How to Transform Insurance Operations in 2026Through Context-Driven GenAI Innovation

What You’ll Learn

• The biggest challenge for insurance AI adoption is complexity: fragmented data systems, intricate policies, and heavily regulated processes that don’t communicate with each other.
• Most insurance organizations have found early success with decision support tools, underwriting assistance, and predictive risk assessment, but scaling beyond pilots remains the core challenge.
• Scaling generative AI to handle complex, multi-system insurance workflows breaks down without a context layer, leading to inconsistent outcomes, high error rates, and limited automation potential.
• Competitive advantage in insurance will be unlocked by organizations that properly model, prepare, and contextualize their data so that AI agents can truly understand, reason over, and act on it.

See what an agentic workforce could look like for your insurance operations.

Understand what context-driven agentic AI looks like in real-world insurance deployments, why deterministic and auditable outcomes are critical to success, and hear key takeaways on where agentic AI is delivering measurable impact in insurance today, from claims adjudication to complex coverage determinations.