Insights from our latest research
Research conducted for the London Market Claims conference highlights both the opportunities and the challenges of adopting AI and automation in a sector defined by complexity, tradition and global responsibility. While there is broad enthusiasm for modernisation, progress depends on establishing strong foundations in data quality, governance and standardisation.
A key finding is the continued importance of Blueprint Two. Despite delays, its focus on standardising messages across claims and settlement, and improving connectivity between systems and trading partners, remains fundamental. Without these foundations, automation cannot deliver at scale. Previous market-wide initiatives, such as the adoption of ECF Write Back, provide evidence that collective action can drive meaningful change.
AI for the London market claims environment
The research also underlines the unique characteristics of claims in the London market. These often involve prolonged lifecycles, multiple handlers and vast amounts of unstructured data ranging from adjuster reports to part payments. Straight-through processing, common in retail markets, is not feasible in this context. Instead, AI and automation should be viewed as enablers of human expertise. Automation can streamline reserving and workflows up to the point where human judgment is required, while AI has the potential to interrogate large volumes of documentation and support decision-making by suggesting next steps.
Clear strategy and cultural alignment
Intentionality emerged as a consistent theme. AI adoption is costly, and fragmented experimentation across multiple vendors risks wasted effort. Organisations must be deliberate, identifying specific use cases, prioritising investment, and ensuring alignment with broader strategy. Data quality, ingestion accuracy and governance are essential foundations, as is the ability to trace decision-making for regulatory purposes. In addition, early engagement with legal and compliance teams is vital.
Case studies show that progress is possible when cultural challenges are addressed. Involving claims handlers in the design and training of automated systems has proven effective in building trust and reducing resistance. By relieving staff of administrative burden, automation allows professionals to dedicate more time to client engagement and higher-value tasks. Crucially, much of the data generated within claims serves other functions such as underwriting and risk management, making cross-departmental collaboration and shared investment essential.
Challenges
Concerns remain over issues such as job security, accountability and the potential for AI hallucinations. However, the prevailing view is that AI should augment professionals rather than replace them. Productivity tools are already familiarising staff with AI, paving the way for more advanced applications that enhance the customer journey and, in time, reshape business models.
The research concludes that AI and automation are not optional but must be implemented deliberately, with data as the foundation and human expertise at the centre. The London market’s defining strength lies in its ability to manage complex risks, and technology should be deployed to reinforce this advantage rather than replicate retail models.
Key takeaways
Intentional adoption is essential
AI and automation require significant investment, and unfocused experimentation risks wasting resources. Organisations must clearly define use cases, ensure alignment with business strategy, and approach adoption with deliberate intent.
Data quality and governance underpin success
Standardisation, consistent data ingestion, cleansing and strong governance are prerequisites for automation. Without reliable data, AI cannot scale or deliver meaningful outcomes, and regulatory traceability requirements cannot be met.
Technology should augment, not replace, expertise
Large and complex claims demand human judgment. AI and automation can relieve handlers of repetitive tasks, interrogate documentation, and provide decision support, allowing professionals to focus on value creation and client relationships rather than administrative work.
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