AI Agents, Governance Gaps, and the Future of Insurance Claims Decision-Making

The latest innovation report from the International Insurance Society frames artificial intelligence not as a quick fix for insurance inefficiencies, but as a catalyst for redefining how risk is identified, priced, and managed. For claims professionals, this distinction matters. Most AI adoption to date has focused on workflow automation, document handling, and cycle-time reduction. The report suggests those gains, while real, represent only incremental improvement if governance and decision authority remain unchanged.

Discussions held during an executive working group at the Swiss Re Centre for Global Dialogue underscored that insurers are reaching a strategic fork in the road. One path leads to marginal efficiency gains layered onto legacy claims systems. The other requires rebuilding operating models around structured data flows, proprietary knowledge graphs, and clearly defined human oversight. For claims teams, this translates into sharper risk selection, more consistent coverage determinations, and earlier loss prevention, but only if data quality and accountability are addressed first.

The report highlights a key tension adjusters already experience: experimentation with generative AI is widespread, yet few organizations have reached mature, production-level deployment. Claims handling sits at the center of this tension because errors, hallucinations, or biased outputs directly affect indemnity decisions, litigation exposure, and regulatory compliance. While most firms still rely on human review rather than formal AI governance frameworks, larger insurers are beginning to introduce audit trails, explainability standards, and ethics committees that could reshape claims authority structures.

Looking ahead, the rise of autonomous AI agents raises new concerns for claims operations. Validation of automated decisions, regulatory scrutiny, and accountability for errors remain unresolved. The IIS findings suggest that insurers able to balance innovation with disciplined governance will be better positioned to handle emerging risks such as cyber losses, climate-driven catastrophes, and complex liability claims. For adjusters, the takeaway is clear: AI will increasingly influence claims outcomes, but human judgment, transparency, and trust remain essential to defensible decisions.