AI & Machine Learning

A retirement wave and cyclical amnesia are erasing institutional memory that could prevent billions in repeated mistakes.

Instead of mass layoffs, companies must contemplate what to do with AI's new capacity by redirecting employees to focus on more meaningful tasks.

Technology for hiring delivers unprecedented speed, yet thousands of qualified candidates remain invisible in systems built for efficiency alone.

Insurance AI implementations fail not from poor models but from organizational gaps in infrastructure, governance, and operational readiness.

As insurance embraces AI, the architecture decisions behind deployment may matter more than the capabilities it delivers.

Agentic AI solutions are achieving 98% accuracy in claims evaluation while reducing processing timeframes from hours to minutes.

First Notice of Loss has evolved into insurance's most fraught moment for fraud, yet carriers treat it merely as administrative intake.

Federated data models offer insurers a pragmatic unification path that accepts fragmentation rather than fighting it.