Driven by Data: The Podcast
Orbition Group is delighted to bring you this podcast series, which is designed for Data Enthusiasts, to hear from some of the most high-profile Data, Analytics and AI thought leaders from around the globe.Each episode w...
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On the show
- Peter Everill2 eps
- Richard Masters2 eps
- Daragh Kelly2 eps
Also: Kevin Cassar, Keith Moody, Edward Chenard, Dru Patel, Sarah Emerson, Peter Crouch, Diana Comsa, Justin Borgman, David Krauza, Greg Freeman, Chris Pearce, Michael Ross, Marion Shaw, Kinnari Ladha, Barry Panayi, Kyle Winterbottom, Nirali Patel
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- 🇬🇧United Kingdom · Tech News#921.4K to 7.2K
- 🇲🇽Mexico · Tech News#83821 to 4.3K
- 🇳🇿New Zealand · Tech NewsHOME#46820 to 4.3K
- 🇨🇭CH · Tech News#72230 to 1.2K
- 🇿🇦ZA · Tech News#66217 to 1.1K
- Per-Episode Audience
Est. listeners per new episode within ~30 days
4.0K to 21K🎙 Daily cadence·200 episodes·Last published 1w ago - Monthly Reach
Unique listeners across all episodes (30 days)
13K to 71K🇬🇧34%🇲🇽20%🇳🇿20%+11 more - Active Followers
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7.3K to 39K
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* Data sourced directly from platform APIs and aggregated hourly across all major podcast directories.
| Date | Episode | Topics | Guests | Brands | Places | Keywords | Sponsor | Length | |
|---|---|---|---|---|---|---|---|---|---|
| 10/15/26 |  Data Debrief: Russian Bots, LIVE was hot & Kyle weeps as he's getting old | In Episode 28 of Season 7 of Data Debrief, Catherine Dowden-King and Kyle Winterbottom look back on a packed Driven by Data Live and the lessons from its roundtables. They then turn to what a reported attack on a Russian data centre might mean for data leaders, and debrief their conversation with German Faraoni, Global Director of Shared Services at Reckitt, on why data teams need to be in the right room.In this episode:Why Driven by Data Live was oversubscribed, and why roughly 45% of attendees being new to the events is good for the community.How Chatham House round tables help people share candidly, and why authenticity matters more than ever in an AI world.An HR agent use case: an anonymous assistant on top of an HR catalogue, with guardrails that signpost support and flag sensitive questions to the HR team.Why internal, people-led AI use cases are likely to come before customer-facing ones, and how they build confidence.How something as simple as understanding your maternity leave policy can influence employee loyalty, especially if non-competes are challenged in the UK.What the reported disruption to a Russian data centre, and the apparent drop in bot and crawler activity, suggests about how much online engagement is real. Both hosts are careful to flag that the reporting is still developing.Why geopolitical stability and data sovereignty are likely to be on every event agenda next year.How AI is giving data management, governance and quality, as well as cybersecurity, a new lease of life.How CISOs balance battening down the hatches against smothering the business, and what data leaders can learn from them.Why data leaders need to work closely with PR and understand their customers’ values, since decisions about where data lives could cost customers.Why doing business is more complex than ever, and what boards are weighing up on AI.A debrief of the interview with [Guest name], including the “if you’re in this room, you’re in the wrong room” idea.How a SKU-based use case showed the value of sitting with the executive team and working back to a use case that moves the P&L.Why no one will invite you into the room, and how to build the trust and credibility to get there.Why data teams working in isolation risk building things that go nowhere.How to write a CV for two audiences, those screening for keywords and those looking for outcomes, and why hiring managers say AI-written CVs now look the same.Community shout: the final event of the year, the quarterly roundtable, takes place on 17th November. Find the details at orbitiongroup.com. | 41m 26s | ||||||
| 10/13/26 | S7 | Ep 28 | The Data Translation Challenge with German Faraoni, Global Director of Shared Services for Data at Reckitt | In Episode 28 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by German Faraoni, Global Director of Shared Services for Data at Reckitt, where they discuss why data and AI investment still struggles to show measurable value, and why the answer lies in articulating it in business outcomes rather than data terms.German also shares how Reckitt cut the time to get a new SKU onto shelves by almost half, and how data leaders can earn their place in the right business conversations.They also discuss:Why data leaders are business professionals first and data specialists second.Why investment in data and AI is still articulated in data terms rather than business terms.How the same trap is repeating with AI, and what “hype credit” means for justifying investment.Why the metrics for data and AI should be the metrics the business already uses to measure success.What a data leader should ask a prospective employer before taking a role.How Reckitt reduced the time to commercialise an SKU from around 200 days to roughly half.Why the SKU release project started with process redesign rather than technology.How Gen AI emerged as the right tool for the job rather than the starting point.Why data practitioners must sit in the business conversations where results are discussed.Why starting small and avoiding “boiling the ocean” matters for scalability.How governance councils by data domain create a sustainable foundation for data quality.Why remediating legacy data issues remains hard, and how to choose which ones to fix.How AI lowers the cost of intelligence and speeds up the decisions that follow insight.What using AI as a “canary in the mine” reveals about weaknesses in your data and access controls.How to approach AI across internal efficiency, reimagining the existing business and creating new business models.Why agentic commerce could reshape how consumers and retailers interact.What AI means for the future of the CDO role, and who may be most exposed to change.Why competitive advantage will come from the right mix of premium and commodity AI, process understanding and orchestration.How large incumbents respond to disruption from smaller, faster AI-enabled businesses.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/ | 52m 05s | ||||||
| 10/8/26 |  Data Debrief: ASOS Breach, AI Index & Driven by Data LIVE | In this episode of the Data Debrief, Catherine Dowden-King and Kyle Winterbottom reflect on the week's news and the latest Driven by Data: The Podcast interview, with Tom Sadler of HP. Their central question is whether organisations are measuring AI activity (headcount, spend, job titles, tooling) instead of the productivity and financial outcomes that matter.They begin with the ASOS breach and the questions it raises about vendor risk. They then work through the latest Evident AI Index and what it rewards, before turning to Tom's candid views on hardware, cost and culture.They also discuss:Why the ASOS ransom note, delivered through the company's own app, marks a new and uncomfortable form of attack.How data leaders should work in lockstep with the CISO, or with the CIO where there is no CISO, as vendor ecosystems grow.Why the full story of a breach like this can take months to emerge, and why speculation helps no one.Why only 12% of reported AI use cases in the Evident AI Index demonstrate operational impact, and just 1% report financial impact.How the index's weightings (45% talent, 30% innovation, 10% transparency) shape what it rewards.Why organisations with the strongest financial returns from AI may not appear on the index at all.What the "too early to judge" argument gets right, and why 1,100 use cases over five years still demands better measurement.Why leaders chasing a higher ranking risk spending more money for the same 1% return.How adding "AI" to a job title, without mandate or budget, repeats the chief data officer pattern.Why the market is starting to reward titles over delivery when it hires.Why Tom Sadler argues hardware should be the last thing you think about in an AI strategy.How local compute can cut experimentation costs compared with spiralling cloud token costs.What running AI locally means for environmental impact.Why the CDO and CIO sometimes have never met, and how that drives sprawling costs and shadow AI.How a confined local "sandbox" lets teams experiment safely, with successful ideas scaled across the business.Why culture, not tooling, decides whether you can spot what has worked, and why a use case that cuts five hours of work to 30 minutes needs a place to be shared.What it takes to build the honesty to review mistakes regularly and correct them.Why a chief financial officer's advice to start running in your old trainers applies to AI spend. | 41m 30s | ||||||
| 10/6/26 | S7 | Ep 27 | The Secret to Enterprise AI Success according to HP with Tom Sadler, Data Science and AI Solutions Lead, HP | In Episode 27 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by Tom Sadler, Data Science and AI Business Solution Lead at HP, where they discuss why most AI and data strategies stall not because of the technology, but because different teams and divisions inside the same organisation simply don't talk to each other.They also explore why the best AI use cases are often built by accident, by employees solving their own problems rather than having a solution handed down from the top; how HP's compact AI workstations are bringing serious compute to the edge; and why data sovereignty and energy consumption are becoming unavoidable parts of every technology decision.They also discuss:Why most organisations buy technology before they understand the problem they're trying to solve.How workflow, governance and people should shape technology decisions, not the other way round.Why organisational silos lead divisions to pursue contradictory AI strategies without realising it.What "people, process, data, governance, technology" means as a decision-making order.Why the best AI solutions are often built by accident by employees solving their own problems.How HP's compact AI workstations bring trillion-parameter-scale compute to the edge.Why starting small and scaling out beats one large, upfront AI investment.How sandboxed, local compute lets teams experiment safely without runaway cloud costs.What the US Cloud Act and data sovereignty mean for where organisations choose to host their data.Why defence and government customers require fully offline, lockdown-capable AI environments.Why token pricing is more expensive in practice than headline prices suggest.How copilots and AI assistants need explicit rules and training to be genuinely useful.Why AI leadership is often fragmented across too many overlapping roles in large organisations.What it takes to give employees the freedom to experiment without losing control of security.Why storytelling and simplification matter when explaining AI to non-technical stakeholders.How rising AI energy and water use is becoming an unavoidable business consideration.Why prompt engineering training could meaningfully reduce unnecessary cloud AI usage.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.Thanks 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/ | 52m 52s | ||||||
| 10/1/26 |  Data Debrief: Dark Hair, AI Nightmare & The Biggest Role in Data? | 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. | 38m 31s | ||||||
| 9/29/26 | S7 | Ep 26 | 300 days as the UK Governments CDO with Aimee Smith, UK Government Chief Data Officer, UK Civil Service | In Episode 26 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is rejoined by Aimee Smith, Chief Data Officer at the UK Government, where they discuss her move from 25 years in policing and law enforcement into government's top data role, and why she believes culture, risk appetite and misaligned investment incentives, not legislation or technology, are what's really blocking data sharing across Whitehall.They also touch on the UK's evolving position on data and AI sovereignty, the real purpose behind the National Data Library, and how Aimee is building a framework to track and prove the value of government data.They also discuss:Why Aimee left a 25-year career in policing to become the UK Government's Chief Data Officer.How she is building influence across government departments without having formal authority over them.Why she restructured the Chief Data Officer Council around a strategic data roadmap and sector-based leads.What makes data sharing across government harder than the equivalent challenge in the private sector.Why culture and risk appetite, not legislation or technology, are the biggest blockers to data sharing.How she plans to fix the incentive problem by changing how Treasury assesses technology and data investment bids.Why she wants government's most valuable data treated as critical national infrastructure.How linking investment to data assets rather than departments could unlock sharing.Why legacy technology is as much a data cataloguing problem as a modernisation one.What she believes better data sharing could unlock for citizens navigating public services.Why she thinks the data sovereignty debate currently overlooks the data itself.How she is working with cross-government commercial teams to embed sovereignty principles into procurement.What the National Data Library actually is, and the shifting priorities behind its original manifesto pledge.How the National Data Library differs from a centralised data lake.Why AI adoption depends on getting the underlying data foundations right first.How she is using AI as a way to keep data on the agenda inside government.Why she is cautious about how AI investment gets communicated to the public.What her three-part framework for tracking data value looks like (commercialisation, valuation, usage).How Treasury's new balance sheet requirement for data valuation came about.What she hopes to point to as evidence of progress in twelve months' time.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.Thanks 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/ | 52m 42s | ||||||
| 9/24/26 |  Data Debrief: Networking, Intentionality & CVs that stand out | In this week's Data Debrief, Kyle Winterbottom and Catherine Dowden-King recap the Future of Data, AI & BI Summit with Starburst, share Catherine's top tips for networking at data events, and debrief this week's main episode with Simon Turner, Chief Technology Officer at Foil AI — including the Welsh Water case study that brought his "autonomic business" concept to life.They also discuss:Why the Future of Data, AI & BI Summit's core theme was the gap between giving people AI tools and reimagining how a business actually operates.What "codified business knowledge" — the context layer — means for scaling AI from local productivity hacks to full agentic systems.Catherine's top tips for networking at data events: doing your homework, messaging speakers in advance, and finding natural pauses for small talk.Why leading with curiosity, rather than negativity, makes conversations easier to build on.Why giving yourself permission to step away from an event is as important as showing up to it.How Simon Turner's Welsh Water case study used agentic AI to cut through false alarms during this summer's drought.Why the "autonomic business" concept compares agentic AI to a heartbeat that speeds up without conscious thought.Why having access to AI tools is no longer a competitive advantage, now that everyone has them.The debate between focusing on a handful of core business metrics versus giving people room to experiment and discover new use cases by accident.Why the best AI use cases sometimes emerge locally, before being scaled across a business.Why AI is making CVs look increasingly similar, and how outcomes-focused writing helps candidates stand out.Why intentionality — in networking and in career planning — matters more than ever in a fast-changing market.Why data and AI leaders should back the people already experimenting successfully with AI tools, not just the official roadmap.A preview of the "data dilemmas" segment returning for Driven by Data Live. | 40m 16s | ||||||
| 9/22/26 | S7 | Ep 25 | The Autonomic Business: Why AI Is a Leveller, Not an Advantage with Simon Turner, Chief Technology Officer at FOIL AI | 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. | 47m 56s | ||||||
| 9/17/26 |  Data Debrief: We get Political | 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. | 40m 52s | ||||||
| 9/15/26 | S7 | Ep 24 | Are you a Merchant of Self-Inflicted Complexity? David Castro-Gavino, Executive Director, Head of Data Deployment at AstraZeneca and Boyan Angelov, Principal Strategist at Exxeta | 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/ | 58m 06s | ||||||
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| 9/10/26 | AI adoptiondata leadership+3 | Greg Freeman | Data & AI Literacy Academy | — | AIemployment+5 | — | 48m 50s | ||
| 9/8/26 | AI literacydata literacy+3 | Greg Freeman | Data & AI Literacy Academy | — | AIdata literacy+3 | — | 50m 02s | ||
| 9/3/26 | AI technologydata literacy+4 | Chris Pearce | ChatGPT-powered smart learning teddy bearToniebox+2 | New York | AI teddy beardata literacy+5 | — | 39m 42s | ||
| 9/1/26 | AI in productiondata engineering+3 | Chris Pearce | Ageas | — | AIproduction+5 | — | 51m 52s | ||
| 8/27/26 | AI impact on job marketgraduate hiring collapse+4 | Michael Ross | — | — | AIgraduate hiring+7 | — | 36m 47s | ||
| 8/25/26 | data insightscommercial value+4 | Michael Ross | Domestic & GeneralMcKinsey+4 | — | data insightscommercial value+6 | — | 1h 01m 34s | ||
| 8/20/26 | data leadershipburnout+4 | Davin Crowley-Sweet OBECatherine Dowden-King | National Highways | — | data leadershipburnout+8 | — | 46m 26s | ||
| 8/18/26 | data valueAI investment+4 | Nick Zervoudis | Value from Data & AI | — | data teamsAI productivity+5 | — | 58m 38s | ||
| 8/13/26 | wildfiresdata culture+4 | Marion Shaw | Cencora | South WalesEurope+3 | wildfiresdata culture+7 | — | 33m 45s | ||
| 8/11/26 | data culturetrust+4 | Marion Shaw | CencoraWhy Data Culture Matters | — | data culturetrust+5 | — | 50m 57s | ||
| 8/6/26 |  Data Debrief: The AI Rollback & Regrets | 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 Kyle's conversation with Laura Fiacco, Founder of Adaptive Assets, exploring why communication, influence and commerciality remain some of the most overlooked skills in data leadership. Alongside the episode discussion, they dive into LinkedIn's apparent AI U-turn, the growing challenge of AI-generated content, and why the future of data leadership may be less about technology and more about transformation.They cover:Why LinkedIn, Snapchat and Substack are all taking steps to tackle AI-generated content, and what it says about organisations pushing AI adoption before understanding its long-term consequencesWhether we're heading towards a world where overusing AI becomes just as much of a performance concern as not using it at allThe ethical grey areas surrounding AI-generated communication, from political statements to funeral tributes, and why context matters far more than blanket rulesLaura's perspective on communication as a skill that compounds over time, and why nobody starts by presenting to a thousand peopleWhy communication isn't synonymous with public speaking, but instead about translating technical concepts into language that business leaders understand and care aboutThe importance of influencing without authority, building relationships, and developing the commercial mindset needed to turn technical work into business valueHow organisations continue to undervalue communication, relationship building and commerciality because they're harder to measure than technical capabilityPractical ways data professionals can develop these skills themselves, including writing, voice conversations with AI, and using large language models as personalised coaching toolsWhy curiosity, listening and asking better questions are just as important as being able to communicate confidentlyKyle's reflections on why transformation is becoming the next major destination for senior data leaders as technology becomes less of the challenge and organisational change becomes the real differentiatorCatherine's comparison between today's AI leadership roles and the "e-business" and "Chief Internet Officer" titles of the dot-com era, and why AI leadership may ultimately become absorbed into every business function as the technology maturesProgramming note: If you've been following Catherine's recent LinkedIn series on the evolution of executive technology roles, this episode expands on that conversation, exploring why today's AI job titles may eventually follow the same path as digital and internet leadership before them.This episode is a reminder that while AI continues to dominate headlines, long-term success still depends on the fundamentals: communicating clearly, influencing effectively, building relationships, and helping organisations change, not just implement new technology. | 39m 50s | ||||||
| 8/4/26 | S7 | Ep 18 | Influence without Authority by Communicating like an Executive with Laura Fiacco, Founder at Adaptive Assets | In Episode 18 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by Laura Fiacco, Founder of Adaptive Assets, where they discuss why communication, influence and commercial thinking have become the competitive advantage for modern data professionals, and how learning to communicate like an executive is now just as important as technical expertise.They also discuss:Why influence without authority is the defining skill for modern data leaders.The 4 quadrant brain framework for tailoring communication to different thinking styles.Why successful influence starts by understanding other people's goals before presenting your own ideas.Why relationship building happens outside the meeting room, not inside it.How to communicate technical work in a way executives immediately care about.Why every presentation should start with the business outcome, not the analysis.Why data professionals often answer questions that were never asked.What data leaders can learn from sales discovery.The questions every data professional should ask before proposing a solution.Why understanding failed attempts and hidden assumptions leads to better stakeholder conversations.How to influence when different executives have conflicting priorities.Why peer success stories influence behaviour more effectively than data alone.Why communication, influence and leadership should become measurable career progression criteria.Practical habits that help build influence, trust and credibility every day.Why AI will make communication, influence and judgement more valuable than technical expertise.Why every person needs to understand their specific role in delivering the wider business objective.Why every business strategy is built on assumptions that data should validate or challenge.How to align stakeholders when everyone interprets the same strategy differently.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. | 51m 08s | ||||||
| 7/30/26 |  Data Debrief: Patios, Politics & the Perils of Meta Glasses | 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 returns from a two-week break to catch up with Kyle on the conversation with Joanne Riseborough, Group Data Management and Culture Director at Lloyd's Banking Group, alongside a wide-ranging catch-up covering AI ethics, the future of education, and why context is everything when it comes to new technology.They cover:Why Joanne's willingness to repeat the same simple truth throughout her episode, rather than apologise for it, was itself the standout takeaway, and why data management has long been the least glamorous but most under-resourced part of the data value chainHow the AI boom has quietly made data management one of its biggest beneficiaries, as businesses scramble to build the foundations needed to use their new tools effectivelyWhy a job title that puts "management" and "culture" side by side gets to the heart of why the two are inseparable, and can't succeed without one anotherCatching up on two episodes missed while on holiday: Priya's candid take on the CIO-CDO relationship, and the idea that failing to draw clear lines of accountability creates "competition for relevance" between the two roles, not collaborationA conversation with Vin on turning AI into revenue, the value of concrete company examples over abstract theory, and how his "information flywheel" concept has moved from a future prediction to something organisations are now actively chasingA detour into Meta's AI glasses, why the debate over them (cool or creepy?) is really about context and nuance, and why platforms like LinkedIn struggle to hold space for anything in betweenA tie-back to Catherine's own past research using facial recognition technology, and how the same tool can be a public safety asset in one context and deeply troubling in anotherWhether AI ethics has a genuine seat at the boardroom table, or whether "activity as the barometer of perception" makes leaders reluctant to be the one applying the brakesAndy Burnham's call for parity between university and vocational routes, what it might mean for how people enter data careers, and the idea (borrowed from a recent Taylor Culver conversation) that data is a skill rather than a career path in its own rightWhy the debate over LLMs in university coursework mirrors the harm-reduction argument in sex education: teaching safe, responsible use beats an outright banProgramming note and community shout-out: Catherine's back from a two-week camping-and-patio-laying hiatus (send help, or bricklaying tips), and registration for Driven by Data LIVE is officially open, with a growing list of bespoke, invite-only events also on the horizon. Make sure you're on the events list to hear about them first.This episode is a reminder that the unglamorous, unsexy fundamentals, data management, clear accountability, honest conversations about ethics, are usually what make the shinier stuff actually work. | 48m 34s | ||||||
| 7/28/26 | S7 | Ep 17 | Data Management: The AI Boom's Biggest Winner with Joanne Riseborough, Group Data Management and Culture Director at Lloyds Banking Group | In Episode 17 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by Joanne Riseborough, Group Data Management and Culture Director at Lloyds Banking Group, where they discuss why the AI boom has quietly made data management one of the most strategically important disciplines in the boardroom.They explore why AI is shining a spotlight on data quality, governance and culture, how large enterprises balance modernisation with legacy technology, and why organisations that invest in strong data foundations will be best positioned to realise meaningful value from AI.They also discuss:Why AI has made data management more important than ever.Why data quality has moved back onto the boardroom agenda.How organisations should define what "good enough" actually means.What data quality should actually be measured against.How large enterprises balance modernisation whilst continuing to operate critical legacy platforms.The unique data management challenges created by hybrid cloud and on-premise environments.How data culture influences the success or failure of AI adoption.Why data and AI literacy is becoming a strategic capability rather than a technical nice-to-have.How Lloyds Banking Group is building capability through education, practitioner communities and leadership development.Why executive sponsorship remains one of the strongest predictors of successful AI transformation.How organisations should balance fixing today's problems whilst investing in tomorrow's capabilities.Why continuous monitoring and data observability will become fundamental components of modern data management.How reusable data products can accelerate both governance and AI adoption.Why organisations should think about both data for AI and AI for data.Why responsible AI starts with trusted data, lineage and governance rather than model oversight alone.How central strategy and standards can successfully coexist with federated ownership and delivery.Why organisations should assess their data maturity before accelerating AI ambitions.Why the strongest AI strategies are built on strong data foundations rather than stronger AI models.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. | 41m 17s | ||||||
| 7/21/26 | CIO vs CDOorganizational design+4 | Priya Enefer | Hakluyt & Company | — | CIOCDO+6 | — | 55m 16s | ||
| 7/14/26 | AI strategybusiness transformation+5 | Vin Vashishta | V-SquaredJPMorgan Chase+1 | — | AIbusiness outcomes+5 | — | 58m 52s | ||
| 7/9/26 | innovationleadership+3 | Peter Crouch | Lloyd's Banking Group | — | innovation functionsolving the right problem+3 | — | 37m 45s | ||
| 7/7/26 | innovation capabilityAI era+4 | Peter Crouch | Lloyds Banking Group | — | innovationAI+7 | — | 47m 00s | ||
| 7/2/26 | customer datagrowth engine+4 | Diana Comsa | Condé Nast | — | customer datagrowth engine+5 | — | 39m 04s | ||
| 6/30/26 | customer databusiness growth+4 | Diana Comsa | Conde Nast | — | customer databusiness value+5 | — | 52m 32s | ||
| 6/25/26 | AI adoptiondata management+4 | Justin Borgman | Starburst | — | AIdata+5 | — | 48m 30s | ||
| 6/23/26 | enterprise AIdata architecture+5 | Justin Borgman | Starburst | — | AI successdata estates+8 | — | 50m 18s | ||
| 6/18/26 | data leadershipstakeholder trust+3 | David Krauza | Comcast | — | data strategystakeholder trust+3 | — | 42m 00s | ||
| 6/16/26 | data strategyAI implementation+4 | David Krauza | Comcast | — | data strategyAI+5 | — | 51m 47s | ||
| 6/11/26 | data leadershipcommercial thinking+4 | Sarah Emerson | Howden | — | dataAI+6 | — | 42m 49s | ||
| 6/9/26 | commercial thinkingbusiness partnering+4 | Sarah Emerson | Howden | — | data leadershipbusiness strategy+4 | — | 47m 39s | ||
| 6/4/26 | data leadershipstakeholder management+3 | Keith Moody | Driven by Data: The PodcastOrbition Group | — | data leadershipstakeholder management+5 | — | 48m 37s | ||
| 6/2/26 | data teamscommercial impact+5 | Keith Moody | Orbition Group | — | data analyticsCDAO+5 | — | 53m 25s | ||
| 5/28/26 | leadershipdata+4 | Nirali Patel | Driven by Data: The PodcastOrbition Group | — | executive journeyleadership+5 | — | 39m 09s | ||
| 5/26/26 | NED rolescareer trajectories+3 | JoAnn StonierLara Izlan+1 | MastercardITV+1 | — | NEDboard CV+3 | — | 1h 02m 20s | ||
| 5/21/26 | data leadershipcommercial impact+3 | Edward Chenard | — | — | data leadershipcommercial impact+5 | — | 30m 45s | ||
| 5/19/26 | data leadershipbusiness value+5 | Edward Chenard | GEBest Buy+4 | — | data leadershiprevenue generation+6 | — | 1h 02m 56s | ||
| 5/14/26 | data leadershipstorytelling+5 | Dru Patel | FA | — | data leadershipstorytelling+5 | — | 43m 12s | ||
| 5/12/26 | data leadershipembracing failure+4 | Dru Patel | The Football AssociationCabinet Office | Kenya | data leadershipfailure+5 | — | 57m 33s | ||
| 5/7/26 | data strategiesAI+4 | Richard Masters | Virgin Atlantic | — | dataAI+5 | — | 38m 44s | ||
| 5/5/26 | data decision-makingsignal over noise+4 | Richard Masters | Virgin Atlantic | — | datadecision support+6 | — | 48m 47s | ||
| 4/30/26 | data leadershipAI market+4 | Peter Everill | Orbition Group | — | data leadershipAI+5 | — | 37m 29s | ||
| 4/28/26 | data transformationAI capabilities+3 | Peter Everill | IAG Loyalty | — | data transformationAI+3 | — | 53m 04s | ||
| 4/23/26 | Trad AIGenerative AI+5 | Daragh Kelly | The Economist | — | Trad AIGenerative AI+5 | — | 31m 57s | ||
| 4/21/26 | AI initiativesdata governance+4 | Daragh Kelly | The Economist | — | AIdata governance+7 | — | 45m 54s | ||
| 4/16/26 | CDO roleAI ownership+4 | Kinnari Ladha | Travelodge | — | CDOAI+5 | — | 36m 35s | ||
| 4/14/26 | CDAO role evolutiondata leadership+4 | Barry Panayi | HowdenThe AI of the Beholder | — | CDAOdata leadership+5 | — | 58m 14s | ||
| 4/9/26 | ROI accelerationAI adoption+5 | Kevin Cassar | Driven By DataAI | — | dataAI+8 | — | 32m 30s | ||
| 4/7/26 | value deliverydata strategy+4 | Kevin Cassar | TalkTalk | — | speed to valuedata governance+5 | — | 44m 40s | ||
| 3/31/26 | data dilemmaspodcast recap+3 | Kyle Winterbottom | Orbition Group | — | Driven by Datapodcast+5 | — | 30m 35s | ||
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Chart history for Driven by Data: The Podcast
Peaked at #40 in IS, currently #40 in IS.
| Market | Genre | Peak | Current | Trend |
|---|---|---|---|---|
| IS | — | #40 | #40 | — |
| New Zealand | — | #46 | #46 | — |
| South Africa | — | #66 | #66 | — |
| CH | — | #72 | #72 | — |
| Mexico | — | #83 | #83 | — |
| AE | — | #89 | #89 | — |
| United Kingdom | — | #92 | #92 | — |
| CZ | — | #105 | #105 | — |
| PH | — | #109 | #109 | — |
| Netherlands | — | #132 | #132 | — |
| SG | — | #161 | #161 | — |
| Finland | — | #166 | #166 | — |
| Denmark | — | #169 | #169 | — |
| PT | — | #183 | #183 | — |
Chart Positions
14 placements across 14 markets.
Chart Positions
14 placements across 14 markets.