Podcasts about CDO

Catherine and Kyle are deep in event-season chaos this week — the printed Driven by Data magazine has just gone to print, the digital edition is about to launch, and Driven by Data Live is just eight days away. Catherine recaps her (very delayed) trip to Big Data London: reconnecting with the community, a noticeably different vendor landscape stacked with new AI-era players, and "context" as this cycle's buzzword of choice. It sparks a wider conversation with Kyle about why staying visible in the market, through events, LinkedIn or simply contributing to the conversation, matters more than ever in a leadership hiring market where six months out of work is fast becoming the norm.From there, the conversation turns to AI and human oversight, prompted by the now-infamous clip of a Canadian politician reading his AI-generated speech live, chatbot suggestions and all. Catherine and Kyle use it to unpick a bigger pattern: traditional checks and review are quietly disappearing as people lean on LLM output uncritically, whether that's AI-generated pitch decks stripped of intentional choices, or candidates' CVs that increasingly sound like the job description they were lifted from. They also debrief Tuesday's episode with Aimee Smith, UK Government Chief Data Officer, covering her culture-not-technology diagnosis of Whitehall's data-sharing problem, the surprising admission from Microsoft and Amazon that government's scale may be beyond current technology, and just how subjective "success" and value become once you're operating in public service rather than the private sector.They also discuss:Why Catherine's top tip about not moaning about trains backfired within hours of giving it.Why so many familiar faces were missing from Big Data London's vendor stands, and what that says about the market.Why "context" has become this season's buzzword, and why some vendors are stretching to say yes to whatever a prospect asks for.Why stepping out of the market for 18 months, even while genuinely busy doing the day job, can leave you without a way back in when you need one.Why the days of walking straight into a new role within a few weeks of redundancy are over.Why one CDO is advising his mentees to keep six months of financial runway.Why leadership hiring is busier than ever, but so is the competition for every role.What the viral clip of a politician reading his AI-generated speech, chatbot prompts and all, reveals about eroding human oversight.Why neither Catherine nor Kyle blame the politician himself, and where they think the real failure sits.Why AI-generated pitch decks and slides are losing the intentionality that came from every element being a deliberate choice.Why candidates rewriting their CVs to mirror a job description word-for-word is backfiring on them.Why six major banks are flagging the fraud and accountability risks of AI agents transacting on people's behalf.Why B2C brands are already leaning into "handmade" and human-made marketing, and why B2B is likely to follow.Why hiring a copywriter who sounds human could become a genuine differentiator again.Why Aimee Smith's move from 25 years in policing to UK Government Chief Data Officer meant relearning how power and language actually work.Why even Microsoft and Amazon weren't confident the technology exists to handle government's scale and complexity.Why culture and risk appetite, not technology, are the real blockers to data sharing across government.Why "value" and "success" mean something fundamentally different in public service than in the private sector.Why government's federated, siloed structure makes Aimee's mandate harder than the equivalent role in the private sector.A reminder that Aimee Smith will be at Driven by Data Live next week, so bring your questions.

Cecilia Dones guides leaders toward meaningful AI adoption by remaining endlessly curious, prioritizing social connection, valuing deviation, and embracing uncertainty. Kimberly and Celicia discuss connection in a tech-centric world; tech's shiny object syndrome; amplifying the right messages; extreme personalization, social affinity and "brand love"; AI slop; why attention and trust travel alone; internet blindness; influencers and experiential activity; scarcity and value; anonymity as a value play; the 2 data camps; valuing nuance and deviation; purposeful growth and mindful decision making; incentivizing ideas over yessing; agency and the construct of consent. Dr. Cecilia Dones is the Founder and CDO of 3 Standard Deviations, which helps leaders and brands navigate AI under conditions of uncertainty. Building on over 15 years of leadership experience at Fortune 500 organizations and in academia, Cecilia works at the crossroads of AI/technology adoption, consumer experience, leadership psychology and organizational decision-making. Related Resources: The AI Shift: Thriving in a World with Smart Machines and Robots (book) A transcript of this episode is here. 

David Carro es Director de Direct to Consumer en Samsung Iberia. Con más de dos décadas de experiencia impulsando iniciativas de transformación digital en grandes multinacionales, Carro es un especialista en experiencia de cliente, modelos digitales y tecnologías aplicadas a la eficiencia del negocio. Además, es un referente en inteligencia artificial, disciplina en la que acumula una amplia experiencia. Es también miembro fundador del Foro de Inteligencia Artificial.Referencias:* David Carro en LinkedIn* Organizaciones de marketing para gobernar algoritmos (David Carro en Programmatic Spain, 10 de septiembre de 2026)* Foro de Inteligencia Artificial* Bernardo Crespo: estadios y niveles de madurez del CDO en la estrategia de datos (Masters of Privacy, abril de 2020)* Sergio Maldonado, The CMO's case against marketing attribution (2017). This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mastersofprivacy.com/subscribe

In Episode 24 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by Simon Turner, Chief Technology Officer at FOIL AI, where they discuss the "autonomic business" – organisations run by bounded, goal-driven digital entities that work alongside humans – and why, when every company has access to the same models and tools, competitive advantage has to come from somewhere else: your codified business knowledge, your data, and the creativity of your people.The conversation covers why the most common mistake is automating processes that shouldn't exist in their current form, a real-world water utility case where an autonomic entity cut alarm triage from 40 minutes to seconds during the drought, and why ownership of this agenda ultimately lands with a properly empowered CDO.They also discuss:Why generative AI was the catalyst for rethinking the traditional consulting model.Why "we want to do more AI" is the wrong request, and what businesses actually need.Why, if everyone says they're behind, someone has to be in the lead.Why the technology is easy, and landing it as systemic change is the hard part.What an autonomic business is, and why the term comes from biology.How an autonomic entity differs from RPA and traditional automation.Why autonomic entities pursue goals rather than execute fixed processes.How Gartner's digital-twin thinking seeded the idea years before ChatGPT.Why the autonomic business depends on knowledge management, not technology.How LLMs and knowledge graphs unlocked the 80% of business information that is unstructured.Why access to the same tools is a leveller, not a competitive advantage.Why reducing cognitive load matters more than raw speed.Why operating model and culture decide whether AI transformation succeeds.Why automating a broken process at scale creates no value.Why most business processes live in people's heads, and how to make them computable.How a water utility used an autonomic entity to cope with alarms rising from 800 to 3,800 a day.What the four human–AI partnership models look like, from "entity proposes, human decides" to "human retains authority".What needs to be true before entities can act fully autonomously.Why the CDO should own the AI agenda, and why that role can no longer sit inside IT.Why generative AI is becoming the Excel of the 90s.Why ROI rarely comes from a single AI project.Why headcount is a dangerous yardstick for ROI, and what successful organisations do instead.Thanks to our sponsor, Data & AI Literacy Academy.Data & AI Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data & AI literacy first.At Data & AI Literacy Academy, they don't just teach data skills. They empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. They're bridging the gap between business and data teams, so they can all work towards aligned outcomes.From those taking their first steps in data & AI literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that they offer. They embed a deep data culture shift through a transformative change management programme.They take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com.

For the 122nd episode of the CIO podcast hosted by Healthcare IT Today, we are joined by Saad Chaudhry, CEO at Evergreen Healthcare Partners, and former CIO, to talk about the roles of C-suite executives! We kick this episode off by discussing what went into Chaudhry’s decision to move from being an IT leader at a provider organization to now being the CEO at Evergreen. Next, we debate why we think more CIOs don’t become CEOs. Then, Chaudhry shares how what keeps him up at night has changed as he transitioned from a CDIO of a large health system to a CEO of a commercial business. We then use this transition to our advantage. CIOs often say they’re the business leaders who happen to lead tech. Since Chaudhry has gone from the outside perspective to being the subject of that belief, we dig into whether or not he still believes that to be true. Next, we talk about what Chaudhry was hesitant to say when he was a CIO that he’s willing to share more openly now. Then, we take a look at the recent Epic UGM to get Chaudhry’s and Evergreen’s reactions. We also discuss the challenges CIOs face and how they should be managing them. Next, we dig into where Chaudhry thinks CIOs should be investing in managed services and when it makes sense to keep things in-house. Lastly, we wrap this episode up with Chaudhry giving his advice to CIOs today. Here’s a look at the questions and topics (inspired by the suggestions of Sarah Hatchett, CIO at Cleveland Clinic, and Shakeeb Akhter, CDO at Memorial Sloan Kettering) we discuss in this episode: What went into your decision to move from being an IT leader at a provider organization to now being CEO at Evergreen? Why do more CIOs not become CEOs? How has what keeps you up at night changed as you transition from a CDIO of a large health system to a CEO of a commercial business? CIOs often say they’re business leaders who happen to lead tech. Now that you’re actually running a business, do you still believe that? What’s something you were maybe hesitant to say when you were CIO that you’re willing to share more openly now? What’s your and Evergreen’s reaction coming out of the recent Epic UGM? What are the challenges CIOs face, and how should they be managing them? Where do you think CIOs should be investing in managed services, and when does it make sense to keep things in-house? What advice would you give to a CIO today? Now, without further ado, we’re excited to share with you the next episode of the CIO Podcast by Healthcare IT Today. We release a new CIO Podcast every ~2 weeks. You can also subscribe to the Healthcare IT Today podcast on any of the following platforms: NOTE: We’ll be updating the links below as the various podcasting platforms approve the new podcast.  Check back soon to be able to subscribe on your favorite podcast application. Apple Podcasts Google Podcasts Stitcher Podcast Radio TuneIn Spotify iHeartRadio Amazon Music Thanks for listening to the CIO Podcast on Healthcare IT Today and if you enjoy the content we’re sharing, please rate the podcast on your favorite podcasting platform. Along with the popular podcasting platforms above, you can Subscribe to Healthcare IT Today on YouTube.  Plus, all of the audio and video versions will be made available to stream on HealthcareITToday.com. We’d love to hear what you think of the podcast and if there are other healthcare CIO you’d like to see us have on the program. Feel free to share your thoughts and perspectives in the comments of this post with @techguy on Twitter, or privately on our Contact Us page. We appreciate you listening! Listen to the Latest Episodes

Die Kommunisten sind die grösste Partei in Berlin, CDU und SPD verlieren deutlich an Wählern, aber niemand getraut sich in der Kanzlerpartei die Verantwortung zu übernehmen.

Wie ist Stuttgart zur smartesten Stadt Deutschlands geworden? Thomas Bönig, CIO und CDO der Landeshauptstadt Stuttgart, erklärt, warum die Stadt bei der Digitalisierung gezielt Schwerpunkte setzt und welche Rolle KI, digitale Verwaltungsangebote und Ende-zu-Ende-Digitalisierung dabei spielen. „Wir haben viele Dinge konsequenter gemacht“, sagt Bönig mit Blick auf den ersten Platz im Smart City Index.Außerdem geht es um die „Rede zur Lage der Union“ von EU-Kommissionspräsidentin Ursula von der Leyen. Jana Gauke, EU-Expertin des Bitkom, ordnet die wichtigsten digitalpolitischen Ankündigungen ein – vom Kids Act und Jugendschutz in sozialen Medien bis zu Physical AI und Europas digitaler Souveränität. Ihr Fazit: Die richtigen Themen wurden angesprochen, bei vielen konkreten Lösungen bleibt die Rede aber noch vage. Hosted on Acast. See acast.com/privacy for more information.

What does it really take to create an environment where different ways of thinking can thrive?   In this episode of Hub & Spoken, Jason Foster, CEO & Founder of Cynozure, is joined by Peter Laflin, senior data leader and former CDO at Morrisons, to explore neurodiversity in data and AI and what it means for building high performing teams. Peter explains why many strengths associated with neurodivergent thinking are particularly valuable in data and AI. From spotting patterns to thinking in systems, different ways of processing information can bring huge value to the work these teams do.   The conversation also looks at strength based leadership and the importance of understanding how individuals work best. They explore where traditional recruitment processes can create barriers and the practical changes leaders can make to help people thrive.   Ultimately, it is about moving away from a one size fits all approach to leadership and creating teams where different ways of thinking are recognized as a strength.

In this week's Data Debrief, Catherine Dowden-King and Kyle Winterbottom are recording a day early ahead of a busy stretch in London – a custom client event, the Future of Data, AI & BI Summit and Big Data London, with Driven by Data Live on 8th October. The headlines this week belong to Donald Trump, who has dismissed AI safeguards and calls for a "kill switch" as a hoax, which sets up the episode's central question: what happens when the people with the power to sign off on AI – presidents or CEOs – sit well above the technical detail and the risk?Catherine and Kyle draw the parallel between geopolitical "space race" thinking and the boardroom instinct to move first and mop it up later, before turning to the vetting questions every data leader should be asking of vendors and LLM providers: what are their values, why are they in the market, and what's in it for them? They then debrief Tuesday's episode with David Castro-Gavino and Boyan Angelov – merchants of complexity, friction versus maturity models, and a CDO role that is hired without an objective – and Kyle's thought of the week on the environmental cost of AI that nobody in the industry seems to be talking about.They also discuss:Why one of the world's most powerful people calling AI safeguards a hoax is a bigger statement than it sounds.Why the AI race is being driven by the fear of China catching up, and how that agenda filters into business.Why "just do it, we'll mop it up later" is the same decision whether it's made in the White House or the boardroom.Why the spectrum between doomsday and handbrake-on leaves everyone struggling to know who to trust.What questions to ask of any vendor or LLM provider before plugging them into your business.What the Careless People revelations about targeting insecure teenagers tell us about tech companies' incentives.Why tech companies handling health and genetic data aren't regulated like health companies.Why "just because you could doesn't mean you should" is the age-old debate, and why nobody boycotts anyway.How a tight-knit CDO community quietly blacklists vendors with poor ethics.Why the vendor community has to own the fact that every pitch deck now sounds the same.Why executives can be forgiven for not understanding the weeds of "AI-powered" everything.How the event agenda has flipped from getting executives to care about data to reining them in.Why data leaders have to learn to sell, and why selling is really just communication.Why influence at ExCo level comes down to trust, credibility and relationships.Why "merchants of complexity" and self-inflicted complexity resonated so strongly with listeners.Why friction isn't uniform, and why "the whole thing's a mess" is rarely true for every department.Why maturity models are theatre, and diagnosing friction through each role's lens is the practical alternative.Why frameworks can contain thinking, and why data people run to structure when they might need creativity.Why the CDO must be the only senior role in business hired without an objective, and what a 90-day plan is really for.Why nobody in the AI adoption conversation is asking whether we need to be using it at all.What 700ml of water per ChatGPT prompt says about the environmental cost of replacing Google.Why nothing in data is sociologically neutral, and why people only care about data centres once the bulldozers arrive.What the new Driven by Data Productions brand means for the community, the podcast, the events and the magazine.How to get 20% off Enabling Data with the code DRIVEN20.

¿La Transformación Digital empieza instalando software o cambiando la mentalidad directiva?

In Episode 24 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is rejoined by David Castro-Gavino, Executive Director, Head of Data Deployment at AstraZeneca, and joined by his co-author Boyan Angelov, Principal Strategist at Exxeta, where they discuss their new book, Enabling Data, and why the data industry is still stuck in Groundhog Day. The same three arguments – who owns that number, is it right, and why does it take so long – have been repeating for thirty years, and rather than fixing them, the industry keeps renaming the problem.The conversation covers why most complexity in data is self-inflicted, why maturity models are "data theatre" compared to diagnosing friction, and why AI hasn't solved any of this – it has poured fuel on the fire.They also discuss:Why the industry has a short collective memory and keeps rediscovering problems solved twenty years ago.What the three recurring arguments are that every data organisation keeps having.Why renaming the symptom – big data, data mesh, platforms – never fixes the underlying problem.How a simple pizza business becomes a data nightmare the moment it goes digital.Why most complexity in data is self-inflicted, and why that is good news.Why "technology is not the problem, you are" is deliberately provocative.What four questions to ask before going back to the market for a new tool.Why fixing the system, not the tool, is the maxim that matters.Who the "merchants of complexity" are, and why consultants are usually the culprits.Why making things simple is the hardest job in data.What's wrong with using maturity scores as the objective.Why measuring the wrong things promotes the wrong behaviours.How to practically find friction by refusing to accept the first answer.Why friction looks different for an analyst, an engineer and a business leader.Why not every foundational problem needs to be solved, and how to avoid spending forever in the basement.Why data teams that don't understand the business are missing the biggest opportunity.What the cargo cult is, and why copying Spotify's operating model won't make you Spotify.How the enabling model's four pillars – people, governance, technology and enablement – fit together.Why the fragility of senior data leadership is structural rather than personal.Why data doesn't create friction in an organisation, it reveals it – and gets blamed for it.Why a clear mandate matters more than who the CDO reports to.Why the industry needs to stop hiring data leaders on a shopping list of technical skills.How AI has exposed how little progress most companies have actually made on the fundamentals.Thanks to our sponsor, Data & AI Literacy Academy.Data & AI Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data & AI literacy first.At Data & AI Literacy Academy, they don't just teach data skills. They empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. They're bridging the gap between business and data teams, so they can all work towards aligned outcomes.From those taking their first steps in data & AI literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that they offer. They embed a deep data culture shift through a transformative change management programme.They take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com/drivenThanks to our sponsor FOIL AIFOIL are an AI consultancy, and one of the most exciting to watch right now.​Fast-growing, genuinely ambitious, and refreshingly down to earth, with a leadership team who have been doing this for years and are well respected for it.​FOIL push data leaders to claim a voice at the top table, to lead the business rather than trail behind it with a handful of AI productivity tools. They push the point that if every competitor has the same tools, productivity is not an advantage. The real prize with AI is bigger and FOIL have the expertise – both strategic and technical – to push the boundaries of what your organisation can achieve, in a practical way. ​FOIL are a lot bolder and braver that the traditional consultancy. That confidence comes from deep practitioner expertise, and it shows in how they engage with their partnerships.​They are claiming the phrase: the autonomic business. A business that senses what is happening, decides within clear guardrails, adapts as things change, and keeps improving on its own. Intelligence built into how the company runs, and they've just been recognised at the British Data Awards for their work with Welsh Water on exactly this concept.​Learn more at https://foilai.co.uk/

AI's Rapid Rise: Challenges, Concerns, and Future Implications Explored with Helena Hornebrant https://www.linkedin.com/in/helenah%C3%B6rnebrant/ About the Guest(s): Helena Hornbrandt is a distinguished technology and transformational leader with over 20 years of experience at the confluence of business, technology, and people. Her expertise spans across financial services, mobility, and technology environments, leading significant digital, data, and operational transformations across more than 60 markets. She most recently held the positions of CIO and CDO at Trayton Financial Services, a subsidiary of the Trayton Group. Helena's career includes noteworthy tenures at Scania, Volvo, Car Mobility, and Nasdaq, coupled with entrepreneurial endeavors. Her work emphasizes that transformation revolves around people more than technology, with a strong focus on how AI is reshaping organizations and creating value in human leadership. Episode Summary: In this enlightening episode of The Chris Voss Show, Chris Voss converses with Helena Hornbrandt, a seasoned leader in technology and transformation, about navigating the rapid evolution of Artificial Intelligence (AI) and its profound impact on global organizations. Helena opens up about her professional journey and experience, shedding light on how AI can be a double-edged sword in both aiding growth and presenting challenges. They tackle varying perspectives on AI's integration into large corporations and the critical influence of human leadership in this transformation. The discussion dives deep into the current landscape of AI, highlighting the pressing concerns, ethical dilemmas, and potential biases these technologies could perpetuate. Helena emphasizes that a strategic and empathetic leadership approach is paramount to successfully leveraging AI's advantages while mitigating its risks. As AI systems become crucial in decision-making processes, the conversation underlines the need for governance, inclusivity, and accountability to shape a sustainable technological future. Key Takeaways: Strategic Leadership in AI: Effective leaders should focus on empathy and inclusivity as AI continues to reshape business landscapes. Historical Bias in AI Training: AI reflects historical bias due to the predominantly male-driven data it's trained on, highlighting the need for diverse perspectives in AI development. Democratizing AI Knowledge: There's an urgent need for expansive education on AI, encompassing government-led retraining programs to minimize cognitive gaps across generations. Oversight and Regulation: The episode underscores the need for systematic regulation and oversight of AI technologies to prevent potential socioeconomic disruptions. Ethical AI Development: Emphasizing that technological advancement should align with societal values, ensuring AI adoption doesn't compromise ethical standards and public safety. Notable Quotes: "Transformation is ultimately about people, not technology." "We need to take responsibility for what AI is trained on." "It's not okay to run AI labs without governance and transparency." "If you're a good leader, this change won't be a big one for you." "What type of society do we want as AI becomes more predominant?"

In Episode 23 of Season 7 of Data Debrief, Catherine Dowden-King and Kyle Winterbottom unpack Tuesday's conversation with Greg Freeman, CEO and Founder of Data & AI Literacy Academy, and the gap between organisations that have given everyone a Copilot licence and those that are actually using AI to change how the business operates. As Catherine puts it, a Sunday league player and a Premier League player are both "playing football" – but nobody's confusing the two.They also get into the week's headline that AI has a "greater than 10% chance" of wiping out humanity, why a growing anti-AI mood outside the data bubble matters for leaders trying to drive adoption, and why a landscaper turned content creator might be the best human-in-the-loop example going.They also discuss:Why September is the real new year for data leaders, with budget season and event chaos hitting at once.Why the "AI will kill us all" headlines are irresponsible without the evidence to back them up.How to tell the difference between a credible warning and a researcher looking for a headline on the way out the door.Why 70% of Facebook comments on an AI-generated event poster are people refusing to attend, and what that tells leaders about the mood outside the bubble.What a year five "meet the teacher" evening on WhatsApp groups has in common with the AI conversations happening in boardrooms.Why the toilet-door graffiti of the 1970s and today's comment sections are the same human behaviour at a scale our brains can't cope with.How Catherine explains agentic AI at the dinner table with trains and tracks, and why it still doesn't land.Why "AI" is used to mean automation, machine learning, LLMs and agents interchangeably, and why that confusion matters.What "buttonology" means, and why both hosts are stealing the term.Why training and education are two different interventions, and why most organisations only do the first one.What Greg's three personas – the asker, the conversationalist and the process redesigner – reveal about where most employees really are.Why AI maturity scales measure who can drive the machine rather than who's transformed their thinking.Why organisations want competitive advantage but are investing in local productivity, and why the two aren't the same thing.Why picking four or five core use cases beats a Venn diagram of everything you could possibly do.Why leaders must ask "have you actually understood this?" before accepting AI-assisted work.Why people treat LLMs like Google when Google gave you sources and LLMs give you a decision.Why the absence of sponsored results in LLMs makes people less likely to question what they're served.Why the context layer, not the tool, is where the real value in AI sits.What a founder's blanket ban on "Claude content" reveals about the perception problem holding back adoption.Why whether AI sits with the CIO or the CDO comes down to whether it's seen as a tool or a transformation.Why culture has to allow people to rip up a process and fail before any of the redesign talk becomes real.Why cutting graduate intake could leave businesses with a succession crisis in a few years' time.How the Dodgy Gardener quit his day job by pairing ChatGPT garden designs with advice from tradespeople in the comments.Why attention is the digital currency of the future, and why B2C businesses will create roles to work out how to win it.

Shachar MEIR has spent 20 years fixing data teams and understanding why they fail. In this live episode, Shachar joins Juan and Tim to discuss the reason why they fail and what they should be doing in order to succeed. Shachar argues that data leaders default to what they can control (cough cough technology_ and underinvest in people, process, and culture. A new CDO comes in, migrates legacy databases to a cloud data platform, and two years later you have the same problems on a better platform. We get into what's actually missing: building trust in data (which takes time and breaks fast), creating incentives so people actually use what data teams build, and spending real time in the business which is not asking what dashboards they need, but what problems they have. Topics discussed: Technology is not why data teams fail Why data leaders default to technology People, process and CULTURE Data trust Incentives Understanding the business Dashboard bloat Self-service analytics Dashboards aren't dead What CDOs do well and what they miss See omnystudio.com/listener for privacy information.

Neste episódio do Podcast Data Hackers, conversamos sobre um dos grandes desafios das organizações na jornada com Inteligência Artificial: o que acontece quando a IA deixa de ser apenas uma promessa e passa a fazer parte da estratégia?Para explorar esse tema, recebemos os executivos do Grupo Boticário: Marcelo Miola - CISO e CDO; Melissa Signori - Gerente Sr. Soluções e Adoção de Inteligência Artificial; e Carolina Michelutti - Diretora de Atração e Gestão de Talentos no Grupo Boticário.Ao longo da conversa, discutimos a jornada de maturidade em IA do Grupo Boticário, os desafios de levar a tecnologia para dentro da estratégia do negócio, a importância da adoção e como pessoas, tecnologia e organização precisam caminhar juntas para que a IA gere impacto real.Uma conversa sobre aprendizados, desafios e os caminhos para transformar a experimentação em cadeia de valor.Conheça nossos convidados:Marcelo Miola - CISO e CDO no Grupo BoticárioMelissa Signori - Gerente Sr. Soluções e Adoção de IA no Grupo BoticárioCarolina Michelutti - Diretora de Atração e Gestão de Talentos no Grupo BoticárioHosts: Monique Femme e Gabriel Lages, do Data Hackers. Dá o play e ouça agora nas principais plataformas de áudio.

In this week's Data Debrief, the companion show to Driven by Data: The Podcast, Kyle Winterbottom and Catherine Dowden-King unpack the week's main episode with Michael Ross and range far beyond it into the collapse in graduate hiring, the succession planning nobody is doing, and what's really happening at both ends of the data job market.From a record 45% drop in advertised graduate roles, to the experienced leaders who've been out of work for two years, to Michael's case that every average hides an opportunity, Kyle and Catherine make the argument that AI is taking the blame for decisions plenty of businesses already wanted to make, and that the bill for not developing people will land in about five years' time.They also discuss:Why a 45% drop in advertised graduate jobs is the lowest figure ever recorded, and why AI can't be held responsible for all of it.How record university enrolment colliding with a shrinking entry-level market creates a problem unfolding in real time.Why "entry-level" data roles asking for two years of Python or SQL were never really entry-level.What happens to the pipeline when the admin-heavy tasks juniors cut their teeth on get absorbed by agents.Why the real risk isn't AI replacing juniors, but having nobody ready when the current workforce retires.How data roles are shifting towards QA, product management and facing back into the business.Why succession planning has only ever been pointed at the top of the house, and why that has to change.What skills matrices and career pathways expose the moment you ask "and when this bottom layer moves up, then what?"Why some organisations announced AI-driven headcount cuts when the business was simply performing badly.How "we're cutting because of AI" got turned into a PR positive rather than a negative.Why a retailer, a telco and an airline sat at the same table are nowhere near the same stage of the journey.What the senior end of the market actually looks like, and why it gets discussed far less than the graduate end.Why there are more head of, director and VP roles than at any point in fifteen years, even as true CDO roles decline.How being overqualified has become as much of a barrier as being underqualified.Why an entire cohort of data leaders has been tarred with the same brush through no fault of their own.How the failure to prove value from data and analytics now has a direct, downstream human cost.What Michael Ross's epiphany moment says about technical specialists becoming commercial operators.Why de-averaging matters more than any dashboard, and how averages quietly mislead entire teams.How an 80% average occupancy hid the fact that no hotel was anywhere near 80%.Why 100% occupancy might be a pricing failure rather than a success story.What it takes for a CEO to get close enough to the commercial detail of their own business to win.Why putting your head above the parapet takes bravery, and why the cost of not doing it is the situation the industry is now in.Why Dolly Parton's Imagination Library may be the most important thing she ever built.What's left of the Future of Data, AI & BI event, Driven by Data Live on 8 October at Tobacco Dock, and the new roles on the NED Appointment Finder.

Richard Entrup is unusual in quantum circles: he's not a physicist, and he doesn't pretend to be. He spent decades as a CIO, CTO, CDO, and CISO at organizations including Verizon, Christie's, Disney/ABC, Time Warner, and Tiffany & Company before joining KPMG to lead its Emerging Solutions practice. That background — deep operational experience on the client side — shapes everything about how he thinks about quantum. He's not selling a hardware roadmap; he's thinking about what it actually takes to get a large, complex organization to change its cryptographic infrastructure before a threat materializes.The conversation matters now because the signals are accelerating. NIST has finalized its first post-quantum cryptography standards, executive orders in the US are pushing federal agencies toward PQC migration, and the algorithmic efficiency gains that reduce the qubit threshold for breaking RSA-2048 keep coming. Listeners who work in enterprise technology, cybersecurity, or quantum strategy — or who advise organizations that do — will find Entrup's practitioner perspective a useful counterweight to the more hardware-focused conversations that dominate the field.What We Get IntoWhy Q-Day's exact date is the wrong question — and why the more important issue is how long it will take enterprises to even inventory their cryptographic exposure, let alone remediate itThe scale of the cryptographic migration problem, including why a single laptop may contain hundreds of individual cryptographic components and why upstream/downstream API dependencies make this a supply-chain-wide challenge, not just an internal IT projectWhy "harvest now, decrypt later" creates urgency today, regardless of when fault-tolerant quantum computers arrive — and how compliance and regulatory timelines interact with that threat modelWhat crypto agility actually means in practice — moving from a "set it and forget it" cryptographic posture to a dynamic, continuously monitored framework, including the pressure SSL certificate renewal windows are already creatingHow KPMG built its PQC practice, incubated it within the firm, and handed it off to the cybersecurity advisory team as a core service offeringThe "good quantum" side of the ledger — how KPMG's emerging research function is approaching quantum computing as a source of competitive advantage, not just risk, and what sectors are furthest along in exploring itThe AI-quantum convergence, including Entrup's observation that AI is already being used to read and crack code — and what that means for the urgency of cryptographic modernizationWhy the enterprise quantum opportunity still has a long tail, and how the current moment compares to the early infrastructure phase of the internet — when everyone was talking about TCP/IP and DNS, not Uber or NetflixResources & LinksGuest & OrganizationRichard Entrup — Worth Magazine Profile — Career arc from CIO/CISO roles at major global brands to KPMG's Emerging Solutions practiceKPMG Quantum Dawn (2025) — KPMG's enterprise quantum readiness hub, introducing the Q-PREP framework and PQC implementation services, with Entrup as named leadReports & ResearchKPMG — "The Quantum Threat Is No Longer Theoretical" (2026) — The threat brief discussed in this episode, charting the rapid decline in qubits needed to crack RSA-2048 and urging immediate PQC migrationKPMG — "From Theory to Impact: Real-World Results in Quantum Machine Learning" (2026) — KPMG's joint report with IBM and Kipu Quantum on measurable quantum ML results on real hardwareKPMG — "Prepare Now for Quantum Cyber Risk" — Board Leadership Article (2026) — C-suite and board-level guidance on integrating quantum risk into enterprise oversightarXiv — "Quantum-enhanced satellite image classification" (2026) — The underlying research paper behind the KPMG/IBM/Kipu Quantum ML resultsEcosystem & EventsChicago Quantum Exchange — KPMG Joins CQE (October 2024) — Announcement of KPMG's formal CQE membership, referenced in the episode as part of the firm's ecosystem-building strategyKPMG 2026 Quantum Consortium — The inaugural KPMG Quantum Consortium event (March 2026, Orlando) discussed in the episodeIndependent CoverageQuantum Computing Report — KPMG joins Chicago Quantum Exchange (2024) — Independent coverage of KPMG's CQE partnership and enterprise quantum strategyQuantum Zeitgeist — Kipu Quantum satellite imagery coverage (Feb 2026) — Independent analysis of the KPMG/IBM/Kipu hybrid QML resultsKey Quotes & Insights> "It's not if but when. And it could be five years, could be three years, could be ten years. The fact is organizations are not gonna be ready. And that's the scary part." — Richard Entrup on Q-Day> "This is not just the CISO. This is gonna be the software engineering app dev guys. This is gonna be all your partners, upstream and downstream, who have to also be compliant — because if you change your crypto and they don't, that stuff's gonna break." — On why PQC migration is an enterprise-wide, supply-chain-wide problemInsight: Entrup draws a sharp distinction between the "bad quantum" (cryptographic risk requiring urgent defensive action) and the "good quantum" (competitive opportunity with a longer tail) — and argues that most organizations aren't adequately addressing either.Insight: The analogy to the early internet is deliberate: just as the 1990s were consumed with TCP/IP and DNS rather than the applications those protocols would eventually enable, the current quantum moment is still largely an infrastructure conversation — and that's normal, not a sign of failure.> "AI is expediting all of this. If AI is doing one thing, the use case is reading code and cracking it. That's pretty scary." — On the intersection of AI capability and cryptographic vulnerabilityRelated EpisodesEp. 81 — Quantum LDPC Error Correction with Larry Cohen and Paul Webster — Directly relevant: Cohen and Webster discuss how QLDPC error correction reduces the qubit overhead needed for RSA cryptanalysis, the technical underpinning of the threat timeline Entrup describesEp. 38 — Quantum Machine Learning with Jessic...

In this week's Data Debrief, the companion show to Driven by Data: The Podcast — Davin Crowley-Sweet OBE, CDO at National Highways, steps into Kyle Winterbottom's seat and is joined by Catherine Dowden-King to unpack the week's main episode with Nick Zervoudis and range far beyond it into the human side of data leadership.From burnout and its lesser-known cousin "rustout," to the serendipity we've lost to working from home, to why psychological safety matters more than technical mastery, Davin and Catherine make the case that the job of a modern data leader is less about building things and more about building the people and the environment in which those things get built.They also discuss:Why burnout has an opposite — "rustout" — and how to tell which one you're actually facing.How working from home has stripped the chance encounters and serendipity out of professional life.Why so much success comes down to luck, and why being open to it is the real skill.What "the worst they can say is no" taught Catherine about taking a chance.Why so many people tie their identity to a job title, and what happens when the badge disappears.How psychological safety, not technical mastery, is the real job of a data leader.Why tension is healthy and shouldn't be mistaken for conflict.What Davin took from Nick Zervoudis's episode, and the subtle power of the words "value from."Why data is valuable for what you do with it, not for its inherent worth.How to get comfortable working in uncertainty rather than chasing a perfect data-driven story.Why "let's take that offline" is the phrase Davin hates most.How cognitive diversity matters as much as the visible kind.What a neurodiversity tribunal case reveals about being thoughtful, not careful, with language.Why mentorship matters at every stage of a career, not just the junior years.How the move from technical to managerial roles goes wrong when leaders revert to command-and-control.Why curiosity and openness to learning matter more than credentials when hiring junior talent.How Davin's role has evolved into developing 170+ people and lifting people out of poverty through data careers.Why "Jack of all trades, master of none" is only half the phrase.Why a GCSE maths resit needn't define anyone, and the danger of self-limiting beliefs.Why Driven by Data Live keeps drawing people who avoid the rest of the conference circuit.

In Episode 20 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by Nick Zervoudis, Founder at Value from Data & AI, where they discuss why so many data and AI teams struggle to demonstrate measurable business value — and why the real failure almost always happens upstream, long before anyone tries to articulate it.Nick makes the case that "we can't prove our value" is usually a symptom, not the disease: teams solve the wrong problem, skip the value case, or hand off value realisation to no one. Along the way they get into his five-point diagnostic framework, how to build a credible back-of-the-envelope ROI estimate before a line of code is written, how to prioritise a portfolio of opportunities, and where AI productivity savings are real versus imaginary.They also discuss:Why the inability to demonstrate value is usually an upstream failure, not a communication problem.What Nick's five-point framework reveals: wrong problem, wrong solution, poor execution, no measurement, weak communication.Why data teams keep solving the wrong problem by starting from technology instead of the problem itself.How to separate the "problem space" from the "solution space" before reaching for a tool.Why 70–80% of data teams operate as order takers rather than true collaborators.Why being ROI-positive is only the entry ticket, not a reason to do a project.What criteria actually decide prioritisation: return, payback speed, implementation readiness, and strategic relevance.Why nothing a data team builds has inherent value without an owner on the business side to realise it.How to build a credible back-of-the-envelope value case before anything gets built.Why estimating value is far easier to learn than the technical craft most data people already have.How to get stakeholders to correct a rough estimate rather than hand them a blank sheet.Why "how will we measure success?" is the most useful question you can ask when scoping work.What the bystander effect has to do with data teams quietly failing to create value.How framing work around outcomes turns engineers from code-writers into problem-solvers.Why hours saved rarely become money on the balance sheet.What the five-to-six buckets of productivity value are, and why you must never double-count them.Why some AI investment should deliberately have no business case at all.How Monday.com turned a five-week experimentation window into a $100M ARR product.Why blanket self-serve analytics or company-wide AI licences often set you up for failure.What first steps a CDO should take to re-prioritise a roadmap around measurable value.Thanks to our sponsor, Data & AI Literacy Academy.Data & AI Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data & AI literacy first.At Data & AI Literacy Academy, they don't just teach data skills. They empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. They're bridging the gap between business and data teams, so they can all work towards aligned outcomes.From those taking their first steps in data & AI literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that they offer. They embed a deep data culture shift through a transformative change management programme.They take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com/driven

Brannin McBee, co-founder and CDO of CoreWeave (CRWV), talks about the company is "second to none" in the AI space after the stock rallied strong on earnings. He addresses how CoreWeave sets up contracts and utilizes its backlog while juggling energy needs and pushback from some public groups. ======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about

Welcome to another episode of the Data Debrief, the companion show to Driven by Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom unpack Tuesday's episode, share what's been on their minds, and explore the realities of leadership, culture, and capability across the data and AI landscape.This week, Catherine and Kyle reflect on the conversation with Marion Shaw, Senior Director of Data, Analytics and Data Management at Cencora, and her new book on data culture, before digging into why the "data culture" debate keeps circling the same questions, and why the answer almost always comes back to people rather than technology.They cover:The wildfires spreading across South Wales and Europe, and how AI and drones are being deployed in France to spot smoke earlier, distinguish dust from smoke, and cut down the false positives that waste emergency resourceThe bigger climate paradox facing the industry, from record-wet winters followed by hosepipe bans and water mismanagement, to the uncomfortable reality that the data centres powering AI advances are themselves enormous consumers of waterWhy absolutism helps no one, and how the healthiest position on AI, sustainability, and change sits somewhere in the messy middle rather than all-in or all-outHow incentives quietly shape behaviour, illustrated by the fact that three flights across Europe can cost less than a single train from Manchester to London, and why people ultimately do what they're incentivised to doCatherine's latest build for the Orbition community: a NED Opportunity Finder, a live, daily-updating table of listed non-executive director roles showing remuneration, location, and whether the board is public or private, free to access for registered community members, and why she's so keen to see more data leaders move into board positionsWhy Marion's candour hit home, especially the reminder that you simply cannot force people to be interested in or care about data, and why that truth is uncomfortable but essentialHow technology becomes a distraction, the "shiny thing syndrome" that pulls focus away from the outcomes that actually matter, and why that's the real answer to "why now"The endlessly debated question of whether "data culture" even exists, why the industry loves arguing over semantics no one outside it cares about, and why every organisation already has a data culture, somewhere on the spectrum from barely-there to full tiltWhy culture and outcomes feed each other rather than being an either/or, and how influencing behaviours and showing results almost always happen in tandemWhy every business claims to be "data-driven," how the reality usually differs, and why a new CDO's first 90 to 100 days is really about working out where the organisation actually sits versus where leadership thinks it doesThe "slippery shoulders" problem, and why nothing improves or gets maintained unless someone genuinely owns itWhy you can't see your own culture from the inside, and how stepping out to network, attend events, and compare notes with peers is often the only way to know whether you're ahead, behind, or better off than you thoughtA look ahead to the Orbition magazine landing in October, featuring a data leader who hasn't spoken publicly in over two years, alongside mentor and mentee stories and perspectives from beyond the CDO communityThe Director of Police AI role at the College of Policing, and how its rigid entry criteria expose the same old problem seen across data leadership: job descriptions that bear little resemblance to what organisations actually want from the roleKyle's thought of the week: most job descriptions are disconnected from what the business actually needs. Organisations have learned to use the right language, asking for leaders who'll work with the board and use data to drive commercial performance, then listing purely technical requirements underneath. Until that gap closes, the mismatch between what's advertised and what's wanted will keep repeating itself. Fundamentally, every organisation already has a data culture; it simply sits somewhere on a spectrum, and the job is to understand where before trying to move it.Catherine's thought of the week: you rarely recognise your own culture until you step outside it. Whether it's trust versus micromanagement, or how your data leaders are really perceived, the comparison only becomes clear when you go out, meet people, and see how others operate. And the honesty applies inward too, because no organisation describes itself as not caring about data, so the real work is uncovering where it genuinely stands.This episode is a candid, wide-ranging conversation on data culture, ownership, and incentives, and a reminder that the hardest problems in data and AI leadership remain stubbornly human, no matter how much the technology moves on.Housekeeping: The podcast is now broadcasting on LinkedIn Live. To watch along in real time, head to the Driven by Data Productions page on LinkedIn and follow it. We go live with each episode every Tuesday at 1pm BST, and our guest often joins the comments to answer your questions. Keep an eye out for upcoming events towards the end of the year, including Driven by Data Live, where Catherine will be handing out physical copies of the new magazine.

Dan Nathan and Guy Adami dig into the biggest story in markets: Nvidia's roundtable with Wall Street's top financiers — Jensen Huang, David Solomon, Jon Gray, and Stephen Schwarzman — and the multi-hundred-billion-dollar backstop deal getting compared to a modern-day CDO. Dan lays out why he thinks this AI CapEx build could make the dot-com bust and the GFC look tame, walks through Nvidia's doubling credit default swaps, and answers a listener question on exactly what would signal the bubble has popped. Plus: the cautionary tale of The Trade Desk's collapse from $140 to $14, why valuations are only richer once before in history (the dot-com peak), and a preview of what to watch in Cisco's earnings after the close today. Show Notes A short history of valuing stocks (FT) Wall Street just endorsed Jensen Huang's ‘big concept' for AI. What now? (CNBC) —FOLLOW USYouTube: @RiskReversalMediaInstagram: @riskreversalmediaTwitter: @RiskReversalLinkedIn: RiskReversal Media The financial opinions expressed in Risk Reversal content are for information purposes only. The opinions expressed by the hosts and participants are not an attempt to influence specific trading behavior, investments, or strategies. Past performance does not necessarily predict future outcomes. No specific results or profits are assured when relying on Risk Reversal. Before making any investment or trade, evaluate its suitability for your circumstances and consider consulting your own financial or investment advisor. The financial products discussed in Risk Reversal carry a high level of risk and may not be appropriate for many investors. If you have uncertainties, it's advisable to seek professional advice. Remember that trading involves a risk to your capital, so only invest money that you can afford to lose. Derivatives are not suitable for all investors and involve the risk of losing more than the amount originally deposited and any profit you might have made. This communication is not a recommendation or offer to buy, sell or retain any specific investment or service.

Today we are bringing a great show for you. Ron Arenas and Ron Kirk are hosting. Our first guest is CDO football coach Scott McKee. Coach McKee brings many years of valuable experience as a coach and as a former walk on player at the University of Arizona.  We'll find out about this season's CDO team.Then, our next guest is Tom Sommerville. A former police officer and current member of Boys In Blue. Tom will share with us the mission of Boys In Blue. And why it means so much to him.

The world of IT is filled with technical qualifications in all manner of disciplines. They've become an expected baseline for knowledge in broad fields like networking and security, as well as narrower, vendor-specific knowledge and skills. But what happens as IT leaders move up to more senior roles? Steve Clarke, cofounder and director of Freeman Clarke joins host Eric Hanselman to talk about the challenges that senior IT professionals have in establishing their bona fides as technical business people. The role of a CIO, CTO, CISO or CDO requires technical depth, but the more important part is the ability to integrate that knowledge with business operations. It's not an easy transition to undertake and even more complicated to identify.  Discussions that are taking place in the 451 Research 451 Alliance community brought up the idea of a business level certification process and how it would have to characterize that unique knowledge set. The Standard is an approach that Steve and his colleagues began to address this issue. The 451 Alliance membership is free and open to all qualified IT professionals and business leaders who want to contribute to industry-leading research. Members take anonymous online surveys in exchange for access to research results that power their IT strategy.   More S&P Global Content: Join the 451 Alliance The Standard Certification The Problem with the Status Quo For S&P Global Subscribers: US tech spending intent dips in Q2, but projects to grow in Q3 – Tech Demand Indicator Highlights from Q2 2026 Beyond connectivity: A CIO's road map from network APIs to business impact Enterprises cautiously optimistic for AI amid data management challenges Host/Author: Eric Hanselman Guest: Steve Clarke, cofounder and director of Freeman Clarke and Tech Leaders Connect Producer/Editor: Dylan Scheible Published With Assistance From: Feranmi Adeoshun and Sophie Carr

Today I am joined by Misty Farmer and Amanda Osborne! Misty Farmer leads Make a Wish South carolina's mission to grant life-changing wishes for children with critical illnesses across the state.   Her forward-thinking approach has enabled the organization to adapt and flourish, leading to a steady increase in revenue and the number of wishes fulfilled each year for more than a decade. Amanda Osborne currently serves as the CDO at Make-A-Wish South Carolina. In this role, she oversees the fundraising operations, event, major gifts solicitations and other revenue generating initiatives.  Amanda is also a proud graduate of Leadership Greenville, Class 42.  In this episode we talk about the Wish granting process, the impact of a single wish, what working at a non-profit is like, how they both got their start in the non-profit sector, and so much more!Make-A-Wish WebsiteMake-A-Wish FacebookMake-A-Wish Instagram

A Delaware state court ruling rewrote the rules on corporate liability and CDOs are directly in the crosshairs. This is our most-played episode ever, and if you haven't heard it, now's your moment.

In this episode, Ricard Vilá, CDO at LATAM Pass, outlines his strategies for designing a future-ready technology organization. He shares lessons on shifting IT from a cost center to a value engine, fostering genuine team empowerment, managing multilingual organizational structures and navigating rapid AI transformation to meet evolving business needs.

The Small Business Administration is ramping up its relationship with Palantir, announcing a “new phase” in its anti-fraud work with the data analytics and software giant. In a press release Tuesday, the SBA said it's formalizing and expanding its work with Palantir after signing a $300,000 contract in January for a fraud prevention pilot and bootcamp. That deal had a projected end date of April 4, but the agency said in the release that the “collaboration” with Palantir will now continue through “ongoing efforts to identify, investigate, and help prosecute fraud in pandemic-era small business relief programs.” The agency pointed specifically to its Paycheck Protection Program and COVID-19 Economic Injury Disaster Loan program as areas previously beset by fraud. SBA Administrator Kelly Loeffler said in a statement that the Palantir partnership “will strengthen our ability to expose fraudulent actors, support criminal enforcement actions, and recover stolen funds with advanced technology and artificial intelligence.” “No amount of fraud is acceptable — whether it is $10,000 or $10 million — which is why the SBA is deploying these tools to accelerate our work to surface wrongdoing and ensure those who cheated taxpayer-funded programs face consequences,” she added. The National Institutes of Health selected Kristen Honey, a longtime government data and technology official, to head up its coordination of public-private research partnerships. In a social media post, the Office of the National Coordinator for Health IT announced Honey as the inaugural official in the NIH role. As part of her duties, Honey will help “to build robust partnership models, reduce duplication, improve transparency, and move promising ideas from concept to execution with greater speed and consistency in collaboration with” ONC and across the department, per the post. The chief partnerships officer role is housed in the Office of the Director's Division of Program Coordination, Planning, and Strategic Initiatives, per the post. “The ‘wicked problems' that I run toward—complex, interdisciplinary challenges no one wants to own and that require cross-sector solutions—just got bigger. Joining NIH as Chief Partnerships Officer,” Honey said in a LinkedIn post. Honey has served in various HHS and White House roles over the past decade — including as HHS's chief data officer. Honey was initially installed as CDO after President Joe Biden's administration reorganization of its IT, data and artificial intelligence portfolio. Her time as CDO, however, appears to have ended after the Trump administration undid that reorganization in March, per her LinkedIn. Since then, she has listed her role as senior executive service. Currently, Arman Sharma, HHS's deputy chief AI officer, is listed as the agency's top data official on the CDO Council webpage. The Daily Scoop Podcast is available every Monday-Friday afternoon. If you want to hear more of the latest from Washington, subscribe to The Daily Scoop Podcast  on Apple Podcasts, Soundcloud, Spotify and YouTube.

In Episode 15 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined for the third time by Vin Vashishta, CEO and Founder of V-Squared, where they discuss why the organisations getting the most value from AI are focused less on models and use cases, and more on outcomes, information architecture and business transformation, which includes;Why AI strategy has become a revenue growth strategy rather than a technology strategy.Why AI is an information product that depends on context, information architecture and data.Why information flywheels will become the defining capability that separates AI leaders from everyone else.Why organisations are moving from buying AI products to forming outcome-based partnerships with technology and consulting providers.Why CEOs and CFOs are now demanding clear links between AI investment, business outcomes and shareholder value.Why meaningful AI ROI requires organisations to transform operating models rather than simply automate existing processes.Why the fastest-growing organisations are extracting the greatest value from AI by creating entirely new forms of value.Why organisations such as JPMorgan Chase and Eli Lilly are turning AI into sustainable competitive advantage.How organisations can begin building information flywheels.Why technical strategy is becoming a core capability for both executive leaders and technical practitioners as traditional management layers disappear.Why ownership of commercial outcomes matters far more than whether AI sits with the CIO, CDO or a Chief AI Officer.Why robotics, autonomous systems and edge AI could soon eclipse today's generative AI conversation.Why LLMs will become just one small component within far more sophisticated agentic systems.Why we'll see LLMs diminish in importance.Thanks to our sponsor, Data & AI Literacy Academy.Data & AI Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data & AI literacy first.At Data & AI Literacy Academy, they don't just teach data skills. They empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. They're bridging the gap between business and data teams, so they can all work towards aligned outcomes.From those taking their first steps in data & AI literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that they offer. They embed a deep data culture shift through a transformative change management programme.They take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com.

Dave Trepanier's path into structured credit wasn't linear. Growing up on a French-Canadian farm in rural Ontario, he learned grit, teamwork, and how to make decisions when outcomes are uncertain—lessons that would later show up in an unlikely place: the earliest days of the CLO market. Now Global Head of GCSS-Structured Products in FICC Trading at Bank of America, Dave has helped build one of the industry's leading CLO and CDO trading franchises while navigating every major modern credit cycle.In this episode, Dave walks through the long road from political science and law school plans to financial engineering, options markets in Chicago, and a pivotal move to Charlotte—where CLOs were still modeled by hand in Excel off faxed trustee reports. We discuss what those “stone age” workflows taught him about risk, liquidity, and market structure, how the product evolved through telecom and the GFC, and why electronification, data, and systematic strategies may define the next chapter of credit markets.

América Latina no está atrasada en IA: está descoordinada. Tito Neira conversa con Michael Collemiche, presidente y fundador de CDO LATAM (comunidad de +18,000 seguidores en 16 países), sobre por qué la región tiene talento, demanda y datos, pero le falta poder de negociación. Hablan de la brecha de inversión, la nube como "el acueducto", los sesgos que pueden costar vidas y la pregunta que define todo: ¿estamos en la mesa de las discusiones o estamos en el menú?00:00 Intro03:06 La brecha de inversión04:53 El talento existe pero se fuga07:51 ¿Por qué seguimos consumiendo?08:21 Sesgos: data del norte10:21 La nube como acueducto12:00 Data centers: agua y energía14:24 Consumo masivo vs valor17:18 Dónde sí se captura valor20:45 Ventaja de los que ya explotaban data23:03 El riesgo sin gobierno de IA25:53 El rol del CDO se transforma26:52 Sesgos críticos: salud y justicia30:53 Transferencia tecnológica: ley de Chile34:00 De consumidores a generadores37:33 Pensamiento crítico y espejitos39:25 ¿En la mesa o en el menú?41:26 Cierre✩ CURSOS DISPONIBLES

Most companies don’t have a technology problem. They have a complexity problem. In this episode of Technovation, Peter High speaks with Gus Shahin, EVP of Business Technology and Operations at NetApp, about consolidating IT, operations, global security, and enterprise process under a single leader. Shahin joined NetApp in 2024 after 24-plus years at Flex, where he served as CIO and led global supply chain. He argues that transformation stalls on change management, not technology, and that the real goal of enterprise AI is not a handful of pilots but an AI-first culture. Key Highlights: Why consolidating four functions under one leader beats siloed CIO, CDO, and CTO roles How NetApp launched 29 AI projects and deliberately killed 11 to 12 mid-year Why the shift to inferencing makes storage performance the new bottleneck How “fail fast” became a transformation lever, not a slogan Where buy-versus-build is shifting, and the hidden cost of building your own This episode is presented by Celonis — Give AI the context it needs. Learn more at celonis.com/technovation

Subscribe to This Week in Hospitality wherever you get you podcasts: Spotify - https://open.spotify.com/show/5oPExA0txHMjEI5Ye13IUy Apple Podcasts - https://podcasts.apple.com/us/podcast/this-week-in-hospitality/id1849637233 Youtube - https://www.youtube.com/@ThisWeekinHospitality   Sean O'Neill of Skift joins the roundtable this week for a conversation that cuts straight to the fault lines running through the hotel industry right now — distribution versus identity, brand proliferation versus brand meaning, and the wellness promise versus wellness delivery. The panel leads with Pali Society's decision to bring its 16-property California portfolio into Marriott's Design Hotels ecosystem — the single largest addition in the program's history. Edwin draws the line everyone in the independent space is afraid to say out loud: using Marriott as a marketing channel is smart; slowly operating for Marriott guests instead of your own is how you lose the thing that made you worth joining in the first place. Scott is blunter: "Every owner in the world loves independence until they have empty rooms." From there, Sean's own Hilton story lands on the table. Hilton's new CDO is signaling five or six organic brands are coming — and a trademark filing, locked domain, and placeholder social accounts are already pointing toward a lifestyle concept called "Tortoise." The group debates whether the major brand groups, Hilton included, are actually delivering on their supposed superpower. Sean's take: in an AI-discovery world, the question isn't how many brands you have — it's whether any of them mean anything. The conversation gets sharper on wellness — a category where nearly everyone claims the space and very few actually own it. Ben makes the obvious argument: if Oura can sync with fitness apps, why can't Canyon Ranch pull your health data? Edwin adds the counterweight — the freedom to do nothing is the next frontier that nobody's building for. Plus: Soho House gets called out for failing to remember Edwin's green tea order after ten years, Scott's Venice discovery about a pool built in feet instead of meters, and Zach's verdict on San Antonio as the most underrated hotel market in America.   This Week in Hospitality is presented to you by Journey. Journey is a loyalty platform built specifically for independent boutique hotels and high-touch hospitality brands. Our mission is to give operators the same powerful rewards engine, data intelligence, and guest insights that major chains rely on — without asking them to give up the individuality, soul, or story that makes their property extraordinary. If you're an owner or operator of an extraordinary, independently owned and operated hotel or residence — and you want to see whether your property is a fit for the Journey Alliance — you can learn more and apply at https://www.journey.com/alliance   Key Topics & Timestamps 00:00 — Intro 38:13 — Story #1: Palisociety Joins Marriott's Design Hotels 49:52 — Story #2: Hilton's New Brand Factory 01:01:51 — Spice of the Week   Your Hosts: Zach Busekrus — Journey LinkedIn: https://www.linkedin.com/in/zachbusekrus/ Instagram: https://www.instagram.com/behindthestays/   Scott Eddy — Global Travel & Hospitality Expert @MrScottEddy LinkedIn: https://www.linkedin.com/in/mrscotteddy/ Instagram: https://www.instagram.com/mrscotteddy/   Ben Wolff — Founder of Onera & Oasi LinkedIn: https://www.linkedin.com/in/ben-wolff/ Instagram: https://www.instagram.com/iambenwolff/   Edwin Kramer — Luxury Hotelier Consultant & Former GM LinkedIn: https://www.linkedin.com/in/edwinckramer/ Instagram: https://www.instagram.com/edwinkramer/

Send us Fan MailAI is finally in everyone's hands, and that's exactly why it's getting risky. Grant McGaugh sits down with veteran tech leader Darrell T. Black (CIO, CTO, CDO) to discuss what it really takes to bring AI into a business without compromising trust, compliance, or the back office. We get into the difference between experimenting with a chatbot and deploying AI inside the systems that run payroll, HR, finance, and customer data.Darrell shares a grounded view of AI readiness: understand your current processes, map the real workflow (not the version on paper), define the future state, then conduct a gap and impact analysis before you automate anything. We also unpack why AI hallucinations matter, how probabilistic AI differs from deterministic technology, and why “it sounds good” is not the same as “it's accurate.” If you're thinking about agentic AI, this is where the conversation gets practical about audit trails, human oversight, and governance that can scale.We also tackle the bigger societal layer: bias in algorithms, safeguards in hiring and healthcare, and why policy often sets the tone for enterprise behavior. And Darrell leaves us with a simple warning you'll remember: you might think you're adopting an AI puppy, but you're responsible for the full-grown AI dog. If you're a founder, operator, or IT leader trying to use AI to scale responsibly, this one is for you.Subscribe for more conversations like this, share the episode with a friend building with AI, and leave a review with the biggest AI risk you want us to tackle next.Thanks for tuning in to this episode of Follow The Brand! We hope you enjoyed learning about the latest trends and strategies in Personal Branding, Business and Career Development, Financial Empowerment, Technology Innovation, and Executive Presence. To keep up with the latest insights and updates, visit 5starbdm.com.And don't miss Grant McGaugh's new book, First Light — a powerful guide to igniting your purpose and building a BRAVE brand that stands out in a changing world. - https://5starbdm.com/brave-masterclass/See you next time on Follow The Brand!

Welcome to another episode of the Data Debrief, the companion show to Driven by Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom unpack Tuesday's episode, share what's been on their minds, and explore the realities of leadership, culture, and capability across the data and AI landscape.This week, Catherine and Kyle reflect on the conversation with David Krauza, VP of Enterprise Data Strategy, Products & Governance at Comcast, diving deeper into the "arts and crafts" trap that derails data programmes, the discipline of building stakeholder trust before you need it, and what it really takes to drive the bus rather than ride it.They cover:Why David's mandated business school module ended up shaping his outlook on data leadership, and the recurring pattern of guests whose commercial thinking was forged outside a purely technical backgroundThe "arts and crafts project" analogy David's boss used to describe technically impressive work that never moves the needle, and why naming the difference between process-enjoyment and outcome-focus matters as much in data as it does in any creative pursuitWhy so much of the data and AI ecosystem gravitates toward exciting new models, tools, and techniques without tying the work back to specific goals, decisions, and KPIsDavid's framing that you have to help people before you need their help, and why the leaders who consistently land the biggest roles are the ones already putting into their networks and communities long before they need anything backCatherine's take on why this same principle defines external brand building, and why leaders who wait until they're job hunting to invest in relationships are always playing catch-up against those who started years earlierKyle's view that building relationships with future stakeholders is not a side project for a data leader, it is the job, every bit as much as overseeing platform delivery, governance, and architectureWhy David reframed the trust gap many data leaders face as a sequencing problem rather than a communication problem, and what that distinction means for how and when leaders should be reaching outThe "bus riders and bus drivers" analogy at the heart of the episode title, and why organisations hire a data leader precisely because they don't already know the answer, making it the leader's job to shape direction rather than simply execute instructionsWhy being a strong, detailed communicator changes the entire dynamic of a hiring conversation, and how that same skill plays out with stakeholders once someone is in the roleCatherine's practical tip for building interview and communication confidence using AI tools like ChatGPT or Claude as a low-stakes practice partner, and why consistent repetition beats waiting for natural talent to show upKyle's thought of the week: prompted by a message from a CDO at a crossroads in their career, Kyle reflects on why the CDO role isn't disappearing or resurging industry-wide so much as it's becoming entirely dependent on whether a business's leadership views data as a commercial value-creation function or a technology delivery capability. Where it's the latter, that responsibility increasingly sits with the CIO, and Kyle notes the early signs of broader transformation-style mandates emerging that fold CDO, CIO, and Chief AI Officer responsibilities into a single board-level role.This episode explores what it actually takes to drive value rather than just deliver outputs, the discipline of investing in relationships long before you need them, and why naming the gap between busywork and real impact is often the first step to closing it.

In Episode 11 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by David Krauza, VP of Enterprise Data Strategy, Products & Governance at Comcast, where they discuss why strategic clarity and proactive stakeholder engagement are the keys to unlocking genuine business value from data and AI, which includes;Why the root cause of failed AI and data programmes is almost never the technology and almost always the absence of a clear business outcome.How to tell the difference between an organisation that has genuine strategic clarity and one that just has a compelling PowerPoint.Why a strategy without explicit trade-offs, knowing what you are not going to do, is no strategy at all.How "arts and crafts" projects quietly drain data programmes of focus, credibility, and commercial impact.Why retrofitting goals around work already underway creates a circular dependency that pulls organisations further from real value.Why the "bus riders and bus drivers" framework reframes what it means to be an effective data leader.Why waiting for perfect conditions before driving impact is one of the most common and costly habits of data leaders.How proactively building relationships with CFOs, COOs, and business unit heads before you need them is what separates influence from scrambling.Why the trust deficit most data leaders face is a sequencing problem, not a communication problem.How starting within your own team or with a single friendly stakeholder is the most practical way to begin building the bus driver muscle.Why most CDO mandates are structurally designed to deliver outputs rather than value and how that shapes the type of leader organisations end up hiring.How to navigate a broken mandate in practice and why challenging it in the interview room is riskier than it sounds.Why the incentive structures within data leadership roles have historically rewarded technical delivery over commercial impact.Why the data industry's technical origins created an archetype that is now working against the commercial value organisations actually need.How company size and culture determine whether data is treated as a strategic asset or an internal IT service and why that changes everything.Why organisations that started their data journey for the wrong reasons often find the perception too deeply embedded to shift from within.Thanks to our sponsor, Data & AI Literacy Academy.Data & AI Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data & AI literacy first.At Data & AI Literacy Academy, they don't just teach data skills. They empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. They're bridging the gap between business and data teams, so they can all work towards aligned outcomes.From those taking their first steps in data & AI literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that they offer. They embed a deep data culture shift through a transformative change management programme.They take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com.

Your people aren't tired of change — they're saturated. There's a difference, and it's the difference between an AI rollout that lands and one that bounces off your workforce entirely. Kelle Fontenot is the Chief Digital Officer at KPMG US, where the CIO, the CTO, and the Chief Data Officer all report to her. She owns internal innovation, architecture, platform, engineering, and data across a 40,000-person workforce — and she's spent the last four and a half years steering that organization through cloud, data, and now an AI wave reshaping how every one of her people does their job. In this conversation, Kelle reframes 'change fatigue' as 'change saturation,' reveals that KPMG employees built 25,000 AI agents in the last six months alone, walks through the synthetic-data acquisition powering regulated AI testing at scale, and explains the brand-new Anthropic partnership turning a 140-year-old services firm into a products company.   What you'll learn • Why 'change fatigue' is the wrong diagnosis — and what 'saturation' changes about how you roll out AI • Why KPMG refuses to use AI as a head-count lever — and why that decision is actually accelerating adoption • How 40,000 KPMG employees built 25,000 AI agents in six months — and what that means for who counts as a 'builder' • Why the CIO, CTO, and CDO all report to one person — and what would break if they didn't • How synthetic data lets a regulated firm test AI at scale without the breach risk • What KPMG's Anthropic partnership signals about the future of professional services   Connect Kelle Fontenot on LinkedIn KPMG US IT Visionaries Podcast   Chapters 0:00 AI Change Has Become AI Saturation 1:29 Why “Change Fatigue” Is the Wrong Diagnosis 3:27 Prompting Like It's November 4:46 Giving People Space to Innovate 6:38 AI Is Not a Headcount Lever 10:07 Building AI in a Regulated Business 11:24 The Risk Container Around AI 14:12 The AI-Augmented Auditor 17:21 The Agent Governance Problem 20:59 Why Digital, Data, and Tech Sit Together 22:59 Building an Inside Startup 30:04 Innovation Has to Happen at the Edge 36:48 The ROI Math for AI Agents 38:50 Why KPMG Bought a Synthetic Data Company 44:09 KPMG's Anthropic Partnership 51:03 Shipping AI at Scale 52:10 Kelle Fontenot's Advice for Leaders -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Welcome to another episode of the Data Debrief, the companion show to Driven by Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom unpack Tuesday's episode, share what's been on their minds, and explore the realities of leadership, culture, and capability across the data and AI landscape.This week, Catherine and Kyle reflect on the conversation with Sarah Emerson, Group Director of Insight & Business Partnering at Howden, diving deeper into the growing importance of commercial thinking, business partnering, and the role relationships play in driving value from data.They cover:Why Sarah's background in finance and corporate strategy offers a unique perspective on data leadership, and how commercial acumen can become a powerful differentiator for leaders looking to influence organisational outcomesThe challenge of connecting data strategy to business strategy, why many organisations struggle to articulate strategic priorities clearly, and the practical ways data leaders can uncover them regardlessWhy curiosity about business value shouldn't be reserved for senior leaders, and how analysts at every level can develop a stronger understanding of commercial impactThe growing importance of business partnering as a dedicated capability, and how organisations can bridge the gap between technical teams and business stakeholders more effectivelyThe realities of operating model design, why federated approaches continue to gain traction, and the trade-offs organisations must consider when balancing proximity to the business with cost and complexitySarah's view that self-service analytics has largely failed to deliver on its original promise, and what that means for the future of data enablement and adoptionWhy understanding how business leaders are measured, incentivised, and rewarded can dramatically improve stakeholder engagement and increase adoption of data-led initiativesThe challenges of discussing performance, incentives, and accountability within organisations, and why trust and relationship-building remain critical leadership skillsThe evolving role of the Chief Data Officer, the increasing consolidation of data responsibilities back into CIO organisations, and what this shift could mean for the future of data leadershipHow AI has accelerated organisational debates around ownership, accountability, and transformation, with many businesses still determining where responsibility ultimately sitsThe emergence of broader transformation and innovation leadership roles that combine data, technology, AI, digital, and business transformation under a single mandateKyle's thought of the week: as more organisations place data leadership responsibilities back under the CIO, many of the lessons learned throughout the evolution of the CDO role risk being forgotten. The challenge now is ensuring that value creation, business engagement, and commercial impact remain at the centre of the agenda, regardless of where accountability sits.This episode explores the realities of commercial leadership in data, the importance of business partnering, and why understanding people, incentives, and organisational dynamics is often just as important as understanding data itself.

Rural healthcare systems across the U.S. are facing a growing physician shortage—and traditional solutions aren't enough. In this episode, Stewart Gandolf is joined by Dr. Kenneth Holmen, President and CDO of CentraCare, to discuss how his organization is tackling the problem head-on by helping launch the first new medical school in Minnesota in over 50 years. From workforce shortages and aging populations to siloed systems and outdated thinking, they explore what's driving the crisis—and how a new, community-centered model for education and healthcare delivery could help solve it.

Most organizations default to replicating data: copying it from source systems into warehouses and lakes so their tools can reach it. Anu Jain, founder and CEO of Nexus One, thinks that's the wrong answer. Malcolm isn't so sure and that's where it gets interesting.

Why Most Enterprise AI Projects Hit a "Value Ceiling" — And How to Break Through | Dr. Fern HalperWhat separates the companies actually winning with AI from the ones burning budget on chatbots that go nowhere? In this upcoming episode of Redefining AI, host Lauren Hawker Zafer sits down with Dr. Fern Halper — VP of Research at TDWI, Founder of the AI Foundations Group, former Bell Labs lead analyst, and one of the most respected voices in enterprise AI strategy — to unpack the ideas behind her highly anticipated new book, Data Makes the World Go 'Round: The Data, Tech, and Trust Behind AI Success.With over 30 years bridging deep technical execution and C-suite strategy, Dr. Halper explains why so many organisations are stuck chasing hype instead of value, and what it actually takes to move AI from lab experiments into production systems that drive real ROI.Inside this upcoming episode, you'll learn:Why generative AI hits a "value ceiling" without trusted, governed data foundationsThe execution traps that sank AI initiatives at Zillow, Amazon, and othersHow data lakehouses and data fabric architectures unify siloed data for AIWhy MLOps is so hard — and why every model eventually degradesThe critical difference between data governance and AI governanceHow agentic AI changes the risk equation when systems start taking autonomous actionsThe shift from controlling what AI produces to overseeing what AI doesHow to tie AI use cases to measurable KPIs instead of vanity metricsEmbedding fairness, explainability, and EU AI Act compliance without killing innovationDefending against shadow AI while democratising analytics across the businessWhether you're a CDO, CIO, VP of Data, AI product leader, or a business executive under pressure from your board to "do something with AI," this is the strategic playbook you've been waiting for.

Why Most Enterprise AI Projects Hit a "Value Ceiling" — And How to Break Through | Dr. Fern HalperWhat separates the companies actually winning with AI from the ones burning budget on chatbots that go nowhere? In this upcoming episode of Redefining AI, host Lauren Hawker Zafer sits down with Dr. Fern Halper — VP of Research at TDWI, Founder of the AI Foundations Group, former Bell Labs lead analyst, and one of the most respected voices in enterprise AI strategy — to unpack the ideas behind her highly anticipated new book, Data Makes the World Go 'Round: The Data, Tech, and Trust Behind AI Success.With over 30 years bridging deep technical execution and C-suite strategy, Dr. Halper explains why so many organisations are stuck chasing hype instead of value, and what it actually takes to move AI from lab experiments into production systems that drive real ROI.Inside this episode, you'll learn:Why generative AI hits a "value ceiling" without trusted, governed data foundationsThe execution traps that sank AI initiatives at Zillow, Amazon, and othersHow data lakehouses and data fabric architectures unify siloed data for AIWhy MLOps is so hard — and why every model eventually degradesThe critical difference between data governance and AI governanceHow agentic AI changes the risk equation when systems start taking autonomous actionsThe shift from controlling what AI produces to overseeing what AI doesHow to tie AI use cases to measurable KPIs instead of vanity metricsEmbedding fairness, explainability, and EU AI Act compliance without killing innovationDefending against shadow AI while democratising analytics across the businessWhether you're a CDO, CIO, VP of Data, AI product leader, or a business executive under pressure from your board to "do something with AI," this is the strategic playbook you've been waiting for.

Juan Fredo brings Bisaya comedy straight from CDO to your feed. A dad of four, OFW, dance instructor, and now 36K-followers-strong creator, he talks reels, local slang, family life, and finding his comedy lane after years of trying.

I'm back after my wedding and honeymoon in March—and I'm coming in with a renewed mindset.One thing it reminded me of was how much I get out of this show. This podcast has always been about three things: gaining understanding, building community, and elevating voices in our field. I hope that experience is mirrored for all of you.This week, Wendy Connors talks with me about her professional journey and her shift from CDO to CEO—and the different levels of stress that come with it.What it means to work differently.What real work-life balance actually looks like. How to recognize good work. What happens when your database grows fast—and expectations grow even faster.Wendy Connors is the President of the Fannie and John Hertz Foundation. She is a passionate leader and advocate for science, technology, and education. As president of the Hertz Foundation, she leads the nation's most prestigious doctoral fellowship in applied science, engineering, and mathematics equipping exceptional students with unparalleled resources and lifelong support.

In this Omni Talk Retail interview, recorded live from World Retail Congress 2026 in Berlin, Chris Walton speaks with Brian Tilzer, former CTO and CDO of Best Buy and current Board Member at Signet Jewelers, about why AI represents retail's “third major technology wave” and what retailers can learn from the ecommerce and mobile revolutions that came before it. Drawing on leadership experience across Best Buy, CVS Health, Staples, and now Signet Jewelers, Brian explains why the retailers that win with AI won't simply use it to drive efficiency, but instead to create more human, personalized, and responsive customer experiences. The conversation explores how AI can help retailers better understand customer intent, empower frontline employees with richer information, and accelerate decision-making across the organization. Chris and Brian also discuss why traditional retail planning cycles may no longer move fast enough for the pace of AI innovation, how adaptive cross-functional operating models are becoming essential, and why testing, learning, and iteration will define the next generation of retail leaders. Throughout the conversation, one theme remains clear: AI may transform retail operations, but human connection will remain the industry's greatest differentiator. Key Topics Covered: • Why AI represents retail's “third major technology wave” • Lessons retailers can learn from ecommerce and mobile transformation • How AI can create more human customer experiences • Why frontline employees become even more important in an AI-driven world • The role of AI in understanding customer intent and personalization • Why retailers need faster planning and decision-making cycles • How adaptive operating models will shape future retail organizations • Why testing, learning, and iteration matter more than ever • The importance of combining digital, physical, and human retail experiences • How AI can help retailers solve long-standing operational challenges Thank you to Vusion for supporting Omni Talk Retail's live coverage from Berlin. #WorldRetailCongress #WRC2026 #OmniTalkRetail #AIinRetail #RetailInnovation #RetailTechnology #CustomerExperience #FutureOfRetail #DigitalTransformation #RetailLeadership

This week on the GovNavigators Show, hosts Adam and Robert sit down with Dr. Amanda Cash of the Data Foundation and Dr. Adita Karkera of Deloitte to unpack the latest Federal Chief Data Officer (CDO) Survey and what it reveals about the state of data, AI, and capacity across government.Drawing on six years of survey data, Amanda and Adita explain how the federal CDO role has evolved since the Foundations for Evidence-Based Policymaking Act and why today's environment may be the most challenging yet. With more than half of CDOs operating with five or fewer staff, agencies are being pushed to do more with less, even as expectations around AI, data governance, and transparency continue to rise.The conversation explores the growing overlap between Chief Data Officers and Chief AI Officers, the risks and opportunities of combining those roles, and how agencies can use AI to compensate for workforce gaps. They also highlight the critical role of the federal CDO Council in enabling collaboration and scaling best practices across government.Show Notes:Check out the CDO Survey hereCDO Survey webinar recordingWhat's on the GovNavigators' Radar:Apr 26 – 28: NASCIO's mid year conferenceApr 30: Fed100 Evening of Honors

AI agents are appearing across every enterprise platform, but most still struggle to move beyond scripted automation into systems that can reason, adapt, and operate within real workflows.On this episode of Ctrl + Alt + AI, Dimitri Sirota,  speaks with Justin Heller, former Chief Data Officer at Synchrony Financial and Chief Data & AI Officer of Quantify Data Advisors, about how organizations can leverage their existing data to reduce cyber risks, manage unstructured data, and integrate AI effectively. Justin, formerly the Chief Data Officer at Synchrony Financial, shares insights on the evolving role of data governance in an AI-driven world and the importance of shifting from a "pilot" mentality to creating sustainable AI-driven business value. Tune in as they unpack the complexities of managing both structured and unstructured data, ensuring relevance, and achieving true data governance alignment with emerging AI technologies.What to expect:How organizations can use existing data assets to reduce cyber risks and enhance AI initiativesWhy relevance, not just accuracy, is the key to effective AI and data managementThe importance of connecting unstructured data, metadata, and AI systems for better decision-makingThings to listen for: (00:00) Meet Justin Heller(01:25) Justin's transition from CDO to data advisor(02:35) From structured to unstructured data in AI environments(04:24) Why context engineering is critical for AI-driven business decisions(06:00) Moving beyond AI pilot projects to sustainable value(08:30) How data stewards can work with AI tools(09:00) Integrating AI across existing business processes(10:03) Building governance models for unstructured data(13:00) AI in unstructured data repositories: Best practices(15:00) Measuring ROI from generative AI in enterprises(18:00) Cross-functional collaboration for effective AI implementation(20:00) The role of CDAOs in driving AI-related outcomes(21:30) Shifting from pilot programs to ongoing AI-driven business value

Craig Hepburn sits at the intersection of enterprise technology and cultural institutions. He spent years as UEFA's Chief Digital Transformation Officer, overseeing its digital ecosystem, OTT platform build, and Innovation Hub. He moved to Art Basel as CDO in 2023. He is now an independent AI strategist, Perplexity Fellow, and prolific writer on the structural implications of AI for organisations and industries. His Substack has become essential reading on the gap between AI hype and implementation reality.Hepburn's central thesis is that most people and organisations are “tourists in someone else's architecture.” He draws a sharp distinction between using AI (prompting chatbots, generating content) and building with AI (constructing proprietary systems, workflows and tools). He argues the latter is what will separate winners from losers — and that the window for making that shift is narrowing fast.Crucially, Hepburn's argument extends beyond sport. His recent writing on “The Builder and the Billion Dollar Lie” contends that entire industries — consulting, systems integration, transformation programmes — were built inside the gap between the person who understood a problem and the person who could build the solution. Agentic AI, he argues, is starting to close that gap. That has profound implications for the agency model in sport.Unofficial Partner is the leading podcast for the business of sport. A mix of entertaining and thought provoking conversations with a who's who of the global industry. To join our community of listeners, sign up to the weekly UP Newsletter and follow us on Twitter and TikTok at @UnofficialPartnerWe publish two podcasts each week, on Tuesday and Friday. These are deep conversations with smart people from inside and outside sport. Our entire back catalogue of 500 sports business conversations are available free of charge here. Each pod is available by searching for ‘Unofficial Partner' on Apple, Spotify and every podcast app. If you're interested in collaborating with Unofficial Partner to create one-off podcasts or series and live events, you can reach us via the website.

Picking a use case, proving value, and expanding has been the standard starting point for enterprise AI. For organizations early in their AI journey, that advice still holds. But for large enterprises that are past the pilot stage and trying to scale across business units, geographies, and brands, it isn't enough.At NVIDIA GTC, Cameron Davies, Chief Data Officer of Yum Brands, shared how his team is thinking about AI differently — and why they had to. With 63,000 restaurant locations, 100 million daily transactions, and 1,500 franchisees across 155 countries, Yum operates at a scale where a single bad AI decision can fail loudly, repeatedly, and fast.In this episode, Maribel breaks down Davies' framework and what it means for how enterprise leaders should be thinking about AI in 2026 and beyond.---**What you'll learn**- Why the use case as a unit of AI planning has a structural limitation at enterprise scale- What "scalable AI skills" means and why it's different from building agents for specific use cases- Why governance has to come before deployment, not after — and what happens when it doesn't- How measurement functions as operational discipline, not just a reporting obligation- What Yum's AI flywheel looks like and why it only works if measurement is continuous- What this framework means for organizations that aren't Yum-sizedAbout Cameron DaviesCameron Davies is the Chief Data Officer at Yum Brands, the parent company of KFC, Taco Bell, Pizza Hut, and The Habit Burger Grill. He leads the company's corporate data and analytics strategy and oversees the development and adoption of advanced data capabilities. He previously spent seven years as SVP at NBCUniversal and over 18 years at The Walt Disney Company, where he led the Corporate Center of Excellence for AI and machine learning.---**Resources and references mentioned**-NVIDIA GTC session: "Scaling AI Agents Globally Across Brands, Use Cases, and Restaurants" (S81755) — Cameron Davies, Yum Brands- Responsible AI Institute — chaired by Manoj Saxena- Trustwise — AI trust startup founded by Manoj Saxena- Byte — Yum Brands' proprietary e-commerce, point-of-sale, and menu platform- Lopez Research blog: The Rules for Scaling AI Have Changed. Yum Brands Proved It. — [LINK]---

AI is forcing enterprises to rethink everything from hardware to governance, and most organizations are attacking it in silos. Mano Bhattacharyya (CTO, Nutanix) breaks down why AI isn't just an application layer problem, but an end-to-end transformation that spans compute (GPUs, ARM, DPUs), data management (unclean enterprise data, knowledge graphs), security (agent gateways, MCP server risks), and economics (token costs vs. usage explosion). He explains why CIOs need cross-functional AI committees, not isolated strategies, and why use case driven AI beats exploratory projects that burn budgets in months. The solution is to form AI committees where CIO, CTO, and CDO work together, not in silos. Focus on use case driven AI by learning from peers, rather than exploratory AI that becomes a budget trap. Start with small prototypes with dedicated use cases, not a free-for-all where every team tries something.   Chapters: 0:00 AI as an End-to-End Infrastructure Challenge 2:16 Networking, Storage, and Bare Metal VM Performance 4:43 Agent Security, Gateways, and Enterprise Governance 6:33 Use Case Driven AI and Learning from Peers -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.