Artificial intelligence is often talked about as the future of the insurance industry. It's described as a game-changer that could transform how things are done. With all this excitement, insurers might feel like they need to jump into big AI projects, expecting fast results. But it's important to see AI not as a magic solution, but as a useful tool. If used strategically, AI can solve specific problems and improve current processes without depleting resources or causing major disruptions.
AI as a Tool, Not a Revolution
Many people think AI will change insurance overnight. This kind of thinking can lead to unrealistic expectations and poor strategies. Instead, AI should be seen as a powerful tool that can enhance different parts of the insurance business. By thinking of AI this way, insurers can focus on using it in specific areas instead of pursuing sweeping changes that might not meet their real needs.
To use AI effectively, organizations need to understand the whole business—from product development and underwriting to claims, customer service, and IT. This means identifying inefficiencies or repetitive tasks that AI can help solve. For example, customer service agents often struggle to provide quick and accurate information because they must search through numerous documents. Also, manual work in claims can slow processes and lead to errors. By identifying these specific issues, insurers can evaluate how AI tools might improve operations.
How to Decide on AI Solutions
When evaluating AI solutions, it's important to be practical. Cost is an obvious factor—tools should be affordable and scalable, whether that means handling more users or more data or adding features over time. Integration is also important—the less an AI tool needs to connect with existing systems, the better. Solutions that require minimal changes to current workflows and are easy to use are ideal because they cause less disruption and are more likely to be accepted by staff.
Two examples are chatbots for customer service agents and AI tools for handling documents in claims. These are effective first steps for AI because they address common problems, are relatively easy to implement, and provide quick, visible benefits without major disruptions. A chatbot can help agents find information faster, leading to better customer service. AI document tools can sort and extract information, reducing manual work and accelerating claims processing.
A practical approach to AI means starting with small projects. Choose simple initiatives that can show quick wins, like fixing a specific customer service issue or automating a repetitive task in claims. Small projects can be completed quickly, often in just a few weeks, which helps build momentum. These quick wins are important for gaining organizational support for AI and encouraging wider acceptance.
Initially, it's best to involve only the people directly affected by the issue. This keeps projects simple and avoids unnecessary complications. For early AI projects, integration with existing IT systems may not even be necessary. Once a small project succeeds, it can serve as a model for other projects and help build support across the company.
Building Toward a Larger AI Plan
After success with small projects, insurers can work on a broader AI strategy. This means scaling AI tools across the company and involving key departments like IT, finance, and leadership. Having a clear plan helps ensure AI is used in a way that meets business goals. Growing AI gradually also helps the company develop the internal skills needed for more advanced projects.
The biggest mistake is starting with projects that are too large and complicated. Signs of this include unclear goals, needing to connect with too many systems, or involving too many departments immediately, which increases complexity. Big, ambitious projects are tempting, but without experience, they can consume too many resources and disrupt workflows. A better approach is to start small, with simple, easy-to-use tools. This helps insurers get real benefits without losing control over adoption pace and scope.
Setting Up for Future Growth
By taking a practical approach, insurers can use AI to work more efficiently, improve customer service and stay competitive. The key is to avoid trying to do too much at once and instead focus on practical uses that fit into current operations. Starting with small projects not only brings quick results but also prepares the company for bigger AI opportunities in the future. A practical approach helps insurers succeed now and set the stage for long-term growth as AI technologies continue to improve.
AI has significant potential for the insurance industry, but using it successfully requires a careful, step-by-step approach. By seeing AI as a set of tools for solving specific problems, insurers can implement solutions that are cost-effective, easy to integrate and compatible with current processes. This approach allows companies to build skills over time and create a strong foundation for more advanced AI use in the future.
