Independent agencies have never had more technology options than they do right now. Agency management systems, CRMs, automation platforms, AI tools, comparative raters, marketing technology, document processing solutions, carrier integrations and countless point solutions all promise to help agencies become more efficient and more profitable. 

For many agency leaders, the challenge is no longer finding technology. It is deciding which tools are actually worth adopting and how to use them in a way that creates real value for your agency. 

That question has become even more important as AI moves from a future-focused concept to a practical business tool. The 2026 Big “I” Agent Council for Technology (ACT) Tech Trends Report reflects strong interest from independent agents, with nearly two-thirds planning to use AI more in the year ahead. But interest is not the same as adoption. Many agencies are still figuring out how AI fits into their daily work, and ACT research points to a clear gap: the biggest blockers are often not the tools themselves, but process, governance and training. 

More than half of agencies do not yet have a documented AI policy, with 56% reporting they have no written AI policy of any kind. Another 44% rely exclusively on informal peer-to-peer training as their primary AI education. Many participating agencies also reported that their core business processes are not fully documented, which makes it harder to know what should be improved, automated or protected. 

At the same time, industry conversations around technology and agency value are pointing to the same conclusion: technology can absolutely help agencies grow, become more efficient and create long-term value, but only when it is solving a meaningful business problem. 

Start with the Problem, Not the Tool 

One of the biggest mistakes agencies can make is chasing technology simply because it is new. AI and automation can be powerful, but they are not strategies by themselves. 

During a recent conversation between IA Valuations and industry leaders, including Brad Winters of Winters Financial Network, Frank Neugubauer of Cincinnati Insurance Companies and Eric Eschliman of Agent Vista, one theme came through clearly:

Technology itself does not create value. The way an agency uses it does. 

Brad Winters described the risk as “shiny object syndrome.” A new product launches, a vendor gives a compelling demonstration, or everyone at a conference seems to be talking about the latest AI-powered solution. Before long, it becomes easy to assume that because a tool is innovative, it must also be valuable. 

The better approach is to reverse the process. 

Instead of asking, “What AI tool should we try?” agency leaders may be better served by asking, “Where are our people losing time?” Are service teams spending too much time on repetitive work? Are producers bogged down with research? Are employees navigating multiple carrier portals to retrieve documents? Are disconnected systems creating delays or duplicate work? 

Once the problem is clear, evaluating technology becomes much easier. The best AI use cases often begin with low-risk, high-volume work that slows the team down but does not require human judgment at every step. 

Build the Foundation Before You Scale 

Successful AI adoption depends less on finding the perfect tool and more on building the right foundation. Agencies need clear workflows, reliable data, written expectations and practical training before AI can become a meaningful part of the business. 

That foundation starts with governance. Agencies should put AI expectations in writing, including how employees may use AI, what information should never be entered into a tool, who is responsible for reviewing AI-assisted work, and how vendors should be evaluated. A written policy does not need to be complicated, but it should give employees guardrails so they can experiment responsibly. 

Process documentation matters too. If an agency has not clearly documented how work gets done today, it is difficult to know what should be automated tomorrow. AI can help improve workflows, but it should not be layered on top of unclear or inconsistent processes. 

Training is another important piece. Agency employees do not need to become technology experts, data scientists or software engineers to remain competitive. But they do need enough understanding to use AI safely, thoughtfully and effectively. Treating AI like a junior team member is a useful mindset. It can help draft, organize, summarize and surface information, but its work still needs review, context and human judgment. 

The Big “I” Agent Council for Technology is working to support agencies in this process through practical resources shaped by agents, carriers and technology providers. More than 1,300 agents participated across the Agency AI Labs series, confirming just how important and challenging this topic has become for independent agencies. 

Use Technology to Create More Time for Human Work 

Inside agencies, some of the most practical AI and automation opportunities are not dramatic at all. They are the everyday tasks that quietly consume hours. 

For example, Brad Winters shared how his agency uses automation to retrieve policy documents and endorsements, eliminating tedious manual work that previously required employees to navigate multiple carrier portals. The result is not simply improved efficiency. It gives employees more time to strengthen relationships and advise clients. 

AI-powered policy comparison tools can also accelerate renewal reviews by highlighting coverage changes and differences between policies. That reduces administrative effort while creating more opportunities for meaningful client conversations. 

On the sales side, Eric Eschliman described how technology can gather and organize prospect information before producers ever reach out to a potential client. Instead of spending time searching for information, producers can focus on strategy, relationship development and problem solving. 

In each case, technology is not replacing agency professionals. It is helping them focus on the work that matters most. 

Technology Spending Is Not the Same as Strategy 

Technology also connects directly to agency value, but not simply because an agency spends more on it. 

IA Valuations regularly analyzes the operational characteristics of high-performing agencies, and one observation continues to stand out: agencies with the highest technology expenditures are not necessarily the agencies receiving the highest valuation multiples. The differentiator is efficiency. 

The most valuable agencies consistently demonstrate stronger productivity metrics, particularly revenue generated per employee. Technology contributes to value creation when it allows employees to manage more business, serve more clients, improve processes or focus on higher-value activities. 

In other words, technology spending is an investment, not a strategy. The value comes from improving productivity, strengthening margins, enhancing client experiences and building a more scalable agency. 

The Relationship Advantage Still Matters 

As AI and automation become more widely available, smaller and mid-sized agencies may gain access to capabilities that were once reserved for the industry’s largest firms. Data analysis, workflow automation, customer insights and operational efficiencies are becoming increasingly accessible. 

But as those tools become more common, the real differentiator may be the quality of the relationship behind them. 

Technology can help an agency move faster, but it cannot replace the trust built between a client and a knowledgeable advisor. Clients still want advocacy, guidance and judgment, especially when decisions are complex or stakes are high. As Frank Neugubauer noted in the IA Valuations discussion, people buy relationships, not machines. 

That may become even more true as concerns grow around misinformation, digital impersonation and AI-generated communication. In a world where digital communication can feel increasingly automated, authentic human connection may become even more valuable. 

What Agencies Should Do Now 

For agencies thinking about AI, the next step does not have to be overwhelming. Start by identifying one business problem worth solving. Document the current workflow. Set basic rules for responsible use. Choose a low-risk, high-volume area to test. Train the team. Review the results. Then decide whether the tool is truly helping the agency work better. 

Agencies should also take advantage of the resources already available through ACT, including sample AI policies, process documentation tools, data quality resources, governance frameworks and Agency AI Labs recordings. These resources can give agencies a stronger starting point for developing AI policies, documented procedures, data-quality standards and responsible governance. 

The agencies that benefit most from AI will likely be the ones that use it with intention. Not to replace people, but to give their people more capacity to do what only humans can do well: build relationships, provide advice, solve problems and create trust. 

About the Author

Jeannine Giesler, CISR, CPIA, and past President of the OIA Board of Directors, Foundation for the Advancement of Insurance Professionals, currently serves as Resource Center Advisor for the OIA. The purpose of the Resource Center is to contribute to building a comprehensive library of resource materials for our members. We pride ourselves on being the one-stop shop for all OIA members and work to solve every problem or situation you may come across.