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.

In this episode of the Databricks Diaries, Andy is joined by Rina Lakhman Interim Director of Digital at the University of Manchester, for a deep dive into AI readiness. Rina brings her extensive experience across legal, telecommunications, and academia to discuss the practical application of AI in large organisations.

The conversation explores the critical balance between agentic AI for personal productivity and the large-scale AI models shaping institutional strategy. Rina and Andy discuss the often-overlooked costs of AI - both financial and environmental and why traditional data engineering remains a vital foundation. From the European AI Act to the nuances of model hallucinations, Rina shares her perspective on building a culture of governance and enablement. Whether you're navigating digital transformation or curious about the ethics of AI, this episode offers essential takeaways for the modern digital landscape.

In this episode of Databricks Diaries, Dave Williams, Head of Data Engineering at National Grid, shares a grounded and practical perspective on what it really takes to unlock AI value in a critical infrastructure organisation. Drawing on lessons from past data and AI hype cycles, Dave explains why AI is an amplifier, not a silver bullet, and why strong foundations in people, process, technology, and especially data are non-negotiable.

We explore how National Grid has embedded governance and responsible AI as enablers rather than blockers, including the creation of a Chief Data Office, a Responsible AI program, and a dedicated AI Value Office to ensure initiatives are driven by measurable business impact. Dave also discusses the evolving role of data engineers, shifting from purely technical delivery toward deeper business engagement and product thinking.

From fixing data quality and ownership issues to selecting AI use cases that matter, this episode is a must-listen for leaders and practitioners focused on sustainable, value-driven AI readiness—beyond the hype and into lasting transformation.