The Databricks Diaries

In this episode of The Databricks Diaries: AI Readiness Series, Andy Davis speaks with Mukund Pandey, Director of Data Engineering & AI within the Investment Bank at UBS. Mukund shares how UBS is approaching AI readiness across mindset, people, and data—shifting AI from “experimental” to a trusted business enabler. The discussion covers the role of governance as an accelerator, embedding compliance and explainability from day one, and how cultural alignment drives adoption at scale. Mukund also highlights practical AI use cases in risk and margin management, intraday exposure, and generative AI for regulatory efficiency. A candid look at how one of the world’s leading investment banks is building AI you can trust.

AI's here – but are we actually ready? In this episode, I chat with Merve Alanyali, Head of Data Science at AXA UK, about what real AI readiness looks like.

We unpack why solid infrastructure matters (don’t build on a swamp), the myth of “quick wins”, and how to bring your people with you on the journey. We also dive into how AI will reshape the way we learn, work, and grow – and what that means for the next generation of data professionals.

Andy Davis speaks with McKinley Hayden, Director of Data Value & Strategy at the Financial Times, about making AI readiness real in a newsroom where trust matters; they unpack the FT’s AI policy and organisation-wide fluency programme, a cross-functional transformation model and impact framework, and practical wins such as AskFT (built with Anthropic) and smarter comment moderation—alongside clear-eyed advice on avoiding hype, measuring value beyond “time saved”, and why governance and ethics must be owned in-house.

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In this episode, Andy Davis talks with Chris Bick, Head of Data Product at Equiniti, about what it really takes to get an organisation ready for AI. They discuss why AI success starts with trusted, well-structured data, the cultural shift from tech-led to demand-led adoption, and how to balance governance with enablement. Chris shares practical use cases, from automating admin tasks to real-time fraud detection, and explains why “fleshware” – people and mindset – is the biggest factor in AI transformation.

In this episode, Andy Davis is joined by Elettra Damaggio, Director of Internal Data Science at Visa, to discuss what AI readiness really looks like from the inside. Elettra shares sharp insights on the pressures data teams face, the operational realities of deploying LLMs, and why clean data is still the unsolved challenge behind the AI hype.

They explore how internal AI use cases—like querying and explaining data—can transform operations, but only when the foundational layers are mature. From MLOps to the myth of quick wins, this is a transparent look at where businesses really are on their AI journey.

If you're grappling with where to start or how to scale, Elettra's practical and grounded advice is essential listening.

In Episode 13 of our AI Readiness series, Andy Davis is joined by Alex Blyth, Head of Data at NEST (National Employment Savings Trust), for a candid conversation on what it really takes to prepare an organisation for AI.

They discuss why cultural readiness matters more than technical capability, how tools like CoPilot are helping drive practical adoption, and the risks of applying AI to the wrong problems. Alex shares his philosophy on removing unskilled tasks to unlock real value, the importance of strong data governance, and why transformation should always be approached step by step.

This episode offers a grounded, inside view of AI adoption in the public sector — full of lessons for any organisation thinking about how to turn hype into impact.

In this episode, we speak with Dizem Ozalp Sari Director & Head of Data Services Domain at bnp Paribas bout the real work behind AI readiness in the financial services sector. With years of experience driving data strategy across global institutions, Dizam shares candid insights on:

• Why mindset and culture matter more than tech
• The growing disconnect between consumer and corporate AI experiences
• What makes a use case truly scalable (and why many won’t survive)
• The critical role of leadership sanity in avoiding AI hype cycles
• Opportunities in synthetic data, data lineage, and knowledge retrieval
• Why product thinking is still the most important tool in your AI toolkit

This is a thoughtful and grounded conversation for anyone navigating AI strategy, transformation, or delivery at scale.

In this episode, Andy Davis is joined by Andy McMahon, Principal Engineer for AI & MLOps at Barclays, to unpack what AI transformation really takes inside large organisations.

They dig into the realities behind the GenAI hype, including the tough conversations around data readiness, process redesign, and the cultural ingredients needed to deliver value at scale. From proof-of-value pitfalls to bridging the POC-to-production “chasm,” this is a brutally honest take on why most AI efforts stall — and how to avoid the same fate.

Whether you're leading technical teams or shaping data strategy, this conversation is full of hard-won lessons from the frontline of enterprise AI.

In this episode, we’re joined by Jane Smith, Field Chief Data and AI Officer at ThoughtSpot, to explore what “AI readiness” really means in practice. Jane shares her perspective on how organisations can move beyond the buzzwords and actually embed AI into how they work, starting with stronger data culture, leadership buy-in, and better alignment between strategy and delivery.

We talk about practical use cases, what’s blocking adoption, and how data teams can avoid the classic traps that stall transformation efforts.

If you're thinking seriously about scaling AI beyond the lab, this one’s worth a listen.

In Episode 09 of the AI Readiness series, Andy Davis is joined by Brian Harkin, Ian Balfour-Church, and George Roffey from Centrus – a financial advisory firm with a strong focus on infrastructure, housing, and sustainability.

Together, they explore:

• Why AI isn’t a silver bullet — and how Centrus is using it as a force multiplier
• How to strike the right balance between innovation, regulation, and lightweight governance
• Why early wins and internal storytelling are critical to adoption
• The tension between efficiency gains and environmental impact in AI adoption
• Real-world examples of AI helping advisory teams focus less on processing, more on delivering insight

Whether you're leading data strategy or just navigating AI's impact in a complex industry — this episode is packed with lessons on culture, mindset, and tangible value.

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