AI & Machine Learning

As AI reshapes decision-making in insurance, the industry faces a critical question: Who holds liability when algorithms influence consequential outcomes?

New transparency laws mandate AI content marking by Aug. 2 -- but don't ensure end users see those marks.

...It has a design problem. Insurers risk wasting AI investments by prioritizing technology over understanding the workflows and needs of the people using it.

Agentic AI's true value in insurance lies not in speed alone, but in decision velocity with built-in governance and accountability.

Insurers experimenting with AI agents face an automation ceiling, with only 11% of projects reaching production because of trust and control concerns.

AI-powered pre-insurance photo inspections eliminate costly FNOL disputes by creating verified, timestamped vehicle condition records before coverage begins.

Most professionals spend more time gathering data than making decisions, making pre-decision AI deployment the smarter strategic move.

Here are five of the most common reasons AI breaks and doesn't scale... and what to do about them.