DSIT Publishes Call For Evidence On Data Regulation In The Age Of AI And Other Data-intensive Technologies

On July 15, 2026, the UK Department for Science, Innovation and Technology (DSIT) published a call for evidence seeking practical examples of how personal and non-personal data regulation interacts with AI and other data-intensive technologies (such as distributed databases and stream processing technologies) and insights in relation to how technological progress may change how data is used in the economy (the AI Call for Evidence). The AI Call for Evidence is open until September 9, 2026.

DSIT is interested in understanding how legal, technical, and governance frameworks can better support data use and re-use, and in identifying friction between regulatory requirements and operational practice. DSIT seeks evidence from organizations and individuals with practical experience of AI or data-intensive technologies, as well as researchers, civil society groups and academics.

The AI Call for Evidence is structured around five themes: 

• Accessing and using data, including how organizations access, prepare and use personal and non-personal data in practice, how lawful bases are selected and evidenced, how purpose limitation and data minimization are applied in large-scale or complex datasets and how permissions and licensing terms shape data use and re-use. 
• Data quality, accuracy, and downstream impacts, including how organizations assess and manage data quality and accuracy at different processing stages, how fairness and impacts on individuals are considered from the outset and how they monitor and address impacts arising from AI model outputs or downstream uses. 
• Governing data use across organizations, including how legal roles and responsibilities are allocated across complex and often global supply chains, how accountability is maintained through governance or oversight mechanisms and how organizations approach automated decision-making and meaningful human involvement.
• Transparency and rights in complex data environments, including how organizations provide transparency where personal data is used at scale or collected indirectly, how they enable individuals to exercise data subject rights such as access and erasure and how data flows across organizations affect transparency.
• Effectiveness of data frameworks in regulating AI, including whether existing data protection principles and data rights offer meaningful protection in practice, whether frameworks are sufficiently adaptable to future developments such as agentic AI and whether alternative approaches may be better suited to address certain risks.
• The government intends to use the evidence to assess whether it needs to issue further guidance, make targeted changes or more fundamental reform to keep regulatory frameworks fit for the technological age, balancing societal expectations around data use with the promotion of innovation and growth. 

For further information, please see the AI Call for Evidence.