30-plus scientists developing non-thermal treatments — cold plasma, high-intensity light, irradiation — that kill foodborne pathogens on produce, meat, poultry, and shellfish without cooking the food. He stepped into the IFT role on December 1, 2025, and joins Sustainability In Your Ear to walk through IFT's new white paper, Food Science & Technology Solutions for Mitigating and Adapting to Climate Change, which lays out a roadmap covering circular bioeconomy practices, AI-enabled supply chain resilience, reusing food waste, precision fermentation, and cellular agriculture.Brendan describes food safety as a three-legged stool — exclusion, containment, and eradication — and notes that in a warming world the first leg is getting harder. Pathogens travel further, persist longer, and show up in places they didn't used to, with warming oceans already expanding Vibrio bacteria in shellfish that previously didn't carry them. That reframes food safety as climate adaptation work — and it lands at the moment when federal research capacity is being thinned out. The conversation then opens into the ultra-processed food debate, where IFT is pressing the case that nutritional quality, not processing intensity, should define dietary guidance, because pasteurized milk, shelf-stable beans, and a deep-fried snack cake are all "processed," and collapsing them into a single category hobbles the very technologies that extend shelf life and cut food waste. Brendan closes on the structural shift coming next: humans domesticated about 50 animal species over 25,000 years of agriculture, but precision fermentation — built on whole genome sequencing and metabolomics — opens up trillions of possible microbial community combinations, each able to turn side streams and waste streams into dairy proteins, vitamins, flocculants for water treatment, and food ingredients. Garbage in, gumdrops out, as he puts it. We're not there yet, but the trajectory is clear.To learn more about IFT's work and download the climate white paper, visit ift.org.Subscribe to Sustainability In Your Ear on iTunesFollow Sustainability In Your Ear on Spreaker, iHeartRadio, or YouTube

Dan DeMeyere, Chief Product & Technology Officer at ThredUp, has spent more than a decade helping scale one of the world's largest online resale marketplaces, growing from one of the company's earliest engineers into the leader of product and technology strategy today. Dan operates at the intersection of AI, ecommerce, and marketplace logistics, with a focus on how emerging technologies are reshaping the customer experience. We asked him to unpack one of the biggest shifts happening in commerce right now: the collapse of the traditional ecommerce funnel. Dan explains why the future of shopping may no longer revolve around static websites and linear customer journeys, but instead around AI agents acting on behalf of every consumer. He shares how dynamically generated experiences and agentic commerce are changing the way brands think about personalization, merchandising, and conversion. The conversation explores why companies need to rethink what's possible with AI, empower engineers to experiment with the latest tools, and evolve from designing interfaces to designing intelligent systems. Why are so many organizations still underestimating this shift, and what will feel obvious five years from now that companies still miss today? Whether you're leading transformation inside a large enterprise or building the next generation of AI-native commerce experiences, this episode offers a forward-looking perspective on how AI will redefine the future of shopping.

Introduction What if the real bottleneck in commercial insurance isn't distribution or pricing—it's the workflow itself? Nearly $100 billion of SME P&C insurance is placed every year using manual processes, disconnected systems, and data that lives in spreadsheets and email threads. Hamesh Chawla has spent the last four years building the infrastructure to change that. Before founding Mulberri in 2021, Chawla led product and technology at Edelman Financial Engines and Asurion. He came to insurance not as a lifer but as a technologist who saw an industry still running on 20th-century tooling. Mulberri is his answer: an AI operations platform connecting PEOs, brokers, SMEs, and carriers—from smart submission and risk scoring to quote-and-bind and certificate of insurance. In this conversation, Josh Hollander and Chawla dig into why the MGA market was the right pivot, what AI governance looks like when binding decisions carry real capital risk, and why the SME segment is the most underserved frontier in commercial insurance. Guest Bio Hamesh Chawla is the Co-Founder and CEO of Mulberri, an AI operations platform for MGAs, PEOs, brokers, and carriers serving the SME market. Before Mulberri, he was EVP and Chief Product & Technology Officer at Edelman Financial Engines, with prior roles at Asurion and Zephyr (acquired by SmartBear). He holds an MS in Computer Science from Texas A&M University. Mulberri has raised $10.8M from Eos Venture Partners, Altamont Capital Partners, MS&AD Ventures, and Hanover Technology Management. Key Topics • The $100B manual workflow problem — Nearly $100B of SME P&C is placed annually using ACORD forms emailed back and forth, loss runs parsed by hand, and decisions made without the data that exists in the market. Mulberri automates this stack. • From embedded insurance to AI operating system — Chawla explains why he pivoted from embedded distribution to building the workflow layer MGAs actually run on—ingesting unstructured data, structuring it through a GenAI OS, and routing decisions with full context. • AI governance when capital is at stake — When AI is binding real policies, black-box models get rejected. Mulberri surfaces claim propensity, frequency, severity, and loss ratio so underwriters can interrogate and trust the output. • The PEO channel as data and distribution — PEOs sit on firmographic and workforce data directly predictive of workers' comp risk. Embedding into that channel is both a data strategy and a go-to-market strategy. • Building for carriers, brokers, and SMEs simultaneously — Carriers need loss ratio visibility, brokers need submission efficiency, SMEs need straightforward access. Aligning all three is the hardest product problem in the space. Notable Quotes "Our mission since day one has been to leverage technology to complement underwriters' expertise—simplifying and streamlining the business insurance process while ensuring transparency." "The Risk Engine puts the information underwriters need at their fingertips to make fast, accurate decisions—not replacing them, but making them dramatically more effective." Resources Guest: • Mulberri: https://www.mulberri.io • Hamesh Chawla on LinkedIn: https://www.linkedin.com/in/hameshchawla/ Host & Organization: • Joshua R. Hollander on LinkedIn: https://www.linkedin.com/in/joshuarhollander/ • Horton International (USA): https://www.horton-usa.com/ • Insurtech Leadership Podcast (LinkedIn Showcase): https://www.linkedin.com/showcase/insurtech-leadership-show Subscribe & Review If you enjoyed this episode, subscribe on your favorite platform and leave a review. The Insurtech Leadership Podcast is available on YouTube, Apple Podcasts, and Spotify.

This episode is about authentic leadership, self-awareness, and the quiet ways competition undermines collaboration in the workplace. Traci sits down with Archana Mohan, Chief Operations and Technology Officer in the finance sector and author of The Thru Line: How Understanding Who You Are Empowers How You Lead.Archana holds a BA from Brown, an MA from Columbia, and an MBA from Yale, but her most formative credential might be what she's carried from classrooms and boardrooms alike: the experience of not quite feeling like she belonged, and choosing to build something different because of it.What We Cover:Why authentic leadership starts from the inside, not from a titleThe two types of self-awareness and why most leaders only develop one of themListening as the most undervalued skill in the workplaceHow school conditioned us to chase the right answer instead of ask better questionsWhy group impact is exponential, not just additiveWhat collaboration actually looks like versus what leaders often mistake for itThe key difference between competing with someone and competing against themWhy not having the answer is just as valuable as having oneHow creating space for others to be seen fully changes what a team can achieveConnect with Archana Mohan: Archanamo.net | LinkedIn | The Thru Line: How Understanding Who You Are Empowers How You Lead.Connect with Traci here: https://linktr.ee/HRTraciDisclaimer: Thoughts, opinions, and statements made on this podcast are not a reflection of the thoughts, opinions, and statements of the Company by whom Traci Chernoff is actively employed.Please note that this episode may contain paid endorsements and advertisements for products or services. Individuals on the show may have a direct or indirect financial interest in products or services referred to in this episode.

Lloyd Metz (Partner, ICV Partners), Doug McCormick (Managing Partner, Oridian Capital Partners), and Sean Mooney (Founder & CEO, BluWave) are joined by James Aylward (Chief Product & Technology Officer, BluWave) and Nathan Plummer (Co-Executive Director, Venture Café Global Institute) to translate AI from concept into execution. The conversation moves beyond buzzwords to where firms are actually applying AI today—from coding and data strategy to real-time decision-making inside portfolio companies. They also address the practical barriers: data readiness, organizational adoption, and the risk of standing still. This is a clear look at what it takes to put AI to work in private equity—hit play.Episode Highlights1:30 - Why AI is shifting from buzzword to practical tool for operators9:45 - ChatGPT as the inflection point that changed AI adoption overnight13:00 - AI moves from “thinking partner” to executing tasks autonomously18:30 - Applied AI in industries like biotech and robotics reshaping outcomes23:10 - Data becomes the primary competitive moat across portfolio companies30:15 - Why most companies struggle: fragmented, unstructured data systems44:00 - Real-world example: automating hiring workflows with AI toolsFor more information on the podcast, visit bestbutneverfinal.buzzsprout.com and embark on your journey to private equity excellence today.Visit us on LinkedIn at https://www.linkedin.com/company/best-but-never-final-podcast/Visit us on Instagram at https://www.instagram.com/bestbutneverfinal/For information on Oridian Capital Partners, go to https://oridiancapital.com/For information on ICV Partners, go to https://www.icvpartners.comFor information on BluWave, go to https://www.bluwave.net

In the latest episode of Executive Function, Brett is joined by Diya Jolly, Chief Product and Technology Officer at Xero. Before Xero, Diya was CPT at Okta and led YouTube's advertising monetization products at Google. In this conversation, she unpacks her three-bucket framework for delegating decisions, why the most important part of a CPO's role is to drive team-wide ambition, and why the best executives need to spend half their time thinking, not doing. In today's episode, we discuss: Why a CPO's number one job is raising their team's ambition, not shipping features How to demand the best from your team without creating a fear-based culture Why organizational politics is actually an incentives problem How Diya is “militant” with her calendar to carve out dedicated thinking time Why you should avoid chasing titles in your career - and what to chase instead References: Google: https://www.google.com Melio: https://meliopayments.com Okta: https://www.okta.com Sukhinder Singh Cassidy: https://www.linkedin.com/in/sukhinders/ Xero: https://www.xero.com Where to find Diya: LinkedIn: https://www.linkedin.com/in/diyajolly Where to find Brett: LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/ Twitter/X: https://twitter.com/brettberson Where to find First Round Capital: Website: https://firstround.com/ First Round Review: https://review.firstround.com/ Twitter/X: https://twitter.com/firstround YouTube: https://www.youtube.com/@FirstRoundCapital This podcast on all platforms: https://review.firstround.com/podcast Timestamps: 00:12 How an excellent CPO makes an impact on the business 02:01 How the CPO role shifts under founders vs hired CEOs 03:38 Influencing a founder without going deferential 07:37 How adding value to customers is always a net positive 08:45 Why roadmaps need more risk in the AI era 12:30 How to shelter innovation teams from the existing system 15:12 What's different about being a great CPO in 2026 17:34 How AI has changed the concept of an app 18:28 It's essential for CPOs to fly at a low altitude 20:34 How misaligned incentives cause organizational politics 25:13 Being demanding without creating a fear-based culture 28:10 Why raising ambition is a CPO's number one job 31:39 The boss who taught Diya to keep raising the bar 32:43 The hardest part of being a CPO 35:28 The three buckets Diya uses to delegate 36:30 How Diya protects deep-work time on her calendar 42:45 Xero's game-changing early bet on AI insights 44:58 How far into the future should CPOs plan for? 47:14 What it takes to be an excellent C-suite member 48:53 Why ambitious PMs should chase impact, not titles 50:28 The four bottlenecks that stall career growth

In this episode of Innovation and the Digital Enterprise, Patrick and Shelli welcome Jolie Fleming, Chief Product and Technology Officer at IHG Hotels & Resorts, to discuss leading tech teams across a global, franchised hospitality ecosystem spanning 21 brands and nearly 7,000 hotels in 100+ countries. Jolie discusses her career journey, specifically what tools she brought and what challenges she met when moving from financial services to hospitality. She explains IHG's combined tech team, which unifies product and dev to increase speed, predictability, and gives business context increased visibility. They discuss the ever-shifting role of AI in future planning. And Jolie shares three key strategic themes: helping hotels keep “heads in beds”, improving operational efficiency with new property management systems, and deepening guest engagement via a new CRM tied to IHG One Rewards.(00:00) Welcome Jolie Fleming, Chief Product and Technology Officer at IHG Hotels & Resorts(01:10) Jolie's Career Journey from Finance to Hospitality(02:39) Understanding IHG's Global Scale and Franchising(09:39) Jolie's One Team Culture(16:58) Discussing Strategic Themes and AI(23:45) IHG's Loyalty Rewards and CRM Personalization(27:17) How to Future Proofing for ChangeJolie Fleming's career spans more than 25 years of leading transformative growth through product management and technology initiatives across fintech, hospitality, and consulting sectors. Currently, she is the Chief Product & Technology Officer at IHG Hotels & Resorts. Previously she spent nearly nine years at E*TRADE, as Managing Director of Investing, Digital Channels, and Banking and then Head of Digital and Client Experience. She earned her bachelor's degree from Northwestern University.If you'd like to receive new episodes as they're published, please subscribe to Innovation and the Digital Enterprise in Apple Podcasts, Spotify, or wherever you get your podcasts. If you enjoyed this episode, please consider leaving a review in Apple Podcasts. It really helps others find the show.Podcast episode production by Dante32.

Meet Nathan Cook

GoFundMe has facilitated over $40 billion in help since 2010, powering a community of more than 200 million people across 20 countries. Arnie Katz is the Chief Product and Technology Officer there — and a three-time CPTO, having previously led product and engineering at StubHub and TheRealReal. In this episode, he brings the rare perspective of someone who has built and scaled marketplaces at every stage, across multiple industries.What you'll learn:The three failure modes every marketplace must solve — cold start, imbalance failure, and false positive growth — and how to fix each oneHow GoFundMe is using AI agents to reduce friction for fundraisers, resulting in an expected $125 million in additional funds raisedWhy AI is driving revenue growth at GoFundMe, not just developer productivity — and how they sequenced that deliberatelyThe real trade-offs of the CPTO model: what you gain in speed, and what you have to mitigate through hiringHow GoFundMe is building demand-side and matching mechanisms to grow donation volume beyond viral sharingKey takeaways:Marketplace liquidity isn't just about having enough supply — it's about designing the right matching and demand mechanisms at every stage of scaleAI unlocks revenue opportunities that were previously uneconomical to pursue, especially when the customer is already in a vulnerable, high-friction stateThe CPTO structure enables faster decision-making, but requires consciously strong functional leaders underneath to offset the natural lean toward one sideCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Arnie KatzSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

What does it take to turn a portfolio of legacy retail brands into a scalable technology platform? In this episode of Technovation, Kumar “Kartik” Kartikeya, SVP and Chief Digital and Technology Officer at Catalyst Brands, shares how he is building a shared operating model across data, AI, and customer experience to unlock enterprise value at scale. Leading technology for a $9B multi-brand retail ecosystem, Kartikeya explains how selective centralization enables faster innovation while preserving brand identity. Key insights include: How shared data and AI capabilities drive cross-brand scale Why “one plus one must equal three” in platform strategy The role of Consumer 360 in personalization and growth How AI is improving both employee productivity and customer experience Why CSAT is the most important KPI

Most people know Pandora for its iconic charms, but far fewer realize the company is the largest jewelry brand in the world by volume — producing more than 100 million pieces a year.In this episode of Retail Remix, host Nicole Silberstein speaks with David Walmsley, Chief Digital and Technology Officer at Pandora, about how the brand is modernizing its business without losing sight of what it really sells: memory, connection and emotion. David shares how Pandora's Program Phoenix transformation has helped turn around the business, why the company is investing heavily in digital and omnichannel infrastructure, and where AI is starting to unlock value across service, selling, forecasting and product design.Key TakeawaysWhy the company focused first on building stronger digital channels and stabilizing store tech before chasing bigger transformation bets; How Pandora is using AI in customer service today, and what the agentic future holds for the company;Why jewelry creates a more emotionally complex AI selling challenge than more functional categories; Where AI may have the biggest long-term impact at Pandora: design, service and operational automation; Why omnichannel success depends on brands — not customers — being the “glue” across digital and physical touchpoints; andHow to avoid the tech pitfall of “platformitis.”Related LinksExplore Pandora's jewelry collections and gifting experienceRelated reading: How Data and Tech Power Jewelry Brand Pandora's Mission to ‘Give a Voice to People's Loves'Get more retail industry insights from Retail TouchPointsSubscribe and catch up on all episodes of Retail Remix

Rigvi breaks down what truly useful AI looks like, grounded in outcomes like spend optimization, revenue protection, and predictive maintenance, not just convenience features or marketing buzz. He also makes the case that AI won't replace FM professionals, it will finally let them do the job they were always meant to do. Welcome to Elevating Brick and Mortar. A podcast about how operations and facilities drive brand performance. On today's episode, we talk with Rigvi Chevala, Chief Product and Technology Officer at ServiceChannel. With over 20 years in B2B SaaS across industries ranging from local marketing to trucking to real estate, Rigvi brings a uniquely cross-industry lens to the challenges and opportunities facing facilities management today. Guest Bio: Rigvi is an experienced management executive with strong leadership skills and over 20 years of experience in software and product development and has led multiple product lines with >$200M in ARR. He manages and and executes product roadmaps and organizational strategy with experience in evolving B2B SaaS products and reusable digital platforms. TIMESTAMPS: 00:52 - About ServiceChannel 04:19 - What surprised Rigvi about facilities 08:47 - Key unsolved challenges in the industry 11:37 - Defining useful AI vs. marketing noise 15:08 - Breaking down AI types (generative, agentic, computer vision) 28:33 - Why 90% of AI initiatives fail 33:54 - Will AI replace FM roles? 39:37 - Advice for leaders evaluating AI tools SPONSOR: ServiceChannel brings you peace of mind through peak facilities performance. Rest easy knowing your locations are: Offering the best possible guest experience Living up to brand standards Operating with minimal downtime ServiceChannel partners with more than 500 leading brands globally to provide visibility across operations, the flexibility to grow and adapt to consumer expectations, and accelerated performance from their asset fleet and service providers. LINKS: Connect with Rigvi on LinkedIn Connect with Sid Shetty on Linkedin Check out the ServiceChannel Website Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Send us Fan MailIn this week's episode of the Digital and Dirt podcast, Ian sits down with Mehmet Bal, Chief Product and Technology Officer at Infinite Studios, a next-generation entertainment platform at the intersection of human creativity and AI. Mehmet discuss how he evolved from aspiring basketball player to tech leader and shares his perspectives on how AI is transforming creativity, storytelling, and the future of advertising.Podcast Breakdown00:00 - 03:35 Introduction, basketball roots & overcoming fear03:36 - 07:05 Journey to engineering, startups & Apple's 5G work07:06 - 10:45 Adobe, generative AI & the start of the creative shift10:46 - 14:20 AI + creativity, tools for artists & founding Infinite Studios14:21 - 18:05 Infinite Studios, scaling content & AI in advertising18:06 - 30:10 Real vs AI media, small brand advantages & automation30:11 - 40:15 AI in film, storytelling & creative possibilities40:16 - 55:52 Evolution of art, workflows & future of creativity with AI

What does it mean to be a true product rebel in the age of AI? Heather Samarin and Vidya Dinamani sit down with Raviv Levi, former Chief Product & Technology Officer at Sift, as they unpack how product leaders can stay focused on what really matters—amid constant noise, data overload, and accelerating change. From building alignment across competing teams to rethinking experimentation in an AI-first world, this conversation explores how faster prototyping, sharper problem focus, and stronger conviction are redefining product leadership.

What if claims processing could be 10x faster without sacrificing accuracy? In this episode of Technovation, Pravina Ladva, Group Chief Digital and Technology Officer at Swiss Re, shares how one of the world's leading reinsurers is using AI to transform claims processing, unlock insights, and redefine how work gets done across the enterprise. Key highlights include: How AI is reducing claims processing time from ~40 days to 4–5 days Why data ingestion is the biggest unlock for AI in insurance The importance of building “AI-ready” data foundations How Swiss Re achieved ~60% enterprise AI adoption Why AI transformation is more about people and process than technology

As conflict in the Persian Gulf threatens global oil supplies and artificial intelligence drives unprecedented demand for electricity, Texas is in a race to unlock the full potential of its diverse and deregulated grid. The path it chooses may arguably shape the U.S. economy and global energy markets.  In this third episode of our series on Texas water, energy, and growth, host Duke Reiter is joined by UT Austin professor, author, and global energy consultant, Dr. Michael E. Webber and president of the Texas Nuclear Alliance, Reed Clay to discuss:  How the U.S.-Israel-Iran war has sent the world reaching for U.S. oil and natural gas and what this means for TexasHow Texas came to lead the nation in renewable energy generation in the years following Winter Storm Uri, despite the rhetoric What makes Texas a leading contender in the U.S. for a nuclear energy renaissanceWhy surging AI-driven energy demand could accelerate the clean energy transition, not slow it down  Relevant Articles and Resources  “US LNG exports break record high as Middle East war disrupts global supply” (Reuters, April 2026)  “A Texas City Faces Water Crisis as Big Oil and Gas Use Most of It” (Truthout, March 2026)  “Is the US headed toward an electricity crisis of its own making?” (Canary Media, January 2026)  “Texas' power grid weathered another winter storm. Is it ready for the future?” (Texas Tribune, January 2026)  “Trump, atoms, AI and the Texas data center gusher” (Politico, January 2026)  “New U.S. nuclear power boom begins with old, still-unresolved problem: What to do with radioactive waste” (CNBC, November 2025)  “Texas renewable energy grid defies Trump's claims on solar and wind” (Power Technology, July 2025)  The Timeline and Events of the February 2021 Texas Electric Grid Blackouts (University of Texas at Austin)  Final Report on February 2021 Freeze Underscores Winterization Recommendations (Federal Energy Regulatory Commission)  Relevant Ten Across Conversations Podcasts  Part One: Can Texas Drought-Proof Its Economic Miracle?  Part Two: Does Texas Have the Water to Support an AI Boom?  Credits Host: Duke ReiterWriter and producer: Taylor GriffithEditor: Kate CarefootResearch and support provided by: Rae Ulrich, Kelly Saunders, Maya Chari, and Sabine Butler  About our guestsReed Clay is president of the Texas Nuclear Alliance. Prior to that, Reed was the Chief Operating Officer of Texas under Governor Greg Abbott and the founder of the government affairs consulting firm Crestline Group. He is also an experienced litigator and founding partner of Clay Scott LLP, with prior experience in the U.S. Department of Justice and Texas Attorney General's Office.  Dr. Michael E. Webber is the Sid Richardson Chair in the LBJ School of Public Affairs and the Cockrell Family Chair #16 in the department of mechanical engineering at the University of Texas at Austin. Prior to that, Michael served as CTO of Energy Impact Partners and Chief Science and Technology Officer at ENGIE, a global energy company. Michael has authored or co-authored more than 600 publications, including the book “Power Trip: the Story of Energy” and “Thirst for Power: Energy, Water, and Human Survival,” both of which, were developed into award-winning documentaries.

Send us Fan MailDaniel Lereya is Chief Product and Technology Officer at monday.com, the AI work platform trusted by 60% of the Fortune 500 and valued at approximately $8 billion. He joined the company when it had 30 people and $4.5M ARR, and has since grown his team from 5 to nearly 900 people as monday.com crossed $1 billion in ARR.In this episode, Daniel draws on nearly a decade of scaling one of the world's most adopted work platforms to share what it actually takes to rebuild product thinking from scratch when AI changes everything you thought you knew.In this conversation, we discuss:Why the instincts that made monday.com successful are the exact ones Daniel says had to be dismantled to build AI-first products.What the critical difference is between building a demo that impresses and an agent that actually works in production, and where most teams get it wrong.Why Daniel believes wrapping AI inside rigid workflows produces better results than giving agents full discretion, and what monday.com learned the hard way.What happened when 2,000 of 3,000 monday.com employees started building their own apps in just two weeks, and what it revealed about the future of who gets to build software.Why Daniel argues that when an AI agent makes a mistake, the real question leaders should be asking has nothing to do with the technology.Why the biggest barrier to AI adoption is not the technology itself, and what Daniel says companies must stop waiting for before they start.Explore:00:00 Why AI Adoption Is Harder Than It Looks00:53 Introduction + AI Commerce Standards: Google, OpenAI & Visa04:30 Daniel Lereya's 9-Year Journey Scaling monday.com to $1B ARR09:00 How AI Forces a Complete Reset in Product Thinking12:25 The "AI Month" Initiative: Pausing R&D to Rebuild from Scratch14:57 Building AI Products When the Output Is Non-Deterministic20:47 What 250,000 Customers Taught Us About AI in the Real World25:38 Responsible AI: Guardrails, Governance, and Data Control31:28 Who Is Responsible When an AI Agent Makes a Mistake?37:04 The Future of Work: Humans, Agents, and What Comes NextResources:Subscribe to the AI & The Future of Work NewsletterConnect with Daniel on LinkedInAI fun fact articleOn How we can take back control from Big Techhttps://peoplereign.io/podcast/

We present a Special Episode of SmarterMarkets™, bringing you exclusive interviews from S&P Global's CERAWeek 2026. SmarterMarkets™ was in Houston last week for CERAWeek to partner with S&P Global. We sat down with participants at the energy industry's most influential annual conference. The theme for this year's conference was Convergence and Competition: Energy, Technology, and Geopolitics – and the implications of the conflict in Iran were on everyone's mind. We've compiled a selection of those interviews into this Special Episode of SmarterMarkets™. If you would like to listen to the full interviews, they are available on the SmarterMarkets™ Presents media portal. They're also available on our second podcast channel, SmarterMarkets™ Presents. Our guests are: Arjun Murti – Partner at Veriten & Publisher of "Super-Spiked" on Substack Susan Sakmar – Visiting Professor at University of Houston Law Center & Board Member of Flex LNG Jeff Currie – Chief Strategy Officer of Energy Pathways, Carlyle Radhika Krishnan – Chief Product and Technology Officer, Quorum Software Michael Greenstone – Director, Energy Policy Institute at the University of Chicago (EPIC) David Keith – Founding Faculty Director, Climate Systems Engineering Initiative, University of Chicago

In this episode, Simon Nazarian, Executive Vice President and Chief Digital and Technology Officer & Nasim Eftekhari, Chief AI and Analytics Officer, City of Hope, discuss building the infrastructure, governance, and culture needed to scale AI responsibly across a complex health system. They explore AI literacy, agent orchestration, and how technology can expand patient access while supporting clinicians and improving care delivery.

Discover how enterprise AI and data strategy are operationalized at scale in one of the most highly regulated industries in the world. Louis DiModugno, Global Chief Data Officer at Verisk, shares how he builds AI-ready data foundations across 40+ petabytes of insurance and risk data, and the best practices behind embedding AI into enterprise products. He discusses unstructured data, deepfakes, and the shift from governance to observability, offering practical insights for data leaders scaling AI responsibly. Key Moments: From Military Leadership to Chief Data Officer: Data Integrity as a Competitive Advantage (03:02): Louis shares how his experience as a U.S. Air Force Colonel has shaped his approach to data governance, data quality, and enterprise AI leadership. He explains why integrity, service, and operational excellence are essential foundations for modern CDOs building trusted, decision-ready data environments. Building AI-Ready Data Foundations at a 40+ Petabyte Scale (17:13): Managing more than 40 petabytes of insurance and risk data, Louis breaks down how Verisk transforms complex, multi-source data into AI-ready infrastructure. From entity resolution and master data management to benchmarking and predictive analytics, he outlines what it takes to prepare enterprise data for AI and advanced analytics at scale. Designing an AI-First Data Strategy for Enterprise Decision Intelligence (20:00): Louis breaks down how Verisk evolved toward an AI-first data strategy across more than 150 insurance and analytics products. Rather than treating AI as an add-on, he explains how embedding AI into core workflows enables smarter underwriting, pricing, regulatory reporting, and risk management. He also discusses the strategic role ThoughtSpot plays in delivering natural language search, embedded analytics, and scalable AI-driven decision making. AI Fraud, Deepfakes, and Risk Management in Financial Services (26:11): As AI-generated images and synthetic claims become more sophisticated, Louis discusses how the insurance industry is combating deepfake fraud and AI-driven manipulation. He shares best practices around AI risk management, vendor partnerships, and regulatory collaboration to protect policyholders and maintain trust. Unstructured Data and AI: Why Governance Still Matters (29:28): Louis explores how expanding beyond structured data is reshaping enterprise AI. He explains why incorporating unstructured data into vector databases, graph models, and knowledge systems can significantly improve model accuracy and decision confidence. At the same time, he emphasizes that stronger governance (or observability as he reframes it) is essential as organizations scale AI across regulated industries. Key Quotes: “The more data that you bring to the equation, the more elements that you have in the algorithm, the higher level of accuracy you should be able to reach with your outcomes.” - Louis DiModugno “I've tried to move away from using the word governance as much as I like to use the word observability, because I really think observability shows more aspects of what it is that we are doing with the data.” - Louis DiModugno “The underlying aspect of what ThoughtSpot's delivering to them is our insights that not only give them their answer, but also give them insights that maybe they weren't looking specifically for. One of the big benefits of ThoughtSpot is that it's trying to anticipate what you're asking for.” - Louis DiModugno “We've partnered with ThoughtSpot, which brings AI embedded within its product. By having our data available through the data sets that we populate through the ThoughtSpot products, we've got the opportunity to utilize Spotter and the natural language processing capabilities to interact with the data, so that you can ‘talk with your data'.” - Louis DiModugno Mentions From Months to Weeks: How Verisk Scaled Embedded Analytics Breaking Down Digital Media Fraud for Claims in the AI Era Randy Bean's 2026 AI & Data Leadership Executive Benchmark Survey Guest Bio  Louis DiModugno brings more than 20 years of career experience in data and analytics to his new role. He has held several leadership positions in insurance and (re)insurance at firms including The Hartford and AXA US, where he served as the company's inaugural Chief Data & Analytics Officer. Most recently, DiModugno pioneered the role of Chief Data and Technology Officer for Hartford Steam Boiler. Before entering the private sector, DiModugno served with distinction as a Colonel in the U.S. Air Force and Air Force Reserves. He has held teaching positions at Rensselaer Polytechnic Institute, and he currently serves on the Chief Data Officer Advisory Council for the George Mason University School of Business. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.