Introduction
Why would an industry that governs almost everything still leave AI sitting on the back burner in the workflows where it would matter most? Earnix research puts AI in most or some workflows at 81% of insurers, and 92% of them run formal AI governance reviews, but fewer than one in three executives strongly agree those reviews are keeping pace with regulation. Aaron Wright, VP of Professional Services for the Americas at Earnix, spends his working life on the far side of that gap, and he argues it is not really a technology problem at all.
In this episode, Josh Hollander and Aaron work through what separates transformation from transformation theater, why modernization programs tend to fail three months before go-live rather than at it, and where AI is already moving numbers a CFO would recognize.
Guest Bio
Aaron Wright is VP of Professional Services, Americas at Earnix, and a Fellow of the Casualty Actuarial Society. He started out of school with a statistics degree as an actuarial analyst at Farmers Insurance, and was on the phone with a Department of Insurance defending the math behind a rate change within six months. He then spent roughly twenty years at USAA across pricing, underwriting, state management, catastrophe management and data science, closing out with a modernization mandate. He now leads the teams that arrive after a carrier has bought the technology and someone has to make it actually work.
Key Topics
-The governance gap - Formal reviews are nearly universal, but the confidence that they track where regulation is heading is not, so real operational decisions move at a measured pace.
-"We have AI" versus AI on the balance sheet - Aaron separates the places where AI is moving cost per ticket and handle time from the places where it is still hype.
-Where programs actually fail - Not at go-live, but months earlier, when somebody has to kill a customization or force a business unit to change and nobody holds the authority to make that call.
-The scaffolding problem - Carriers have built so many workarounds around legacy systems that the workarounds, not the systems, are often what hold them back.
-Parallel-process fatigue - Running the old process alongside the new one creates burnout that can kill a project's momentum, and only leadership can set expectations around it.
Vibe coding has a ceiling - Aaron will build a prototype to show the art of the possible, and he will not put it into a governed insurance environment.
-AI that enables expertise - One Earnix customer sees about twelve months of average tenure in the call center against eighteen months to train a representative fully, which is the kind of math that makes embedded, governed AI worth the effort.
Notable Quotes
"Saying you have AI and actually having it be something that hits the balance sheet that your CFO cares about is a very different thing."
"Most programs are not going to fail at the go live. They're going to fail three months before it, when somebody has to make that unpopular call and there's nobody with authority to actually make it happen."
"The average tenure for call center representatives is about twelve months at their company, and it takes eighteen months to get them fully trained. Well, that doesn't work."
"Our view of how AI should be used within insurance is to enable expertise."
Resources
Guest:
Earnix: https://earnix.com/
Aaron Wright on LinkedIn: https://www.linkedin.com/in/aaron-wright-fcas/
Host & Organization:
Joshua R. Hollander on LinkedIn: https://www.linkedin.com/in/joshuarhollander/
Horton International (USA): https://www.horton-usa.com/
Insurtech Leadership Podcast (LinkedIn Showcase): https://www.linkedin.com/showcase/insurtech-leadership-show
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