Anthony R. O’Donnell | Insurance Innovation Reporter
Mutual insurers have long faced a structural dilemma. Deeply rooted in their communities and guided by a member-first ethos, they often lack the scale, capital, and technical talent enjoyed by large national carriers. The question is not whether technology can help close that gap, but whether it can do so without eroding the trust and identity that define the mutual model.
For Vineet Bansal, Chief Information & Technology Officer of The Mutual Group (West Des Moines, Iowa) artificial intelligence represents precisely that opportunity—if it is approached with discipline, restraint, and a clear understanding of what mutuals are trying to protect as much as what they are trying to modernize.
“AI is not a destination. It’s a journey,” Bansal says. “It’s not an IT project. It’s a transformation in how business gets done.”
From Automation to Assistance
Bansal is careful to demystify AI’s role in insurance operations. At its most basic level, he says, AI extends familiar automation by making it easier and more flexible—particularly through generative models that can interpret unstructured information. But the more meaningful gains come when AI begins to assist core insurance functions without attempting to replace human judgment.
“In underwriting, for example, we’re not using AI to make decisions,” Bansal explains. “We’re using it to become an assistant to the underwriter—especially in low-risk submissions.”
The same philosophy applies across claims and back-office operations. At The Mutual Group, AI is already being used to ingest first notice of loss (FNOL) emails, interpret incoming documentation, file records in enterprise content management systems, and create claim records in backend platforms before an adjuster ever touches the file.
“By the time the adjuster gets to the claim, they can spend more time on the claim itself and more time with the customer,” Bansal says. “They’re not doing repeatable work that can be eliminated.”
Why AI Matters Differently for Mutuals
While many of these use cases apply across the insurance industry, Bansal argues that AI has particular relevance for mutual insurers. Mutuals, he notes, are fundamentally about member protection and long-term relationships—often built at the local level through agents and deep community presence.
“A wrong decision or an AI hallucination can hurt a customer and erode trust that’s been built over decades,” he says. “That’s why responsible and compliant use of AI is so important for mutuals.”
At the same time, mutuals may be better positioned than larger carriers to adopt AI thoughtfully. Their smaller size can make them more nimble, allowing them to focus on targeted, high-value use cases rather than sweeping, capital-intensive transformations.
“With AI becoming a companion in the talent ecosystem,” Bansal says, “mutuals can start to shrink the gap with larger players. AI allows them to scale in ways they couldn’t before.”
The Real Barriers to Adoption
Bansal identifies three challenges mutuals must confront as they explore AI adoption.
The first is trust and liability. Because mutuals trade so heavily on credibility within their communities, mistakes carry disproportionate consequences.
The second is regulation and compliance. Fear of falling behind can tempt organizations to move too quickly, risking bias, noncompliance, or governance failures. “It’s not a race,” Bansal cautions.
The third—and often overlooked—challenge is business value. Bansal points to industry research showing that a majority of AI investments fail to deliver expected returns.
“Experimentation is important,” he says, “but you also have to be bold enough to stop an experiment if it’s not delivering the outcome you expected.”
Not Behind—Yet
Despite the rapid pace of AI development, Bansal rejects the notion that mutuals are already behind.
“AI is important, but it’s not a sprint,” he says. “Sometimes it’s actually good to not be the earliest entrant, because you can learn from others’ missteps.”
That window, however, is not open-ended. Mutuals that delay serious engagement indefinitely risk falling behind in ways that will be harder to recover from.
“Today, they’re not behind,” Bansal says. “If we were having this conversation a year from now, my answer might be different.”
A Stage-Gated Path Forward
Rather than big-bang deployments, Bansal advocates a staged approach to AI adoption—one that mirrors neither traditional software rollouts nor open-ended experimentation.
It starts with foundations: modern, API-driven core systems and reliable data. “AI is only as good as the data you feed it,” he notes.
From there, Bansal outlines a three-gate execution model. The first gate tests feasibility over a few weeks. The second introduces a limited production rollout with a human in the loop. Only after those stages are validated does a use case move into full production—with ongoing monitoring for model drift, hallucinations, and compliance issues.
“It’s never one and done,” he says. “You have to keep checking that the model is delivering the outcome you tested it against.”
Build, Buy, and Pressure on Core Platforms
Bansal also sees AI reopening long-standing debates around core systems. As AI-driven development lowers barriers to building software, open-source and services-led models are beginning to challenge traditional licensing-heavy platforms—particularly for midsize carriers and mutuals.
“Vendors will have to reduce costs and deliver more value,” he says. “The current model isn’t immutable.”
For The Mutual Group, which supports multiple mutual insurers, the focus is on platform-agnostic capabilities that can scale across organizations—while still recognizing that some carriers may choose to embed AI directly into their core platforms or develop proprietary capabilities where differentiation matters.
Competing Without Losing Identity
Throughout the conversation, Bansal returns to a central theme: AI should help mutuals compete without forcing them to become something they are not.
“AI is real, and it’s here to stay,” he says. “But mutuals don’t need to fear it. If they adopt it thoughtfully, it can make them bolder and stronger—while staying true to who they are.”
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