Artificial intelligence (AI) is rapidly reshaping UK fund management. Firms are achieving general productivity gains as they deploy AI across investment research, portfolio optimisation, risk analytics, compliance monitoring, and client communications. What was once experimental is quickly becoming embedded in critical operations. As adoption accelerates, operational leaders are asking an increasingly practical question:
Do traditional insurance policies adequately cover AI-driven risks, or do UK fund managers now need specific insurance cover for AI risk?
The answer is becoming clearer. While AI adoption is delivering measurable value, it is also introducing new and unfamiliar risks that many existing insurance policies were never designed to absorb. As a result, coverage gaps are emerging, often unnoticed until a claim arises.
4 key areas where traditional insurance may fall short
1. Professional indemnity (PI) and errors & omissions (E&O)
AI-driven investment models and decision-support tools can fail in ways that are difficult to predict or explain. Data bias, model drift, flawed assumptions or unexpected correlations may result in investment underperformance or client losses.
Traditional PI and E&O policies typically assume human-led decision-making. Where losses stem from opaque AI systems, insurers may challenge whether a claim falls within scope, particularly if AI use was not explicitly disclosed, appropriately documented, or subject to robust governance.
2. Cyber risk
AI is reshaping the cyber threat landscape. UK fund managers are increasingly exposed to AI-enabled attacks, including deepfake impersonation, automated phishing, and synthetic identity fraud.
While cyber insurance will often continue to respond, many insurers now require affirmative AI wording or specific endorsements to confirm coverage. Firms without robust AI governance, security controls, and ongoing monitoring may face exclusions or higher premiums.
3. Management liability (D&O)
AI introduces new governance challenges for boards and senior management. Claims may arise where AI capabilities are overstated, risks are poorly controlled, or automated AI-driven decisions are insufficiently supervised.
From an insurance perspective, undisclosed or weakly governed use of AI may undermine D&O cover, particularly where insurers argue that directors failed to meet their regulatory duties.
4. Regulatory fines and investigations
AI-related failures may also trigger regulatory scrutiny. Breaches of FCA expectations around systems and controls, data governance, or operational resilience can result in enforcement action, remediation costs and financial penalties.
Insurers are increasingly restricting coverage for regulatory investigations or fines linked to AI-related failures, unless firms can demonstrate robust governance through documentation and clearly defined accountability frameworks.
How is the insurance market responding? The emergence of AI-specific insurance solutions
In response to these challenges, insurers are beginning to offer AI-specific liability cover. UK insurers and Lloyd’s market participants are introducing policies that explicitly address risks such as model failure, data drift, bias and negligent AI-driven advice.
These solutions are still evolving, but they send a clear market signal: insurers expect AI risk to be explicit, well governed and carefully priced, rather than absorbed within legacy policies.
Regulatory context: Why are governance and insurance converging? FCA principles-based oversight
The FCA continues to apply a principles-based approach to AI. For fund managers, this means ensuring AI systems are safe, explainable, fair and subject to appropriate human oversight.
Under the rulebook, firms must demonstrate control, accountability and auditability, particularly where AI influences investment decisions or client outcomes. Increasingly, insurers are using these same principles as benchmarks for underwriting.
So, do UK fund managers need specific insurance cover for AI risk?
For many firms, the answer is increasingly “yes,” if not soon. AI risks are no longer theoretical, and insurers are no longer assuming they fall neatly within traditional policy wording. Fund managers who rely on AI without explicitly addressing insurance implications may find themselves exposed to coverage gaps, exclusions, or escalating premiums.
