In this episode of the Databricks Diaries, we sit down with Tim, the Head of Data Science at The Citation Group, to explore his journey from a PhD in statistics at Lancaster University to leading AI innovation in a private equity-backed firm. Tim discusses the transition from the massive R&D landscapes of companies like Shell to the resource-constrained environment of an SME, where he now balances experimental projects with the need for immediate returns.

Throughout the conversation, he provides a masterclass on scaling data functions, from the importance of building a "proper" foundation to avoid technical debt to his "fire starter" strategy for managing and retaining high-performing talent. We also dive into his team’s National AI Award-winning project on call-back prioritization, which utilizes LLMs and sentiment analysis to optimize sales efficiency, and the "AI Champion" scheme - an initiative empowering over 200 employees across the business to experiment with the latest generative AI tools.

This episode offers a grounded look at how to maintain a "scientific method" mindset while navigating the rapid release cycles of platforms like Databricks.

In this episode of the Databricks Diaries, Sunando Das, Global head of Predictive Analytics at Unilever shows how they approach AI readiness at scale, balancing proven predictive models with emerging generative AI to drive measurable business growth. Drawing from years of applied AI across demand forecasting, marketing, innovation, and investment efficiency, Sunando estimates AI's potential to unlock 2–3% incremental growth when applied with discipline and focus.

The conversation tackles one of the biggest challenges in AI today: why only around 5% of generative AI pilots make it into production. Sunando explains why closing this gap requires more than better models, it demands cultural change, shared ownership, and a clear expectation that experiments must convert into real business outcomes.

We explore how cross-functional collaboration between business experts and technical teams is essential, why AI must be treated as a shared business asset rather than a data team initiative, and how conversational interfaces and agent-based workflows are reshaping how organisations interact with data. From continuous upskilling to test-and-learn experimentation, this episode offers practical guidance for organisations looking to move beyond pilots and turn AI into sustained impact.

In this episode of the Databricks Diaries, Andy sits down with Nuno Faustino, Head of Data and Analytics at Credit Spring, to discuss the strategic reconstruction of a data function designed for the AI era. Drawing on his experience at global giants like AstraZeneca and Lloyds, Nuno provides a blueprint for building a future-proof architecture from the ground up, moving away from legacy constraints to a flexible, modular stack.

We dive deep into the technical building blocks of AI readiness, including the implementation of a lakehouse architecture and a medallion infrastructure to ensure data quality and governance. Nuno explains his pragmatic approach to open-source models and vector databases, sharing how his team developed in-house AI agents and RAG systems to interrogate company documentation and SQL databases in real-time.

The conversation also explores the human side of digital transformation, highlighting the importance of data literacy, the establishment of a "Community of Practice," and the use of internal champions to drive adoption across the business. This episode is a must-listen for leaders looking to balance technical robustness with the agility needed to deliver immediate value in a rapidly evolving landscape.

In this episode of the Databricks Diaries, we are joined by Seeta Halder, Head of Data Insights at Nottingham Building Society, to discuss the unglamorous but essential work of AI readiness. Seeta challenges the industry's rush toward AI by reminding us that "you can't be artificially intelligent if you're dumb with data".

This episode explores the "Foundation First" approach, detailing why Nottingham Building Society is prioritising a central data repository and high-quality data governance over immediate AI deployment. Seeta explains the cultural and technical shift required to stop departments from working in isolation and move toward a unified data community. We also dive into managing the "AI Nerve", discussing how to address organisational anxiety by positioning AI as a tool for professional evolution and empowerment rather than a replacement for human talent. Finally, Seeta shares how high-integrity data allows specialist lenders to move from reactive services to proactive customer support by truly understanding behavioural data.

Whether you are navigating legacy systems or building a modern data stack, Seeta’s insights provide a practical roadmap for achieving genuine AI maturity.

In this episode of The Databricks Diaries, Daniel Thornton sits down with Yann Cluchey, CTO at Corsearch, to explore what it really means to build an AI-first business.

Yann shares his journey from writing code and specialising in web technologies, databases, and distributed processing, to leading technology strategy at Corsearch, where the mission is to protect consumers and brands by fighting counterfeits, piracy, and trademark infringement at scale. It is a powerful example of technology being used with real-world purpose: as Yann puts it, writing code to fight crime.

The conversation dives into Corsearch’s transformation journey, including the challenges of fragmented systems created through years of growth and acquisition, and the thinking behind consolidating onto a more scalable, modern data platform with Databricks and AWS. Yann explains why simplicity, talent availability, community support, and long-term scalability all matter when choosing foundational technology.

Daniel and Yann also unpack some of the harder realities of AI adoption: migrating legacy pipelines, managing cost in pay-per-use platforms, building organisational readiness, and closing the gap between promising AI experiments and reliable production systems. Along the way, Yann shares practical lessons on MLOps, change management, platform design, and how businesses can create faster, more accurate, and more innovative data workflows.

If you’re a CTO, data leader, architect, or AI practitioner thinking about replatforming, AI readiness, or scaling data-driven products, this episode is full of practical insight.

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In this episode of The Databricks Diaries, Daniel Thornton sits down with Sami Alsindi to explore what it really takes to turn AI ambition into business value.

Sami brings a rare blend of scientific thinking, hands-on technical experience, and commercial perspective. With a background spanning neuroscience, data science, machine learning, generative AI, and AI leadership, he shares a grounded view of how organisations should think about AI in 2026, beyond the buzzwords.

The conversation dives into the evolution from data scientist to AI engineer, the rise of vibe coding, and why so many companies are still stuck in the world of pilots and proofs of concept. Sami explains why production thinking must start on day one, why the best early AI wins are often smaller and more practical than leaders expect, and why success comes from solving today’s real problems rather than chasing tomorrow’s hype.

Daniel and Sami also unpack what good AI ROI actually looks like, how leaders should think about augmentation rather than replacement, and how teams and roles may need to evolve as AI becomes more operational. Packed with real-world examples, hard-won lessons, and practical advice, this episode is a must-listen for anyone trying to make AI useful inside the enterprise.

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In this episode of the Databricks Diaries, we continue our AI Readiness series with Ali-Reza Moschtaghi, a veteran Chief Architect with a wealth of experience transforming IT landscapes for global organisations. Ali-Reza strips away the "silver bullet" hype surrounding artificial intelligence, arguing that the true value of AI is found not in isolated vertical solutions, but in a horizontal architectural view that prioritizes business outcomes over technology for technology’s sake. We dive into the "rubbish in, rubbish out" reality of legacy systems, discussing why automating existing complexity without first simplifying processes only creates complexity on complexity.

The conversation explores the critical pragmatic approach required for modern leadership-balancing the need for foundational "data hygiene" and integration with the pressure to deliver appealing front-end innovation. Ali-Reza shares his perspective on the cultural and human challenges of adoption, the diminishing cost of customer interaction, and how tools like Replet are revolutionising rapid prototyping for MVPs. This episode is a must-listen for technology leaders looking to future-proof their architecture by aligning it directly with core business strategy.

In this episode of the Databricks Diaries , Daniel Thornton sits down with Donal Simmie (Head of Data Science & AI at PEI) to unpack why many AI initiatives never reach production, and how leaders & teams stay motivated. They explore governance, prioritising use cases by value vs effort, creating stakeholder buy-in, celebrating “weekly wins”, and hiring curious, product-minded teams.