(Image source: Guidewire.)
For John Mullen, President, Guidewire (San Mateo, Calif.), the question is not simply how artificial intelligence will change insurance workflows. It is how insurers will create the operating context in which AI can act reliably, auditably and in accordance with the rules of insurance.
That view reflects Mullen’s role at Guidewire, where he oversees field functions including sales, customer success, professional services, solution and industry advisory, and field engineering. It also reflects his view that the property/casualty insurance industry is entering a moment when business and technology can no longer be treated as separate domains.
“It would be very difficult to overstate the impact,” Mullen says of AI.
Mullen characterizes AI as a general-purpose technology, but one that differs from earlier technology shifts. Previous waves, he suggests, helped organizations scale operations or improve prediction. AI, by contrast, can increase both scale and expertise.
John Mullen, Guidewire. Source: Guidewire. (Click to enlarge.)
“It’s the first generally available general-purpose technology that addresses scalability of a function or an organization and increased expertise of an organization, a function or society in equal measure,” Mullen comments. “That’s really why you can’t overstate it.”
AI as Scale and Expertise
For insurers, Mullen says, that dual effect will be felt not only in productivity but in how companies organize work, make decisions and connect business strategy to technology execution. He argues that AI will drive a convergence of business and IT more powerfully than any prior technology wave.
“There is no longer an opportunity where somebody can say, ‘I’m in the insurance industry, I’m an IT professional,’ or, ‘I’m in the insurance industry, I’m a business professional,’” Mullen says. “Those lines can no longer be drawn. You have to be both if you want to navigate and lead in this industry.”
Mullen sees that change emerging as many insurers move faster than they have during previous technology cycles. Some carriers, he says, are already past experimentation and into early scaling. Others remain in proof-of-concept mode. Still others are building AI assumptions into budgets as a way of pulling organizational change forward.
“The most pervasive thing is: learn—go fast enough to learn fast enough so you can continue to reshape what you want your organization to look like in the face of AI and how you want to lead in the face of AI,” Mullen says.
That does not mean moving without discipline. Mullen repeatedly returns to the need to balance speed with durability. Insurers need agility in product development, risk selection, pricing and customer interaction, but they must also preserve the reliability, auditability and regulatory defensibility required to operate at scale.
“The conversations I’m having with customers are about the balance of agility and durability,” Mullen says. “How do you, as a leader in today’s environment, balance product speed-to-market, risk selection and pricing, and the agility required to do that with the durability required to still run an insurance enterprise at scale?”
A Field View of Carrier Change
Mullen’s perspective is shaped by Guidewire’s proximity to carriers and by his own long history in insurance technology. He says Guidewire’s customer relationships and partner ecosystem are among the company’s most important strategic assets.
“I love this industry,” Mullen says. “Guidewire’s two greatest strategic assets are proximity to customers, and the willingness of customers to work well with Guidewire, and Guidewire’s willingness to listen and act responsibly against that, and our ecosystem of partners.”
Mullen says he returned to the P&C insurance industry after spending five years outside it, and that the return reinforced his appreciation for the industry’s social function.
“In order to unlock the full power of AI and build an agentic insurance carrier, you have to be running on a modern core platform.”— John Mullen, Guidewire
“Everybody finds their way into insurance through some funny story that they love to tell,” he says. “But the reason they stay is always the same. It’s the commitment to the outcome and service of society.”
That sense of insurance as a social mechanism informs the way Mullen talks about AI. He does not describe the technology only as a way to reduce labor or accelerate processes. He argues that AI can prompt insurers to rethink the exchange of value across the insurance chain, from distribution and underwriting to claims, reinsurance and capital.
“It will prompt a rethinking of the exchange of value over the long measure of time,” Mullen says. “In the near term, speed and competitiveness are going to put carriers under more pressure for competition and change management than they’ve ever seen.”
One reason the industry is moving quickly, Mullen suggests, is that generative AI did not enter the market as a technology-only solution.
“It didn’t come as an enterprise technology,” Mullen says. “It came to the world as a generally available technology.”
That created its own management challenge, because employees were already experimenting with the tools in their personal lives.
“Those that were super curious were using it anyway,” Mullen says. “Getting on that train and driving that train toward using it for the outcome of the enterprise was absolutely critical for leaders to get their arms around quickly.”
Where Agentic Insurance Needs Context
The deeper question for core systems is what happens when AI begins not only to summarize or assist, but to act. Mullen says the agentic insurance carrier will still need a reliable operating foundation because AI agents will require the same business context that human users have historically drawn from core systems.
“In order to unlock the full power of AI and build an agentic insurance carrier, you have to be running on a modern core platform,” Mullen says. “Just like the human actors interacted with a core operating system, the agentic actors will need that same foundational element for predictability, scalability and reliability.”
For Mullen, that context includes the policy, claim, billing and underwriting information that enables decisions to be made correctly and repeatedly. It also includes the rules and controls that make those decisions auditable and suitable for a regulated industry.
“The rules of insurance will remain very much the same,” he says. “Regulation will also use AI, so the friction in regulation should go down materially, but the protection of the customer is not going to change.”
“We’re no longer talking about call avoidance metrics. We’re no longer talking about reducing call times. We’re talking about enabling the maximum understanding of the customer intent and customer need.”— John Mullen, Guidewire
That is where Mullen makes the case for the continuing importance of modern core systems. AI can act only as well as the context around it allows. In insurance, that context is not generic data. It is coverage logic, reserving guidelines, operating procedures, pricing context, claims history, billing status, regulatory constraints and customer communications.
“Context is everything,” Mullen says. “In order to become an agentic carrier, you need to be operating on a modern, reliable core system because the context upon which your agents operate, the context upon which your insurance rules exist, are absolutely fundamental.”
AI’s probabilistic capabilities, Mullen suggests, must be balanced by deterministic insurance rules and durable operating processes. The goal is not merely to generate answers, but to generate answers and actions that are appropriate, repeatable and improvable.
“That context piece is absolutely critical,” he says. “You need to be making all of your IT investments toward that durable context.”
From Answers to Actions
Guidewire’s approach, Mullen says, begins with openness. He describes open API surface area and open Model Context Protocol surface area as fundamental to supporting customer choice while providing the durability carriers need.
“Guidewire’s intent is to remain open in that architecture to give our customers the choice for the agility that they want and also provide the durability that they need,” Mullen says.
He describes Guidewire’s AI strategy as operating across several layers: agentic capabilities within Guidewire applications such as ClaimCenter, PolicyCenter and BillingCenter; native AI applications such as UnderwritingCenter and PricingCenter; and autonomous agents that sit at the enterprise level.
The company’s acquired ProNavigator technology is central to delivering agentic capabilities into Guidewire’s applications.
“ProNavigator is the vehicle by which Guidewire delivers agentic capabilities into the Guidewire application suite,” Mullen says.
Mullen describes those capabilities as a staged progression. First, AI can provide answers in the context of a user’s work. Then it can provide suggestions, flagging issues or recommending next steps. Finally, it can be configured to take actions inside the workflow.
“It provides for the user, in the carrier context, in the customer context, in the claim context, the policy context, the billing context,” Mullen says. “It pulls all of that together agentically and presents to the human worker the ability to answer inquiries, like, ‘What should I do next?’”
From there, the technology can suggest actions or warnings, such as confirming special handling instructions, checking policy coverage, identifying a potential work injury or highlighting a change to a claim file.
“It provides those suggestions to the claim adjuster right at the point of need and at the moment of highest impact,” Mullen says. “And then the third element is taking those actions.”
Mullen is careful not to suggest that every process becomes fully autonomous at once. Instead, he describes a progression in which workflow becomes less visible to the user over time.
“There is no longer an opportunity where somebody can say, ‘I’m in the insurance industry, I’m an IT professional,’ or, ‘I’m in the insurance industry, I’m a business professional.’ Those lines can no longer be drawn.”— John Mullen, Guidewire
“Over time, the workflow will move more to the background, and the work and the decisions themselves will move more to the foreground,” he says.
That progression may be especially important in claims, where first notice of loss is among the most visible early use cases. Mullen also points to commercial underwriting as an area likely to be profoundly changed, especially because of the amount of unstructured information exchanged between brokers and carriers.
“I think the exchange of underwriting information in the world of commercial insurance between broker and carrier will be the most fundamentally changed, just because of the amount of unstructured data,” he says.
Mullen also points to risk selection and pricing, product design and the exchange of information between primary carriers and reinsurers as areas where AI can create meaningful gains.
“The ability to get data to the right place in the enterprise without the constraints of human conversation, or without the interpretation of some debate elements, is going to be extremely powerful,” he says.
The Human Side of Faster Claims
Mullen also raises a less obvious consequence of AI-enabled claims work. If AI removes administrative burden and reduces the process time between customer interactions, it may also reduce the natural pauses that claims professionals have historically had between emotionally intense conversations.
In claims, Mullen says, AI should allow people to focus on the work that depends on their expertise rather than merely their presence in the process. That includes the ability to deliver a more compassionate and brand-aware claims experience.
“We’re no longer talking about call avoidance metrics,” Mullen says. “We’re no longer talking about reducing call times. We’re talking about enabling the maximum understanding of the customer intent and customer need at that point in time, because the cost to support that is far less than it was.”
That shift could improve service. But it could also intensify the emotional demands on adjusters, especially in catastrophic events.
Mullen says the traditional claims workflow sometimes created a “natural mental break” for the adjuster after an empathetic exchange with a customer. As AI compresses administrative work, those breaks may become shorter.
“How do you build in the mental health awareness and all of the components that make sure that the claims adjusters who don’t have that time between those empathetic moments are cared for?” Mullen says. “It’s going to be exhausting, and we have to really think and care for that.”
The observation complicates the usual AI productivity story. Faster work is not automatically easier work. If AI removes low-value tasks, insurers may also need to redesign jobs so that the remaining human work is sustainable.
AI-Enabled Implementation
Mullen says Guidewire is also applying AI to implementation and development. Core system projects have historically been large undertakings, and Guidewire is investing in tooling to help its professional services teams, systems integrators and customer developers reduce the cost and time required to move to cloud and extend Guidewire systems.
“These core system projects are big,” Mullen says. “We’ve been making material investments in tooling and enabling, through AI, our own professional services team and the ecosystem to be able to develop to dramatically reduce the cost and timeframe of implementations.”
Guidewire is also using Claude AI for its developer harness, while allowing customers building agents on top of Guidewire’s context to choose among frontier models.
“When our customers go to build agents on top of our MCP context, they can pick any frontier model to do it in, ” Mullen says.
That reflects the broader architectural point Mullen makes throughout the conversation. Guidewire’s position is not that one model or one application will determine the future of insurance AI. It is that carriers will need open, durable, updatable systems of context on which AI agents can safely operate.
Closing the Trust and Value Gap
For Mullen, the long-term opportunity is larger than workflow efficiency. He argues that AI can help insurers become more relevant, dynamic and responsive to customers, while preserving the discipline required to underwrite, price, service and indemnify risk.
“Agentic is a means to an end,” Mullen says. “The end is becoming more relevant and dynamic and agile in support of customers and in support of society.”
That ambition returns Mullen to the social purpose of insurance. He says the industry has long suffered from a gap between the value it provides and the trust it receives from society. AI will not close that gap by itself, but Mullen believes it gives insurers new capabilities to narrow it.
“For a long time, this industry has suffered between this kind of trust and value gap,” Mullen says. “The value that the industry offers to society and the trust that the industry has garnered with society has been a gap too big for too long.”
After three decades in insurance core systems, Mullen says he is more optimistic than ever about the industry’s ability to improve that relationship.
“I’ve never felt more optimistic about us being able to lay down all of the capabilities to close that gap,” he says, “and improve that relationship.”