Trade coverage says independent agencies have left the demo phase. The next bottleneck is boring: integrate one workflow, train people, and prove ROI before EO risk shows up.
Via IA Magazine: Independent Agents Are Past AI Hype-Now Comes the Hard Part
Halfway through 2026, independent insurance agents stopped asking what artificial intelligence is and started asking what it does to the daily workflow-and where it lands errors and omissions exposure. That is the through-line in IA Magazine July 15 Viewpoint by Kasey Connors, executive director of the Big I Agents Council for Technology (ACT), drawing on a Vertafore webinar and Vertafore 2026 Agency Technology and Growth Outlook Report.
Connors framing is blunt: adoption is real, returns are mostly unglamorous, and the gap is not missing software so much as missing integration. For owner-led agencies, that is the difference between a tool that looks clever in a lunch-and-learn and a process that actually frees an hour before renewal season.
According to Vertafore report as cited by IA Magazine, about one-third of agencies are actively using AI today, another third are experimenting, and approximately 39 percent are still spending 2026 exploring use cases rather than putting anything into production. The Big I ACT 2026 Trends Report puts a sharper point on it: only 8 percent have truly embedded AI in their daily workflow. Larger agencies are investing ahead of smaller ones, though Connors notes that gap should close as implementation gets cheaper.
Where results show up, they are everyday wins-not moonshots. Agencies point AI at high-volume, repetitive work: policy checking, call note summaries, drafting client communications, email processing, and commission statement automation. One example from the 2025 Best Practices Study (Big I and Reagan Consulting), cited in the piece, reported an agency saving 30 minutes per staff member per day on policy checking. Connors gloss: that is not transformation, that is arithmetic-the kind of case that gets a skeptical principal to say yes.
Most agencies are not under-investing in tools, Connors argues. They are under-integrating them. A tool that sits outside the daily workflow gets forgotten, no matter how good the pitch deck. The agencies pulling ahead start with the workflow problem and then find technology to solve it-not the other way around.
Underneath the AI conversation sits a duller constraint. Only about 25 percent of agencies actively use their own data to make strategic decisions, according to the 2024 Agency Universe Study as cited by IA Magazine. Clean data enables segmentation; segmentation enables cross-selling; cross-selling drives revenue. Poor data quality blocks every step, regardless of model capability.
Client expectations are rising as the market stabilizes. Vertafore policyholder expectations reporting, cited in the article, finds only 1 in 5 policyholders (21 percent) say they receive proactive updates or outreach from their agent. Speed at the front end matters: 83 percent of policyholders expect a response within one business day, and 35 percent expect a reply within one hour. About 30 percent of consumers only think about insurance once a year or at a major life event, per a Big I and Trusted Choice consumer survey cited in the piece-so the agency has to initiate contact, not wait for the renewal call.
Only 8 percent of agencies have truly embedded AI in daily workflow, while about one-third actively use it and roughly 39 percent are still exploring.
Connors prescription is deliberately small: agencies do not need a five-year AI roadmap. Pick one workflow, identify two manual steps inside it, and automate them. Write down institutional knowledge that currently lives only in long-tenured employees heads-roughly 20 percent of agency principals are over 55, per the 2024 Agency Universe Study as cited-so knowledge survives the people currently holding it.
That is workflow design with a governance spine, not another pilot. AgentsROI.ai is a managed AI services provider for owner-led SMEs. I do not sell a chatbot. I run, govern, and measure AI so it keeps paying for itself-vendor-neutral and outcome-first.
Start with a Workflow ROI Audit. Map the high-volume loops Connors names-policy checking, notes, email, commissions-and cost the minutes. Prioritize the two steps that free capacity without inventing a new EO story.
Pair it with Managed AI Operations once something works, so the tool stays inside the workflow instead of becoming shelfware. Model changes, vendor pricing, and staff habits all drift; managed ops is how you keep the arithmetic honest.
Add a Fractional AI Officer when the principal is also the unpaid compliance desk: light governance, training cadence, and decision rights so AI said so never becomes the agency defense file.
IA Magazine coverage is a useful mid-year reality check: independent agencies have moved past experimentation theater into the harder work of integration, training, and ROI. The winners will look boring on LinkedIn-one workflow, two automated steps, measurable minutes back, human judgment still on the signature line.
If your agency is stuck between exploring and embedded, start with a Workflow ROI Audit. Book a no-pressure assessment when you are ready to treat AI as operations, not as a headline.
This article summarizes publicly reported information and is for general informational purposes only. It does not constitute legal, tax, financial, investment, security, or compliance advice. AgentsROI.ai is not a law firm, accounting firm, or registered investment adviser. Facts, pricing, statistics, and product capabilities cited here reflect the sources listed at the time of writing and may change. Readers should verify current information independently and consult qualified professionals regarding obligations specific to their industry, jurisdiction, and circumstances-including applicable New York State and New York City requirements. AgentsROI.ai may have commercial relationships with vendors mentioned; where material, such relationships are disclosed. Nothing in this article is an endorsement of any specific AI product, model, or provider.
