We've all heard some version of the same story this year: Many carriers and brokers are still on the fence about AI because of regulatory risk, errors and omissions (E&O) exposure, or "black boxes" they can't explain to a state department of insurance (DOI) examiner.
All of this is true. But none of it tells the whole story.
Spend time with almost any carrier's IT and operations leaders, and eventually they'll say the quiet part out loud: They're not avoiding AI; they're waiting for it to arrive inside the systems they already run. Those systems are the core platforms, such as Duck Creek, Guidewire, Majesco, Sapiens, and Insurity, that sit beneath a large share of the policies and claims on the books today.
The Real Bottleneck Isn't Fear. It's Architecture.
For most carriers, policy, billing, and claims data live in a core system: a multi-year, multimillion-dollar investment that the business treats as its "single source of truth." The vendor varies from carrier to carrier, but the obstacle their IT teams face is the same.
Bolting a standalone AI tool onto that architecture, even an elegant and streamlined one, isn't a plug-and-play decision. It's a multi-team integration project that typically stretches across several quarters, exposing the organization to delays, cost overruns, and shifting priorities. One claims technology vendor estimates that AI vendors lose roughly 40% of their projected timelines to integration complexity, whether the carrier runs Guidewire, Duck Creek, Majesco, or a custom legacy core.
That kind of complexity is often the difference between a pilot that launches and one that quietly dies in the backlog.
Naturally, carriers also scan the standalone AI market. They see dozens of point solutions for underwriting triage, claims scoring, and first notice of loss (FNOL) intake, and wonder: "Why integrate a third-party layer today when the core vendor is about to deliver the same capabilities natively?"
It isn't a hypothetical question. Nearly every major core platform vendor is moving to close this gap. Consider a few examples:
- Duck Creek launched its Agentic AI Platform in April 2026.
- That same month, Guidewire embedded ProNavigator, an AI assistant that gives adjusters context-specific guidance, into ClaimCenter and its other core applications. In August, Guidewire followed with its Qusar release, which added Guidewire-built claims and underwriting agents, including an agentic FNOL tool.
- Majesco announced that it's quadrupling its AI investment in 2026 to build an AI-native P&C platform and expand Majesco Copilot and its agentic AI capabilities.
- Sapiens has been rolling AI-based functionality into its CoreSuite releases.
- Insurity has committed an additional $100 million over two years to embed AI in its core systems, on top of the more than $50 million it had already invested in AI and R&D.
In each case, the pitch is essentially the same: The AI isn't a separate purchase; it's part of the system carriers already pay for.
That point is missing from many of the "why insurers are hesitant" stories in the media. Carriers aren't approaching AI cautiously simply because they're risk-averse. They're using their position as large, long-term platform customers to create a buyer's advantage. That leverage lets them be deliberate about their "build-versus-buy-versus-wait" calculations—and for many carriers, waiting has so far proved the more disciplined option.
Why Waiting Is a Deceptively Difficult Decision
The problem is that waiting has a cost, too, and that cost doesn't fall evenly. One AI underwriting vendor that sells a core-agnostic product has argued that carriers and managing general agents (MGAs) can't afford to wait for a full core system transformation before deploying AI and can't afford to be locked into a tool that works with only one platform.
Both concerns are valid, which makes waiting a strategic bet rather than an obvious answer.
There's also a quieter signal that undercuts the "carriers are simply being cautious" narrative. A May 2026 IA Capital Group survey of national and regional carriers found OpenAI's models in 91% of respondents' AI stacks, often delivered through Microsoft Copilot. Carriers aren't AI-averse. They're AI-selective, using their scale to adopt productivity tools quickly while holding the line on systems of record until their core vendors catch up. For many of them, that moment has either arrived or is very close.
The Exception That Proves the Rule
So why do carriers buy standalone tools at all? Because when a tool solves a problem that general-purpose AI, or the AI now arriving in core platforms, doesn't handle well, the calculus flips.
That's where most insurance-specific AI vendors stake their pitch: not "we're AI," but "we're AI trained on insurance data and workflows, which a horizontal model wrapped around your files isn't." It's an argument that still holds water. Shift Technology has made this case to carrier IT leaders directly, arguing that generic horizontal AI players often lack the data foundations and expertise needed to move a pilot into production. It's a real distinction, not just positioning. A general-purpose model can summarize a claims file. Reasoning reliably across coverage language, state-specific regulations, and loss histories is a different problem, and it's one that a system trained specifically on that data is, at least in theory, built to solve.
What sustains the "insurance-specific always beats generic" argument, then? The products carriers keep buying from these vendors, despite their preference for waiting until such capabilities arrive inside a core system, share one trait: They're widely believed to do the job better because of deep domain training, proprietary data, or a workflow too specialized for a core vendor to prioritize anytime soon.
Everything else, such as a general chat interface bolted onto a claims queue, is the kind of functionality most likely to show up natively in the next core release, whichever vendor delivers it. That's why carriers aren't rushing to pay for it twice.
What This Means If You're Evaluating Tools Right Now
A few things are worth doing before you sign anything:
- Separating "edge" AI from "core" AI. Marketing copy and service-desk triage carry low regulatory exposure and can run successfully on general-purpose tools today. Underwriting and claims determinations that touch policyholder outcomes are a different risk category, where the wait-for-native instinct makes more sense.
- Asking vendors for proof of successful integrations, not just a demo. A clean demo says nothing about how a tool behaves once it's wired into a decade-old core system. Ask for a named carrier reference on your exact platform and version.
- Pushing for a real audit trail. If a vendor can't produce output in a format that your internal compliance team and state DOI examiners would accept, that's a governance gap that will surface at the worst possible time.
- Ensuring pilot programs don't require a multi-year lock-in. Any AI vendor worth considering should be comfortable running a three- to six-month pilot on a limited book of business before asking for a long-term commitment.
- Watching your core vendor's product roadmap as closely as the pitch deck. If your platform vendor plans to deliver the capability you're evaluating in its next release cycle, that changes the decision, even if the standalone tool works well today.
- Testing whether the value is domain-specific. If a vendor's edge could be replicated by connecting a general-purpose model (for example, an enterprise assistant such as Microsoft Copilot, or an AI workflow that retrieves and summarizes documents) to your own policy forms, endorsements, claim files, and underwriting guidelines, don't count on that edge lasting once your core system catches up. If it depends on proprietary data or workflow depth that a core vendor is unlikely to build soon, that's the case worth paying for.
- Knowing the legacy exception. If a legacy system will continue to house and service existing policies for years before any platform migration, a general-purpose AI layer built over that system's documents and data, such as a search-and-summarize workflow for policy forms and claim notes, can still earn its keep as a bridge, even without a lasting edge.
The Differentiator
Most coverage of AI hesitancy in insurance treats reluctance as a problem of mindset: Carriers are cautious, regulators are strict, liability is scary. That may be true, but this framing overshadows a more relevant (and more interesting) story.
Carriers that are being deliberate aren't necessarily behind the curve or tech-averse. Many are making a sequencing bet: Let the core platform vendor absorb the integration risk, compliance burden, and audit-trail engineering, and then adopt AI as native functionality instead of a fragile add-on.
That strategy holds up well, with one condition: Waiting has to remain an active decision rather than a default. A carrier that sequences AI adoption around its core platform should still revisit that choice whenever a standalone tool offers an edge its core vendor can't match soon, using the tests outlined above. Handled that way, the real story in 2027 won't be whether insurance is "ready" for AI. It will be which carriers turned strategic patience into a well-timed rollout.
Sources:
- Decerto, AI Claims Processing: The Complete 2026 Guide for US Carriers, April 2026: integration complexity and the estimate that AI vendors lose roughly 40% of projected timelines to it.
- PRNewswire / Convr, Convr Delivers AI Underwriting Across Guidewire, Duck Creek, Sapiens, and Beyond, June 2026: the case against both waiting for core transformation and single-platform lock-in, from a core-agnostic AI vendor.
- Duck Creek, Duck Creek Launches Insurance-Native Agentic AI Platform and Unveils New Applications to Transform Underwriting and Claims, April 28, 2026: launch of the Duck Creek Agentic AI Platform.
- Guidewire, Guidewire Launches ProNavigator, Embedding Expert AI Insights into Insurance Workflows, April 16, 2026: ProNavigator embedded in InsuranceSuite (including ClaimCenter) and InsuranceNow.
- Guidewire, Guidewire Introduces Qusar Release to Help Insurers Build and Control AI Agents, Aug. 3, 2026: Qusar's Agentic Framework and Guidewire-built claims and underwriting agents.
- Zfort, Guidewire ClaimCenter vs Duck Creek Claims, August 2026: comparison of Duck Creek's Agentic AI Platform and Guidewire's Qusar release.
- Hesper AI, Claims management systems compared, May 2026: Guidewire's ProNavigator embedded directly into ClaimCenter.
- Business Wire, Majesco Accelerates P&C Market Leadership with 2026 AI Investment Surge, December 2025: Majesco quadrupling its AI investment and deepening Majesco Copilot and agentic AI capabilities.
- SEC filing, Sapiens Launches Enhanced CoreSuite for P&C, September 2025: Sapiens rolling AI-based functionality into its core platform releases.
- Business Wire, Insurity Named to the AIFinTech100 List of Leading AI Innovators in Financial Services, July 2026: Insurity's additional $100 million commitment, on top of more than $50 million already invested in AI and R&D.
- The Insurer, OpenAI dominates AI stacks as insurance industry moves from pilot to production, May 2026: IA Capital Group survey data on foundation-model presence in carrier AI stacks.
- Shift Technology, Making Agentic AI Work for Insurance webinar page, 2026: the case against generic horizontal AI models for production-grade insurance agents.
