Growing the UK’s AI assurance market in defence and security
File(s)
Published version
Author(s)
Karner, Natasha
Knack, Anna
Shute, Rupert
Carolyn, Ashurst
Type
Report
Abstract
Executive Summary
This CETaS Briefing Paper provides an evidence-based analysis of the UK’s AI assurance market for Defence and National Security (D&S). A thriving AI assurance sector could enable AI adoption and become a key
driver of UK economic growth. If organisations are confident that AI harms can be mitigated, this will help the UK Government achieve its aim of “fast, wide and safe” adoption of AI1 and prevent AI capabilities from failing at the implementation stage. Effective assurance
processes allow for the rapid integration of AI into existing business structures and processes, which can contribute to economic growth across multiple sectors. However, a range of factors currently limit both the supply of and demand for AI assurance services.
1 HM Government, AI Opportunities Action Plan (Department for Science, Innovation and Technology: January 2025).
This Briefing Paper describes the current state of AI
assurance in national security, defence and policing
organisations, highlighting its strengths, challenges and
possible mitigations. Drawing on this, the paper identifies lessons from D&S to support the growth of a robust AI assurance market for other sectors and advance AI innovation across the UK economy.
Key findings from this study are as follows:
• D&S is a diverse sector in AI assurance maturity, as it
includes both early adopters and organisations at the
start of their AI assurance journeys. This is due to a range of factors that vary across the sector, including:
level of AI adoption; technical skills; infrastructure and
testing capabilities; risk appetite; preference for inhouse
or external offerings; and level of engagement
with external providers of AI assurance.
• Demand for AI assurance in D&S is driven by a desire
to secure strategic and operational advantage from
effective AI, the risk of high-consequence errors, policy requirements, and a need to assess AI providers’ claims. Demand for third-party assurance is driven by skills shortages in government organisations, a lack of resources, a desire for independent testing and
potential price advantages.
• Supply of AI assurance in D&S is limited by information
asymmetries, skills gaps, unclear regulatory guidance
and a lack of long-term funding. Demand for AI
assurance in D&S is constrained by confusion over
assurance offerings, information-sharing barriers,
cultural barriers, a lack of funding and slow procurement
processes.
• D&S provides a case study with broader lessons for
the UK as it works to bolster its AI assurance market.
This includes the need to: articulate sector-specific
requirements; cultivate a market that caters for different
levels of AI assurance maturity; develop initiatives
to upskill key stakeholders; create mechanisms to
disseminate best practice; and establish certification
schemes for AI assurance providers.
This CETaS Briefing Paper provides an evidence-based analysis of the UK’s AI assurance market for Defence and National Security (D&S). A thriving AI assurance sector could enable AI adoption and become a key
driver of UK economic growth. If organisations are confident that AI harms can be mitigated, this will help the UK Government achieve its aim of “fast, wide and safe” adoption of AI1 and prevent AI capabilities from failing at the implementation stage. Effective assurance
processes allow for the rapid integration of AI into existing business structures and processes, which can contribute to economic growth across multiple sectors. However, a range of factors currently limit both the supply of and demand for AI assurance services.
1 HM Government, AI Opportunities Action Plan (Department for Science, Innovation and Technology: January 2025).
This Briefing Paper describes the current state of AI
assurance in national security, defence and policing
organisations, highlighting its strengths, challenges and
possible mitigations. Drawing on this, the paper identifies lessons from D&S to support the growth of a robust AI assurance market for other sectors and advance AI innovation across the UK economy.
Key findings from this study are as follows:
• D&S is a diverse sector in AI assurance maturity, as it
includes both early adopters and organisations at the
start of their AI assurance journeys. This is due to a range of factors that vary across the sector, including:
level of AI adoption; technical skills; infrastructure and
testing capabilities; risk appetite; preference for inhouse
or external offerings; and level of engagement
with external providers of AI assurance.
• Demand for AI assurance in D&S is driven by a desire
to secure strategic and operational advantage from
effective AI, the risk of high-consequence errors, policy requirements, and a need to assess AI providers’ claims. Demand for third-party assurance is driven by skills shortages in government organisations, a lack of resources, a desire for independent testing and
potential price advantages.
• Supply of AI assurance in D&S is limited by information
asymmetries, skills gaps, unclear regulatory guidance
and a lack of long-term funding. Demand for AI
assurance in D&S is constrained by confusion over
assurance offerings, information-sharing barriers,
cultural barriers, a lack of funding and slow procurement
processes.
• D&S provides a case study with broader lessons for
the UK as it works to bolster its AI assurance market.
This includes the need to: articulate sector-specific
requirements; cultivate a market that caters for different
levels of AI assurance maturity; develop initiatives
to upskill key stakeholders; create mechanisms to
disseminate best practice; and establish certification
schemes for AI assurance providers.
Date Issued
2026-01-26
Citation
Centre for Emerging Technology and Security (CETaS) Briefing Papers, 2026, pp.1-20
Publisher
Imperial College London
Start Page
1
End Page
20
Journal / Book Title
Centre for Emerging Technology and Security (CETaS) Briefing Papers
Copyright Statement
© 2026 The Author(s). This work is licensed under the terms of the Creative Commons Attribution License 4.0 which permits unrestricted use, provided the original author and source are credited. The license is available at: https:// creativecommons.org/licenses/by-nc-sa/4.0/
Subjects
AI Security
centre for sectoral economic performance
defence
report
security
Place of Publication
London, United Kingdom
Publication Status
Published online
Article Number
1