Beyond confidence: closing the gap between AI ambition and data foundations

With the Treasury Committee, FCA and Bank of England sharpening their focus on AI, the onus is on insurers to show how and why they've made AI-driven decisions. Based on this snapshot survey, there's still real work to do. 

While perceptions of AI governance are strong, daunting questions remain about data quality. The technlogy is there, but the biggest issue is leadership and cultural resistance. And therein lies the opportunity. 

Great governance and poor data quality can co-exist. 

71% of insurance leaders rate their data governance as advanced or leading, and being compliant brings a sense of safety. But 48% name lineage and auditability as their single biggest data challenge. With regulation changing all the time, a wait-and-see approach is dangerous. Poor data acts like quicksand for AI innovation, especially at scale. 

Data foundations are now a genuine business case. 

Insurance leaders have long wrestled with data foundations and legacy systems. 86% still run legacy in their core stack, and IT has struggled to prove the impact on the bottom line. With regulatory scrutiny now a question of when, not if, first movers can use AI to tackle age-old data issues while modernising incrementally. That frees them to focus on transformation while others scramble to catch up. 

The biggest barrier is people 

Leadership and cultural resistance is the top barrier to scaling AI (39%), ahead of regulatory uncertainty and legacy integration. Firms that frame data modernisation in business terms and bring leaders along early can turn AI from an IT initiative into a shared priority. They'll also be better placed when regulators come asking. 

 Inside the report: