Two-Thirds of Independent Agents Plan to Boost AI Use in 2026

Two-thirds of independent insurance agents say they plan to increase their use of AI tools in 2026, according to a report released in February by the ACT group of the Independent Insurance Agents and Brokers of America. That is a significant number for an industry that has historically moved carefully on technology. The catch is that data privacy and regulatory compliance concerns are slowing actual deployment, which means the gap between agents who figure this out and those who stay cautious is about to get wider.

What Do Agents Actually Want AI to Do for Them?

According to Vertafore (2026), agency professionals are not looking for AI to write their coverage recommendations or replace their client relationships. They want it to free up time for exactly those things. The clearest demand is for AI to handle administrative load: drafting routine communications, pulling policy data, summarizing renewals, and managing follow-up tasks that eat hours without generating revenue.

That framing matters. An agent who deploys AI to cut two hours of paperwork per day has effectively added capacity without adding headcount. For a three-person shop, that is a meaningful operational change. For a solo producer who also manages the office, it is potentially the difference between growing a book of business and treading water.

The tasks most frequently cited as targets for AI assistance fall into a few clear buckets: client communication drafts, renewal preparation, policy comparison summaries, and internal documentation. None of these require AI to make coverage judgments. They require AI to do the repetitive structured work so the agent can do the relational and analytical work that actually closes business.

What Is Slowing Adoption If Agents Already Want This?

According to the Independent Insurance Agents and Brokers of America ACT report (2026), the primary barriers to AI adoption are data privacy concerns and uncertainty about regulatory compliance. Those are not irrational worries. Insurance agencies handle sensitive personal and financial data. State insurance departments have jurisdiction over how that data is used, and federal frameworks are still evolving. An agent who feeds client information into an AI tool without understanding where that data goes has a real liability exposure.

The compliance question is layered. There is the data storage question, the disclosure question, and the question of whether AI-generated client communications require any specific disclosures depending on the state. None of these are resolved uniformly across the country, and most small agencies do not have a legal team to sort it out. That uncertainty is enough to keep cautious operators on the sideline even when they want to move forward.

The practical answer for most independent agents is to start with AI tools that operate entirely within your existing agency management system, or tools that have published data handling policies and do not train on client data. The vendors serving this space have responded to agent concerns, and several now offer explicit data isolation options. Asking the question before you sign up is not paranoia; it is due diligence.

Where Are Carriers Taking AI, and What Does That Mean for Agents?

According to Cognizant (2026), the next phase of AI in insurance is what they call coordinated agentic activity, where AI systems manage other AI systems to handle complex multi-step workflows. For carriers, that could mean automated underwriting decisions, real-time risk scoring, and faster claims processing. Bain, cited by LinkedIn contributor Sabine Vanderlinden (2025), estimates that redesigning claims with scaled AI can deliver roughly 35 percent productivity gains and cut processing times approximately in half.

For independent agents, this has a direct operational implication. As carriers invest in AI-driven workflows, the agents who interface with those carriers digitally and efficiently will get faster turnaround on quotes, endorsements, and claims status. Agents who are still sending faxes, or whose agency management systems are not integrated with carrier portals, will feel that friction as a competitive disadvantage, not just an inconvenience.

There is also a client expectation dimension here. According to Nationwide Agency Forward (2026), personalization driven by AI is becoming a baseline expectation among insurance consumers, not a premium feature. Clients increasingly expect that their agent knows their situation without being reminded of it at every call. AI-assisted CRM tools that surface renewal dates, life changes, and cross-sell opportunities make that possible at scale. Agents who do not have that visibility will feel it in retention numbers before they feel it in new business numbers.

Why This Matters for Insurance Agents

The two-thirds figure from the ACT report is the headline, but the real story is the gap between intention and action. In practical terms, this means that right now, the agents who move first on AI adoption have an advantage that may not be available in 18 months when adoption becomes standard. The tasks that feel like technology experiments today, drafting renewal letters, flagging cross-sell opportunities, summarizing policy comparisons, will feel like table stakes within two years.

The compliance concern is real and should not be dismissed, but it is also solvable. The agents who are working through that question now, reading vendor data policies, asking their E&O carrier whether AI tool use affects their coverage, and checking with their state department on any disclosure requirements, will be positioned to scale their AI use confidently. The ones who wait for the industry to fully resolve those questions may wait too long.

Reputation also factors in here in a way that is easy to overlook. As more client interaction gets mediated by AI tools, the touchpoints where agents build trust become fewer and more important. A well-timed, personalized renewal note is not just good service; it is a data point that shows up in reviews and referrals. Agents who use AI to do the administrative work, then show up fully present for the client conversations, will differentiate on service quality in a market where many of their competitors are doing the opposite.

The window for early-mover advantage on AI in independent insurance agencies is open right now, but it will not stay open indefinitely. Start with one workflow, resolve the data question for that tool, and build from there. That is a more useful posture than waiting for a perfect answer that will not arrive on any clear schedule.