How AI Is Changing Executive Decision-Making In Insurance

In my previous article, I looked at how AI is finally solving insurance’s unstructured data problem – automating ingestion, connecting systems, and reducing manual work.

Once that data is flowing automatically, the next challenge emerges: How do we use it to make better decisions, especially at the executive level?

AI is giving us a way to do that more effectively, and more intuitively, than ever before.

The Return of the “Expert in the Middle”

Before the advent of PCs, if an executive needed a report, he or she would call down to the “nerds in the basement”: a team of experts that understood the tools, the systems, and how to pull everything together. 

But then came the PC era — Excel, dashboards, databases — and executives were expected to engage with data directly. Whether building reports themselves or leaning on analysts, the burden of insight shifted closer to the business side.

Agentic AI effectively puts the expert back in the middle, without the delays of the past. Not as a team of specialists in the basement, but as an intelligent system that understands your goal, navigates the data, and delivers relevant insight.

In insurance, this shift is especially powerful. It means decision-makers don’t need to be experts in tools or wait days for reports — they can simply ask questions and get answers.

With this evolution, we’re seeing a new role emerge for AI—not just as a data processor, but as a decision partner.

AI Agents as the Middle Layer

Advances in LLMs, document intelligence, and NLP have made it possible to process unstructured data at scale. But the real transformation is how these capabilities are now being operationalized.

Agentic AI wraps these models in autonomous agents that can interpret objectives, take action, and deliver business-relevant outputs.

These agents can:

• Query multiple systems
• Cross-reference internal and external data
• Return answers aligned with business goals

Agentic AI serves as a middle layer between humans and data—an intelligent system that understands goals, navigates information, and surfaces insights without manual stitching, dashboards, or technical queries.

A key enabler is Model Context Protocol (MCP) — essentially a 'yellow pages' for AI-aware tools. While still an emerging standard, MCP is gaining traction as a way for agents to dynamically discover and interact with systems, whether that’s a database, analytics dashboard, or even a PDF parser.

In insurance, where data lives across bordereaux files, submissions, claims platforms, and industry reports, this unlocks orchestration without months of IT lift.

Why This Matters in Insurance

Insurance is a math- and data-driven industry. Every decision — whether to expand into a new peril, allocate capital to a line of business, or exit wildfire-prone regions — depends on analytics.

But insight isn’t just about data. It’s about access.

Agentic AI reduces the friction between data and decisions. It enables executives to engage with their business context more directly — asking strategic questions to surface key insights, like:

• How do we deploy our limited capital for maximum return?
• Which regions or perils should we double down on?
• Where are we underpriced compared to market risk?
• What exposures are shifting faster than we realized?
• What trends are emerging across our portfolio?

These are strategic considerations that depend on fast, accurate, and contextual insight—something traditional BI tools struggle to deliver without a lot of engineering support. With agentic AI, you can simply ask the question in plain English and often get answers in seconds, far faster than traditional reporting cycles, without waiting for a report to be built or learning a query language.

The Future is Executive Intelligence

As this technology matures, the gap will widen between those who embrace AI as a strategic tool and those who fall behind.

Early adopters will gain a competitive edge by unlocking insights that were once gated behind systems, specialists, and slow reporting cycles. Agentic AI removes those barriers, giving decision-makers direct access to what matters.

At Brisc, we’re building toward that future — helping insurance leaders move faster, think clearer, and make better decisions with AI.

Book a demo to see what’s possible.