GETTING YOUR AGENCY AI READY FOR 2026

Step 1:
Define your use cases

Agencies that are seeing the most success with AI are those that start with clear business goals and a few high-value use cases. A defined scope and a targeted approach make adoption more manageable, allow you to really measure outcomes and successes, and build your team’s confidence to become AI ready for other uses down the road.

Many agencies start putting AI to work in one of three ways:

1. Workflow automation. Agencies are finding value in streamlining common tasks with AI automations and tools.
2. Risk prediction. AI can analyze an agency’s claims history and spot patterns, such as which policies are likely to see premium increases or where carriers may pull out.
3. Data entry. Manual data entry is tedious and error-prone, and pulls staff away from revenue-driving work. AI can populate client information automatically, cutting data-entry time and improving accuracy.

To decide which AI use cases are best for your agency, start by looking at your current workflows and business needs. Where is your team spending the most manual hours? Which client processes cause the most errors or rework? Where would faster insight improve the client experience? These answers reveal where AI might create the most value for your agency.

In addition, agency leaders should consider whether workflows and processes are standardized across the agency. If two groups in an agency do the same process in completely different ways, giving them the same AI solution won’t deliver the same results. Consistency is foundational to success.

Step 2:
Integrate your tech and data

Once agencies identify where AI could help most, the next step is ensuring that their systems (and data) are ready to support it. Agency leaders should audit existing tech stacks and ensure that they’re ready to handle AI-powered workflows. The key is having integrated data and tools that can talk to each other.

First, integrated systems help with data management. With AI, the quality of the data determines the quality of the output. Without integrated systems, data will be incomplete and insights from AI will fall short, lacking critical information. But when data is consistent across connected software solutions, AI can access all the information it needs, leading to better quality outputs.

Imagine if client data lives in one system, claims data is in another, and carrier information is in a third. AI working without data integration might flag a policy as low risk when, in reality, recent claims data from another system tells a different story. When these systems are integrated, AI can analyze all the relevant information together, identifying clients at risk of non-renewal earlier and helping the agency retain business.

Along with data integration, tool integration is also essential for automation to work because agencies rely on multiple tools to do their work effectively. For example, consider how many tasks start with an email. New prospects, policy changes, and client requests all flow in through an inbox. With AI, integrated tools can read the email, match it to the client in the management system, automatically create tasks, and launch the right workflow.

Strong data and system integration set the stage for AI to deliver real business impact. When your tools and data work together, AI can do more than automate tasks, it can drive smarter decisions and stronger client relationships.

Step 3:
Empower your teams

Defining the best use cases and ensuring that your tech stack is AI-ready are essential, but success depends most on people. Ultimately, AI is a tool to amplify your team’s expertise and free them to focus on what matters: growing the business and building relationships with clients. Agency leaders need to be thoughtful and deliberate with empowering their employees with AI.

I’ve found that change management works best when it comes from within. The most effective way to get people on board is to highlight teams who are already excelling. Create space for their peers to hear directly from them about what worked, what mistakes they avoided, and how they’re seeing success. That’s far more accurate and helpful than emailing a PDF of an outside case study.

The magic happens when agency employees see how AI eliminates duplicate data entry or cuts down hours of manual work. AI isn’t here to replace agents and account managers; it’s here to make their jobs easier by taking on the heavy, manual tasks that slow them down. Pairing the right tech with the right training frees your teams to focus on the work that drives agency growth.

Conclusion

AI-readiness is all about empowering your people with the tools they need for success. The agencies that take these steps today will enter 2026 with a clear advantage: streamlined operations, empowered employees, and the ability to deliver faster, smarter service to clients.

The author

Daniela Ivey, vice president of product management at Vertafore, brings over 15 years of experience in the technology industry. Her expertise spans multiple domains, including software, hardware, mobile, and web-based products. She is passionate about elevating teams to their highest potential. Daniela’s expertise, leadership, and dedication to excellence have positioned her as a thought leader and strategic visionary in the technology industry.