AI for Insurance Agencies: 2026 Industry Report Summary

Table of Contents

• How Are Insurance Agents Using AI Today?
• What Do Agents Want AI to Do With Their Book of Business?
• Why Do Agents Want This Built Into Their AMS or CRM?
• What Does It Take to Earn AI Access to a Book of Business?
• Where Do Agents Expect AI to Make the Biggest Difference Next?
• Why This Matters for AgencyBloc's AI Strategy
• Get the Full Report
• Frequently Asked Questions

Insurance Agents Want AI That Knows Their Book of Business, Securely

AgencyBloc surveyed 55 health, life, Medicare, and employee benefits insurance professionals this spring to better understand how AI is being used in agencies today. . While it wasn’t surprising to learn that most insurance agencies are already using AI, the survey revealed what agents want AI to help with next and where they see the greatest opportunity for it within their workflows. 

91% of agencies surveyed are already using AI in some form, and 58% use it every day. But most of that use is still relatively surface-level: drafting emails, writing marketing copy, summarizing a call, etc. The capabilities agents say they want most, renewal reminders, risk flags, data entry help, and compliance support, all require AI to work directly with their book of business data — the client records, policies, and renewal dates that live inside their AMS or CRM. 

Here's what the data shows about where agents are today. It covers what they want AI to do with their client and policy data, and what it would take for AI to earn that kind of access.

How are insurance agents using AI today?

Mostly for writing. 80% of agents use AI to draft emails or client communications, the single most common use case by a wide margin. Marketing content comes next at 61%, followed by summarizing calls and meetings at 48%.

That's a sensible place to start. Drafting is low-risk; the agent reviews and sends the final version either way, and the time savings show up immediately. It's also why general-purpose tools dominate the landscape right now: 83% of agents who use AI use a tool like ChatGPT, while only 24% use AI features built into their AMS or CRM. Most agents' first AI experience has been a chatbot helping them write, not a system working with their actual client data.

What do agents want AI to do with their book of business?

Something more operational. When asked which AI capabilities would be most valuable inside their AMS or CRM, agents ranked renewal reminders and risk flags highest at 72%, ahead of drafting follow-up emails (65%), data entry assistance (61%), compliance or documentation support (54%), and cross-sell or upsell alerts (52%).

The common thread across these capabilities is that they require AI to work directly with policy and client data. A copy-and-pasted snapshot lacks the context needed to support agency workflows and quickly becomes outdated. That's a meaningful shift from where current usage sits. 

What’s more: marketing content, the task AI already handles decently today, ranked lowest on the wishlist at 44%. Agents don't need more help with what AI has already solved for them. They want it pointed at the parts of their book of business that eat up time every week: tracking renewals, flagging risk, keeping records current.

Why do agents want this built into their AMS or CRM instead of a separate tool?

Because the value is in the data, and the data already lives there. 61% of agents say it's extremely or very important that AI be built directly into the systems they already use, rather than living in a separate app. Right now, only 24% say they’re using AI directly within their AMS or CRM.

Here's an example of that gap brought to life: 48% of agents already use AI to summarize calls or voicemails, but how are they connecting that exported summary to their AMS data and, better yet, how are they making that summary actionable? 

The summary may end up in the contact record, but turning it into a follow-up task, renewal note, or reminder still requires the agent to take the next step manually. That's not a limitation of summarization, but rather a limitation of where the summary originates. A general-purpose tool can write a clean recap of a call, but it doesn't know which client that was, what policy they have, or what should happen next inside the agency's system. AI built into the AMS does, which is likely why 65% of agents say drafting follow-up emails would be one of the most valuable things AI could do inside their AMS or CRM, not in a separate app.

It's also interesting that some of the examples agents are asking AI to handle are already possible today. Renewal reminders, for instance, can already be built with workflow automation inside many agency systems. But building one means setting up the logic by hand or editing a workflow recipe, which is likely part of why agents describe this as something they want AI to do. It's not because the capability doesn't exist, but because making it automatic and intelligent, instead of manually configured, is the harder problem that's still unsolved. Either way, agents are clear about the destination: AI that works inside the system holding their book of business, not a tool they have to copy information into and back out of.

What does it take to trust AI within a book of business?

Security, oversight, and a clear paper trail, in that order. 83% of agents say strong data security protections would make them more comfortable using AI, the single most-requested factor in the entire survey. 67% want confirmation that their client data isn't being used to train public AI models. 74% want human approval before anything AI-generated reaches a client, and 72% want the ability to review and edit AI output before it's used.

Read together, that's not a list of objections, but rather a checklist. Agents already see the potential value of AI. What they want now is confidence that it is secure, transparent, and reviewable before it becomes part of their daily workflows. That's a reasonable bar for any system getting access to client policy data, AI included.

This lines up with what agents told us directly in their own words, too. When we asked agents about their biggest open questions, compliance came up more often than job displacement, cost, and general distrust of AI combined. Agents aren't opposed to AI, but they have clear standards for what it has to get right before they'll trust it with the data that runs their business.

65% currently say they trust AI output "a moderate amount," which reads less like hesitation and more like a reasonable starting point that should grow as security and oversight are proven.

Where do agents expect AI to make the biggest difference next?

Administrative work, by a wide margin. Reducing administrative work was ranked the #1 priority by 48% of agents and included in the top three priorities by 88%, the strongest result of any category in the report. Improving client service came in a clear second (29% ranked it #1, 79% in the top 3), with increasing sales productivity trailing behind that.

Most agencies are still building their AI approach rather than scaling a formal one. Roughly a quarter are testing tools, a quarter are building internal processes, and a quarter are watching and learning. 59% said better training on how to use AI would make them more comfortable adopting it, indicating that the next year will be less about developing flashier AI tools and more about equipping agencies with the time, training, and support needed to apply AI to their highest-priority work.

Why this matters for where we're headed at AgencyBloc

The message from the data is clear: agents want AI built into the systems they already trust, focused on reducing administrative burden, and backed by the security and oversight that their work demands.

We're developing new AI capabilities powered by AgencyBloc Intelligence directly within AMS+. These capabilities are built with that same principle at the forefront: giving agents faster, clearer ways to interact with the client and policy data already in their system where the agent is always in control of what happens next. 

To learn more about AgencyBloc Intelligence, visit our AgencyBloc Intelligence overview page.

Get the full report

This summary covers the headline findings, but the full report breaks results down by agency size, role, and line of business, and includes five strategic recommendations built directly from the data. If you want to see how your agency's AI use compares to your peers, the full report is the place to look.

FAQ

What do insurance agents want AI to do with their book of business?

Agents rank renewal reminders and risk flags highest (72%), followed by drafting follow-up emails (65%), data entry assistance (61%), and compliance or documentation support (54%). All of these require AI to work directly with client and policy data, not copied and pasted context.

Why do insurance agents want AI built into their AMS or CRM instead of a separate tool?

61% of agents say it's extremely or very important that AI be built into the systems they already use, since their book of business data already lives there. Only 24% currently have that, mostly relying on general-purpose tools like ChatGPT instead.

What security standards do insurance agents expect from AI?

83% want strong data security protections, the top factor in the entire survey, followed by confirmation that client data isn't used to train public AI models (67%), human approval before anything reaches a client (74%), and the ability to review and edit AI output (72%).

How are insurance agents using AI today?

91% of agencies surveyed use AI in some form, most commonly for drafting emails and client communications (80%), writing marketing content (61%), and summarizing calls or meetings (48%). 58% use AI tools daily.

This blog was posted on Tuesday, June 30, 2026.

Posted by Kelsey Rosauer on Tuesday, June 30, 2026 in AgencyBloc Intelligence

1. ai
2. insurance automation
3. productivity
4. vendor vetting