The State of AI in Insurance: Why Most Agencies Aren't Adopting (Yet) — and What to Do About It

Presented by 1Fort AI

Artificial intelligence is everywhere — but inside most insurance agencies, it's still in the early innings.

Catalyit Premium Solution Provider, 1Fort AI, has worked alongside hundreds of agencies and surveyed many more to understand how AI is actually being used today — and why adoption is lagging.

The takeaway: AI has not yet become part of the core operating system of most agencies.

Where AI Stands Today

From 1Fort AI recent survey of 300+ agents:

• 71% are not using AI at all
• Among the 29% who are:
• 53% use it for paperwork and workflows
• 22% for comparing quotes
• 17% for marketing
• 8% for client communication

A closer look reveals something more telling. AI adoption today is fragmented, back-office focused, and non-core. Agencies are experimenting around the edges — drafting an email here, summarizing a document there — but very few have rethought how AI fits into the heart of their business: submissions, quoting, binding, and servicing.

The Real Barriers to Adoption

Three themes came up repeatedly among the 70%+ not using AI:

"We don't know where to start." This was the most common response. There's no clear AI playbook for agencies — no guidance on what workflows to start with, what good adoption looks like, or what to change vs. leave alone.

Data security and compliance concerns. Insurance runs on trust. Agencies handle sensitive client and carrier data every day, and without clear standards, many default to not adopting. Not because they don't believe in AI, but because the downside risk feels higher than the unclear upside.

Cost and unclear ROI. Agents care about winning more deals, binding faster, and retaining clients. If AI doesn't clearly drive these outcomes, it stays stuck in pilot mode.

Most AI Isn't Built for Agents

Generic tools (ChatGPT, copilots) and horizontal SaaS add-ons weren't designed for agency operations, which are inbox-driven, document-heavy, carrier-fragmented, and time-sensitive. If agents have to leave their workflow to use a tool, that's not transformation. It's added friction.

What Early Adopters Are Getting Right

The 29% using AI share a pattern: they don't try to "AI everything." They focus on high-friction, repeatable workflows tied to revenue: extracting data from submissions, comparing quotes, generating proposals, cleaning applications. Not glamorous, but that's where time is actually spent. The result: faster turnaround, more submissions per team member, and fewer errors.

How to Start

Three principles to move from experimentation to real impact:

1. Start with revenue-adjacent workflows. Speed to quote, submission quality, client responsiveness. If it doesn't touch revenue, it won't stick.
2. Embed AI into existing workflows. Adoption only happens when behavior doesn't need to change much. Ask: does this live inside the tools my team already uses (e.g., email)?
3. Prioritize trust before scale. Understand how data is handled before rolling anything out. Many tools lack SOC 2 Type II, clear data policies, or real security ownership — making them hard to trust with sensitive data.

Where This Is Going

AI will shift from standalone tools to core infrastructure, from assistive to embedded, from back-office to revenue-driving. The agencies that win won't be the ones using the most tools. They'll be the ones who embed AI at the center of their workflows.

This isn't about replacing agents. It's about removing operational drag so they can focus on what matters: advising clients, winning business, and building relationships.

Curious to learn more? Schedule time with 1Fort AI to see how this can work for your agency.