CHRIS MCLAUGHLIN
VERTESIA
The real problem, according to Keith Schlosser – a 36-year veteran and Insurance Transformation Advisor at Vertesia – is hiding in plain sight: the crushing weight of the industry’ s own history.
Decades of mergers and acquisitions, Keith argues, have created a tangled web of legacy platforms, trapping data in silos and making innovation feel nearly impossible.
Insurers are facing a clear choice: break through the complexity or fall further behind.
CHRIS MCLAUGHLIN
CHIEF REVENUE OFFICER
Chris McLaughlin is the Chief Revenue Officer, where he leads the company’ s global go-to-market strategy and helps customers rapidly build and intelligently operate AI apps & agents. He brings more than 25 years of experience in enterprise software, with leadership roles spanning highgrowth startups and large global organizations. Prior to Vertesia, Chris served as CRO at Hyland Software, a $ 1.2B leader in content services, and as Chief Product & Marketing Officer at Nuxeo, where he helped increase revenue by over 500 %. He has also held senior executive roles at LumApps, Dell EMC, and Thunderhead.
The automation paradox in insurance For decades, insurers have tried to innovate their way out of complexity one piece at a time. They buy a point solution for claims, another for renewals and a third for underwriting. Each tool promises to reduce manual work and, in isolation, it often does. But this approach has created a monster.
This is the“ automation paradox” – each solution adds complexity, increasing system fragmentation and creating more – not less – work. This cycle of buying, integrating and maintaining separate tools is why conventional automation has failed to truly transform insurance.
Traditional automation is rigid. Operating through predetermined logic paths, these systems are a series of‘ if-then’ statements that can fail the moment a situation veers offscript. If a claim amount exceeds a set threshold, it gets routed to an adjuster. If a policyholder’ s address is missing, it gets flagged.
Agentic AI represents a fundamentally different approach. It doesn’ t follow a script; it follows a goal. Chris explains,“ agentic tools excel in complex processes working with a variety of different documents where we’ re asking the AI agent to reason its way through a specific task.” It’ s designed to handle the unpredictable reality of insurance, where no two cases are ever truly the same.
Keith believes agentic AI isn’ t just another technological advancement but a transformational advantage for insurers, and sees it as the key to finally breaking free from the industry’ s fragmented past.
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