New tried and tested guide for civil servants to use AI more effectively and responsibly.
Imagine facing a mountain of consultation responses with just days to analyse them before your minister’s briefing. Traditionally, this would mean late nights and hasty summaries. But what if you could process thousands of responses in hours rather than weeks while improving the quality of your analysis?
A new guide from the Bennett Institute for Public Policy addresses this challenge and dozens more faced by today’s civil servants. “Using Large Language Models responsibly in the civil service: a guide to implementation” bridges the critical gap between LLMs’ technological potential and practical, responsible implementation in government settings.
This policy resource is particularly valuable as departments across Whitehall are being charged with deploying AI technologies effectively – in light of the recent Artificial Intelligence Playbook for the UK Government and previous Generative AI Framework for HMG – but provides more detailed, practical guidance specifically for civil service contexts.
“UK civil servants face a potentially transformative moment with Large Language Models. These AI systems can enable efficiencies, including speeding up tasks such as evidence reviews and summarising many documents. The challenge is particularly acute given the pressure to improve efficiency in public service delivery while ensuring robust governance and maintaining public trust,” says the author of the guide, Dr Aleksei Turobov, Bennett Institute for Public Policy, who specialises in AI and geopolitics.
The practical value of this work lies in its balanced approach to opportunities and responsibilities for LLMs implementation. Rather than focusing solely on technical aspects, it connects LLM implementation to civil service values and accountability frameworks. The guide introduces a practical risk-based approach with four clearly defined usage levels, from foundational tasks to critical decisions, each with appropriate safeguards.
It is the result of Turobov talking to civil servants across multiple departments to find out where they need to use AI and how to do it. The consensus was for a practical guide that improves efficiency and productivity in analysis and decision-making.
A standout feature is the comprehensive framework (with a practical block-scheme) for implementation that integrates LLMs into existing civil service workflows through three interconnected layers:
- Established civil service processes (maintaining institutional standards)
- Governance requirements (embedding essential obligations)
- LLM implementation guidance (providing practical instruction)
The guide offers immediately applicable tools, from detailed prompt engineering techniques with examples designed explicitly for government contexts to risk management approaches:
“The effectiveness of LLM use largely depends on how we communicate with these systems. Understanding prompt engineering techniques enables civil servants to achieve consistent, reliable results.“
The guide addresses questions of security – it explicitly states that certain information should never be processed through public LLMs, including “materials classified SECRET” and “personal data requiring special protection.” This pragmatic approach to security categorises usage into three tiers – prohibited, restricted, and controlled – giving departments clear boundaries while enabling innovation where appropriate:
“The fundamental challenge stems from the architecture of public and corporate LLMs. These systems operate on infrastructure outside government control, with implications for data protection and information security.“
For departments just beginning their LLM journey, the step-by-step implementation roadmap emphasises starting small with specific challenges, like analysing consultation responses, where success can be easily measured:
“Start where you are, use what you have, and build on what you learn. Implementation isn’t about perfect execution – it’s about continuous improvement in service delivery.“
The guidance recommends establishing a Centre of Excellence approach to ensure consistent standards and knowledge sharing across departments. This would “centralise expertise and implementation guidance, systematise knowledge transfer, use a risk assessment approach and monitoring, and centralise the best-practice library and AI/LLMs risk register.“
The guide equips civil servants to meet the AI era’s challenges by providing theoretical understanding and practical implementation tools. Far from diminishing the civil service’s role, it highlights how human expertise remains paramount, with LLMs serving as analytical assistants that inform, not determine, decisions:
“Officials’ judgment remains paramount when using LLMs. Consider LLMs as analytical assistants that inform, not determine, decisions. Your professional judgment provides crucial context interpretation and ensures alignment with civil service values.”
As government departments face increasing pressure to deliver more with constrained resources, this guide offers a pathway to harness transformative technology while upholding the core values of integrity, accountability, and public service excellence.
The views and opinions expressed in this post are those of the author(s) and not necessarily those of the Bennett Institute for Public Policy.
