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Patel, Preeti, Dey, Maitreyee and Simmons, Clarke, V. (2026) Response to the GOV.UK Call for Evidence: data regulation in the age of AI and other data intensive technologies. Department for Science, Innovation and Technology, GOV.UK. (Submitted)
This submission presents evidence from the GENESIS Research Programme, a sustained body of research undertaken by the GENESIS Research Lab investigating the application of AI, data engineering and operational data management within modern electricity distribution networks. Drawing on eleven peer-reviewed publications, the programme examines how continuously generated operational data can be acquired, managed, analysed and governed to support reliable AI-enabled decision-making within critical infrastructure.
Although situated within the electricity sector, the findings have wider relevance across transport, manufacturing, telecommunications, healthcare and other operational environments where AI increasingly relies upon continuously generated operational data rather than static research datasets. Collectively, the research demonstrates that trustworthy AI depends not only on advances in analytical methods but equally on the availability, quality and governance of the underlying data. Future approaches to AI regulation should therefore consider the complete operational data lifecycle, recognising that operational data are continuously acquired, validated, transformed, shared and reused before becoming suitable for AI-enabled decision-making.
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