Callum Stayton

Thames Estuary 2100 (TE2100) is a 100-year climate adaptation programme protecting 1.4 million people and 275 billion pounds of infrastructure from tidal flood risk. Despite its scale, the programme had no agreed data management strategy. Data was hard to find, inconsistently stored, duplicated, and often not trusted, creating operational risk in a safety critical environment. This session is a case study of moving from fragmented data to a structured, AI informed data strategy. We interviewed 90 stakeholders across 36 groups and analysed 91,000+ sentences of feedback using AI and NLP, identifying recurring themes at scale. We also ran a data maturity assessment aligned to the Institute of Asset Management framework to understand strengths, gaps, and priorities. Rather than defaulting to new technology, we defined five objectives covering governance, data quality, interoperability, retention, and culture, translated into an 85 action roadmap. This talk shows how AI enabled insight can transform data management in complex programmes. Key Takeaways How to use AI and NLP to convert stakeholder feedback into strategy insights. How to structure a maturity assessment and turn it into a roadmap. Practical approaches for embedding governance and resilience into infrastructure programmes.