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.