What Agencies Got Right With AI Adoption—And The First Steps They Took

• May 4, 2026

By Francisco Lopes

Artificial intelligence (AI) isn’t a threat—but uncertainty is. For many independent insurance agents, the idea of bringing AI into an agency raises real questions. However, the agencies seeing results from adopting AI tools started with the exact same ones: Will clients feel like they’re talking to a bot? Will things fall through the cracks? Will it undermine the relationships we’ve spent years building?

Questions also arise around AI in internal workflows. Will it compromise data privacy? Is this going to be another tool layered on top of systems that don’t integrate?

All of these questions and concerns point to one thing: agencies don’t need another vendor pitch about the future of AI. They need to see how it actually fits—or doesn’t—into real agency operations, based on what’s already working.

The Real Opportunity

Independent agencies are under pressure from rising client expectations, talent shortages and the constant need to do more with less. This is where AI can help.

In practice, the pattern is straightforward: AI handles the repetitive volume—the calls that interrupt producers mid-conversation, the after-hours inquiries that become Monday morning voicemail pileups—and gives that time back to licensed staff, enabling them to focus on higher value work, such as advising clients, building relationships and selling.

Agents can be more responsive without adding headcount and clients can get answers quickly while still having access to a human when it matters most.

One common concern from agents is “my clients won’t accept this.” However, the data says otherwise. More than 65% of consumers said they’re willing to interact with an AI assistant if it means faster responses, according to a Sonant survey of more than 1,000 consumers. And the highest comfort levels came from consumers aged 45–60, the core demographic for most independent agencies.

The agencies that have adopted AI successfully didn’t start with a big rollout; they started with a conversation with their staff first, then with their clients. They were specific about what AI would and wouldn’t do, where humans stay in the loop, and what the fallback would look like if something didn’t work as expected.

Trust in AI is a major issue for customers. The top three concerns consumers have when interacting with AI are incorrect or unreliable information, privacy and data security, and not being able to reach a human when needed, according to the survey.

Successful adoption requires agents to be upfront with clients about when they’re interacting with AI and how it’s being used. When deploying AI to answer calls or manage website chats, position it as a first point of contact capable of handling initial questions quickly, while making it easy to connect with a human at any time.

For example, one agency deployed a voice AI assistant to handle inbound calls but kept a short list of clients who preferred to speak directly with a person. That kind of flexibility made their staff and clients comfortable with the change.

Agencies can also be proactive in addressing other common concerns, including data privacy, security and accuracy. That means selecting solutions that meet compliance standards and clearly communicating those safeguards to clients. It’s equally important to reinforce that there’s always a human in the loop and AI is not making final coverage decisions or replacing professional advice.

Playbook: Start Narrow, Prove It And Then Expand

For agencies looking to move forward, the key is to start small. The most effective implementations focus on low-risk, high-impact areas where AI can deliver immediate value without overhauling existing processes. Call triage, basic inquiry handling, and document analysis are good starting points where many agents can begin.

At the same time, agents should be realistic about operational readiness. Some tools depend on clean, structured data and if that foundation isn’t there yet, results will fall short. That’s why piloting matters. Start small. Test. Gather feedback from both employees and clients. Refine the approach before scaling. The goal isn’t to add complexity, it’s to reduce it.

The question for most agencies isn’t whether AI will be part of insurance operations—it’s whether you’ll be the one who figures it out early in your market, or the one who has to catch up later.

Francisco Lopes is CEO of Sonant, a voice AI receptionist built for insurance agencies and brokerages.