This project is intended to determine a proof of concept foundation for the use of an AI Large Language Model tool (‘RegNav’) to minimise the density of regulatory review and response by reducing the time required to metabolise and disseminate new regulatory proposals. The current process is entirely manual and this project will help us understand if AI LLM (Large Language Model) tools can be used to improve the associated times and costs through the introduction of automation usage and generation of long format responses, sometimes referred to as reflection.

This tool will assess published regulatory changes in the form of consultations, calls for input, calls for evidence, and create prospective responses, and incorporate a feedback loop to improve responses over time. The tool is aimed to help minimise the density of regulatory early-stage response by reducing the time required to consume new regulation and quickly understand its impact.

Benefits

This project will help improve the efficiency and effectiveness of regulatory processes, ensuring that NESO can respond to regulatory changes with faster, more precise, more targeted and scalable outcomes. The tool this project will provide test will help to develop a repository of knowledge and ‘information memory’ from business areas across NESO. In addition, the tool will be able to generate the information concisely and provide efficient summaries of complex consultation documents.

With digitalisation being pivotal, we will be working more closely towards NESO’s strategic priority to develop a digital mindset to unlock the potential of technology and teamwork. This also fits in with NESO’s four key values: to accelerate progress, be curious, build trust and create belonging.