AI & Machine Learning

With fewer adjusters entering the field and claims growing more complex, AI offers capacity without replacing the human judgment insurers need most.

We're suddenly having a debate about whether AI is about to kill us all, and it obscures some pressing issues.

Directors face mounting fiduciary pressure as board packs balloon while preparation time shrinks, creating a governance crisis few acknowledge.

AI-generated claim summaries gain investigator trust only when findings trace back to original evidence and survive expert scrutiny.

Digital musculoskeletal care has proven its market value, but the next frontier is using AI to measure functional decline before it becomes disability.

Converged platforms can unify underwriting, claims and policy data in real time, letting AI act on complete context rather than fragmented systems.

Insurers' self-assessed AI risk ratings determine regulatory scrutiny, but rating customer-facing models too low leaves coverage errors undetected until claims arrive.

Asian insurers show that agentic AI success requires reimagining market forces, not just chasing productivity gains through isolated use cases.