NPS
Privacy and “where do we start?” hold agencies back more than cost does. Both have practical answers. Here are two tests to decide with.
In our InsuredMine AI Pulse Report 2026, privacy, security and compliance concerns lead the list of barriers, named by 43% of agencies. Not knowing which use cases to prioritize follows at 39%. Budget (13%) and leadership priority (10%) sit near the bottom. Another 27% say their systems don’t integrate well enough to make AI useful. The privacy concern holds near 40% at every agency size.
We read those numbers as a reasonable hesitation: owners want control over how AI is used, where client data goes and what happens when staff start using it on their own. Each of those can be answered.
In our first piece, we looked at what manual work costs. This one looks at why many agencies still wait.
What does responsible AI adoption mean for an insurance agency?
It means the agency, not each individual, decides four things: which tools staff may use, what client data may go into them, who reviews the output and who is accountable when something goes wrong. Without those decisions, staff make them alone.
In Liberty Mutual’s 2026 survey of about 1,150 agency principals and staff, 65% said they had used AI for work in the past year, but only 14% said their agency had put an AI tool in place. Only 18% said their agency has a well-defined AI policy. Where individual use runs ahead of agency setup, client data can end up in tools nobody chose or reviewed.
It’s the same blind spot as in our first piece. The headline adoption numbers show how much AI is used, not what it touches.
Is AI safe to use with insurance client data?
It depends on where the data goes and who controls it. Our report suggests three questions for any AI tool, including ours and the ones your team already uses:
Where does our client data go, and is it used to train models? Can every output be traced back to its data and rule? If we leave, what do we take with us, and how?
A tool that works inside your existing systems cuts copy-and-paste, but that alone doesn’t make it safe. How a tool connects, how it’s governed and how it protects data are three separate things, and these questions test the last two.
Our view is that a tool the agency has chosen at least gives staff a sanctioned way to use AI instead of finding their own.
Where should an insurance agency start with AI?
Start with one workflow that passes three tests:
- It repeats every week.
- One person or a small team owns it.
- You can measure it before and after.
Take renewal preparation. It repeats weekly, an account manager owns it, and you can time it before and after. It passes. A one-time data migration doesn’t. Quoting and renewals are the workflows agencies in our first piece most often named as taking the most staff time. Here is what to measure for four common starting points:
Where to start & what to measure
In our survey, the first thing owners ask for is clarity on which day-to-day workflows AI actually improves (34%), followed by a low-commitment pilot (17%) and a live demo on a similar agency’s data (16%). ROI models draw 4%. A pilot should count review time as part of the work and make room for people who prefer not to use AI.
How do you get your team comfortable with AI?
Kingsgate Insurance’s story is about adopting a CRM, not AI, but the hesitation is the same. Marketing lead Nicole Clegg says the hard part was getting a staff used to working in Epic comfortable working somewhere else. Her own line for the shift: “Epic is the filing cabinet. InsuredMine is the book you work out of.”
Nicole became the agency’s internal champion, learning the platform and writing every task so a newcomer could follow it.
How can we help you decide?
You now have two tests, one for trust and one for where to start. Run both on us.
For trust, put the three questions above to us. InsuredMine is SOC 2 Type II certified, and we’d rather you ask than assume.
For where to start, bring a workflow your team handles every week. We’ll show you how InsuredMine connects with your existing AMS, where AI can reduce the manual work, and what the process looks like day to day.
What’s the bigger hesitation at your agency: trust with client data, or knowing where to start
This is part of the AI Ready for 2027 series. Next: where AI pays off first, the revenue already in your book.
Frequently asked questions
Is AI safe for insurance agencies to use with client data? It depends on where the data goes and who controls it. Ask any tool where client data is stored, whether it’s used to train models, whether outputs can be traced to their data, and what you take with you if you leave.
What is responsible AI adoption for an insurance agency? The agency, not each individual, decides which tools staff may use, what client data may go into them, who reviews the output and who is accountable when something goes wrong.
What stops insurance agencies from adopting AI? In our survey, privacy, security and compliance concerns (43%) and not knowing which use cases to prioritize (39%) lead the list. Budget is named by 13%.
Where should an insurance agency start with AI? With one workflow that repeats weekly, has a clear owner and can be measured before and after. Quoting and renewals are common choices.
