Agentic AI reshapes Insurance Ops

Across global financial centers, a fresh wave of automation is quietly reshaping how insurance ai connects carriers, brokers, and outsourced service providers.

Pace and the rise of agentic automation in insurance

What links London, New York, and Bermuda? According to Jamie Cuffe, each city stands as a major hub for the global insurance sector and its complex operations.

Cuffe grew up across all three markets while his father worked at Lloyd’s of London, often described as the world’s oldest and most prestigious insurance marketplace. That background, he argues, gave him a front-row view of how specialty coverage and back-office work really function.

After years working in startups, Cuffe has come full circle. Today he is the CEO and cofounder of Pace, an agentic AI startup built to handle insurance operations at scale, with a particular focus on business process outsourcing, or BPO, workflows.

From offshore outsourcing to AI-first insurance operations

Cuffe draws a direct historical line between the rise of the Internet and the growth of large offshore BPO providers. In his view, connectivity in the 1990s and 2000s fundamentally changed where insurance work could be done.

“The Internet is really what gave rise to outsourcing,” Cuffe said. “In the 1990s, 2000s, for the first time, you could basically do this work wherever you were and send it back.” However, he now believes a similar shift is underway as core processes move from human workers to AI systems.

“Now we are seeing the same thing, where all of this work that was being outsourced offshore can now be outsourced to AI,” he added. That said, he frames this not as a replacement of carriers and brokers, but as a restructuring of how repetitive, document-heavy tasks get executed.

Backing from Sequoia and the scale of the BPO opportunity

Pace, founded in 2024 by Cuffe, already counts Prudential, The Mutual Group, and Newfront among its customers. Moreover, the company has just closed a $10 million Series A round from Sequoia Capital, Fortune has exclusively reported.

Within insurance, the BPO market represents around $70 billion in annual spending, according to Cuffe. However, when including broader financial services operations tied to the sector, that number rises sharply to about $400 billion, underscoring the size of the addressable market.

“That is the part of the market that Pace really addresses,” said Bryan Schreier, the Sequoia partner leading the deal. Schreier previously worked with Cuffe at his last startup, Cheer, which sold to Retool in 2020.

Why AI fits the operational side of insurance

Schreier describes the operations side of insurance as a roughly $100 billion opportunity that is ripe for automation. In his view, Pace sits at the center of this shift toward more intelligent, software-driven processing.

“The thesis behind Pace is that the next wave of disruption on the operations side of insurance—this $100 billion market—is AI because it is a perfect fit,” Schreier said. Moreover, he argues the technology is arriving just as many incumbents look for new efficiency levers.

Both Schreier and Cuffe emphasize that modern AI systems excel at reading and interpreting massive amounts of text. That capability matters in insurance, where policies, submissions, endorsements, and claims files generate an extraordinary volume of documentation.

Lessons from the legal sector’s AI moment

Because these models are strong at parsing dense, technical language, they have already transformed parts of the legal industry. In recent years, mega-unicorns such as Harvey and Legora emerged by targeting legal workflows with specialized tools.

Cuffe believes that history offers a preview of what is coming next for insurers and brokers. However, he also stresses that insurance work, especially in commercial lines, tends to operate at a scale that far exceeds typical legal caseloads.

“Legal took off first because copilots were useful, and there were a lot of people doing that work,” Cuffe said. That said, he argues that the volume and structure of insurance submissions create an even stronger case for agentic systems.

The agent moment for insurance ai

In commercial and specialty insurance, carriers may face hundreds of thousands or even millions of submissions each year, Cuffe noted. In addition, some insurers must handle tens of thousands of claims while maintaining compliance and service levels.

Cuffe contends that this is exactly where the full promise of insurance ai starts to show. The combination of high document volume and repeatable processes creates ideal conditions for autonomous agents rather than simple suggestion tools.

“In insurance, the tasks are at much, much higher scale—hundreds of thousands or millions of submissions, tens of thousands of claims, for some of these insurers,” he said. “They need to be able to process that. The agent moment is what is unlocking the insurance industry for us.” Moreover, he suggests that the winners will be those who can pair deep domain expertise with robust agentic architectures.

As incumbents in London, New York, Bermuda, and beyond grapple with cost pressures and regulatory demands, players like Pace are betting that intelligent agents will become core to everyday workflows. If Cuffe and Schreier are right, the next phase of competition in insurance operations will be defined less by headcount in offshore BPO centers and more by the sophistication of the AI that underpins them.