Insurtech: Why Independent Agents Need Data Support to Use Agentic AI
IMA Financial Group, managing over $8 billion in annual premiums, operates as an independent broker and has been building AI capabilities internally. Despite its size, the firm focuses on how agents and brokers can effectively use agentic AI technology. Garrett Droege, senior vice president and director of innovation and digital risk at IMA, shares insights on the challenges and data requirements for agentic AI in insurance.
What Makes Agentic AI Useful for Insurers?
Many startups promote agentic AI services as transformative, but they often assume easy access to well-structured policyholder data. In reality, insurance data is rarely organized to support these technologies without significant infrastructure. Agencies not built on modern architectures struggle to realize broad AI benefits beyond simple tasks like call center support. True integration demands access to core data systems and a solid technology foundation.
Technology Challenges Hold the Industry Back
A large portion of major property and casualty insurers still rely on legacy mainframe systems, with actuarial data dating back decades. These outdated systems are difficult to connect with modern AI tools, forcing firms to reverse-engineer core data processes to improve workflows. The industry understands that without modernization, staying competitive will be tough. Agencies not upgrading risk being acquired, as those leveraging agentic AI can boost profitability by 30 to 60%.
Evaluating Agentic AI Services
Testing agentic AI effectiveness is tricky without updated core systems. Many AI platforms simply layer insurance functions over existing public models like ChatGPT or Gemini, which may not deliver unique value. Brokers and carriers often lack the expertise to differentiate between these solutions. Sustainable AI applications must rely on technology controlled by the firm, not external platforms. IMA has rigorously vetted partners to ensure security and genuine innovation.
Do Insurers Have the Right Data for Agentic AI?
Most insurers lack the necessary open data access. For example, routine commercial insurance tasks—such as handling certificates of insurance or coverage updates—could be automated by agentic AI if the system could access the agency management system (AMS). Without open AMS integration, AI solutions fall short, no matter how promising they seem.
Can Independent Agents Use This Technology Effectively?
Smaller and mid-sized independent agents face growing challenges competing with larger firms that offer better client experiences. Understanding risk profiles and providing personalized recommendations is key. As agentic AI improves user interactions, clients will likely favor firms that use these tools well. Agents who enhance user experience through AI stand a stronger chance of success.
Will Insurtechs or AI Companies Bridge the Gap for Smaller Firms?
Many insurtech startups recognize the difficulty of accessing AMS data directly. Instead, they embed AI assistance within popular platforms like Outlook or Google Workspace to help manage service requests. However, this approach still relies on human input into the AMS, leaving core data access issues unresolved. While these solutions may help temporarily, they don’t fix the fundamental problem of outdated core systems. The long-term viability of such tools remains uncertain as the industry evolves.
For insurance professionals looking to improve their AI skills and understand these technologies better, exploring specialized AI training courses can be valuable. Resources like Complete AI Training offer focused courses that cover AI applications relevant to the insurance sector.
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