Crawford CTO warns AI could weaken insurance talent pipelines
As insurers automate entry-level work with artificial intelligence, they risk eliminating the roles that have traditionally trained future experts. In insurance, where professional judgment develops over years of handling complex claims, that trade-off could create serious gaps.
Joel Raedeke, chief technology officer at Crawford & Company, sees a paradox. AI can dramatically increase productivity, but it delivers the greatest value when experienced professionals use it-not when it replaces their early-career training grounds. "When you're new at something, you don't know what good looks like," he said. "There's a strong chance of doing a lot of bad things at scale without recognizing it."
Expertise becomes more valuable, not less
Raedeke believes AI is unlikely to replace expertise in claims. Instead, it may make expertise more valuable than ever. Generative AI can produce summaries and insights that seem impressive on the surface, but only experienced adjusters can spot what's weak or inaccurate.
Crawford treats AI as the latest stage in embedding advanced technology into claims operations. The company subjects generative AI workflows-including machine learning, predictive modeling, and large language models-to extensive testing before they reach adjusters.
Small errors in claims can influence outcomes for both policyholders and carriers. Raedeke stressed the importance of rigorous scrutiny. "If you've used ChatGPT to summarize something, you'll often find it's amazing in terms of what it can do," he said. "But when you look at the details, it may not be summarizing things exactly the way you would want."
Crawford ensures that AI tools don't undermine adjusters' ownership of claim strategy. "If it isn't meeting our standards for accuracy and comprehensiveness, it can negatively impact the claim outcome," Raedeke said.
Overcoming distrust of AI in contracts
Early concerns about generative AI led some clients to prohibit AI use entirely in contracts. The irony: insurers had already been using forms of artificial intelligence for decades.
"About a year and a half to two years ago, one challenge involved the language around AI and what it actually means," Raedeke said. Clients worried that AI might expose their data to outside parties, so they inserted contract language banning AI from claims processes.
But optical character recognition (OCR)-which turns scanned images into text-has been in use since the early 2000s. That's a type of AI. "There was a disconnect where people would prohibit something in contracts that had effectively been in use for decades," he said.
Those conversations are becoming more sophisticated. "We're not fully free of distrust, but clients are becoming more nuanced," Raedeke observed. "The conversation is less about 'You can't use AI' and more about data privacy, security and how it's being used."
Augmentation, not replacement
Raedeke does not expect claims professionals to disappear. "The analogy I use is that if we once worked with hand tools, now we have power tools," he said. "If we once had shovels, now we have cranes and bulldozers." The goal is to automate administrative tasks, not the decisions themselves.
The insurance industry faces competing pressures. AI-powered fraud is already emerging as a significant challenge. UK insurer Aviva reported detecting a record £233 million in fraudulent claims during 2025, citing increasing use of AI-generated documents and manipulated evidence by fraudsters.
At the same time, insurers are investing heavily in AI capabilities. A recent KPMG survey found that 73% of insurance CEOs now rank AI as their top investment priority.
Senior expertise matters most
Raedeke said an unexpected lesson from Crawford's AI work applies broadly: AI-generated code works well when paired with senior engineers. "They know what to look for and can recognize when something isn't right," he said. "Putting AI into the hands of a junior developer isn't something we've found to be a good practice. Putting it into the hands of a very senior engineer can be extremely valuable."
That principle extends beyond software development. In AI for insurance, the professionals using the tools matter more than the technology itself.
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