AI & Machine Learning

Healthcare faces a critical choice: responsibly embrace AI to enable proactive, personalized care or risk system collapse under mounting costs and workforce strain.

Companies rushing to deploy generative AI must assess 12 critical factors across suitability, risk, operations and transformation before implementation.

Commercial insurers face a strategic challenge: identifying which submissions merit scarce underwriting attention, not just processing more faster.

AI in claims is no longer about what the technology can do but what insurers should let it do autonomously.

AI agents optimizing for bind rates may exploit underwriting systems the same way OpenAI's test agents hacked shared infrastructure.

Claims adjusters report the highest AI dissatisfaction rates across all occupations, but poor implementation—not the technology—is to blame.

AI pilots prove capability, but production adoption hinges on workflow integration, data relevance and user trust at scale.

As AI masters producing realistic images and expert-level outputs, imitation doesn't mean it understands cause-and-effect.