AI in the Driver's Seat: Coverage Denials, Broker Strategy, and the Executive Priority Shift
AI moved from strategic aspiration to operational imperative this week, with new data showing it now commands the top priority of insurance executives globally, regulators and carriers clashing over its role in coverage decisions, and technology reshaping how brokers compete for business.
46 of 100 — neutral. Executive urgency around AI is at an all-time high, but a widening gap between strategic priority and organizational readiness, plus an unresolved state-federal fight over AI claims decisions, keeps this week in neutral territory rather than clearly favorable.
AI Becomes the Industry’s Top Priority, but Preparedness Lags
A sweeping new survey from the International Insurance Society makes clear that artificial intelligence has crossed a threshold in the insurance industry: it is no longer something executives are planning to address but something they feel urgency about right now. According to the IIS 2026 Global Priorities Report, 71% of executives across insurers, brokers, and risk management organizations named AI as their top business priority, by a significant margin.
The report, drawing on responses from executives associated with the IIS, The Institutes, the Insurance Information Institute, and several other leading bodies, captures an industry navigating simultaneous pressures. Financial market volatility topped economic concerns at 62%, and regulatory uncertainty surged to the leading political and legal worry for the first time in five years, overtaking cybersecurity. Executives are now explicitly concerned about a patchwork of AI-related regulatory frameworks at both state and federal levels, an environment that promises to complicate underwriting decisions and product design across multiple lines.
Technology modernization is also now ranked as a top social and environmental priority by 51% of respondents, surpassing climate risk for the first time in the survey’s six-year history. That is a notable shift, one that signals how thoroughly AI and automation have permeated the strategic planning conversation at the highest levels of the industry.
Yet the report surfaces a meaningful tension. Despite AI’s dominant status, 17% of executives acknowledged their organizations remain unprepared to manage its full implications, a figure that ranked AI second-to-last only to blockchain in terms of organizational readiness. Combined with a deepening talent shortage in data analytics and underwriting, the industry faces a gap between strategic intent and execution capacity that risk managers and their carrier partners will need to manage carefully in the months ahead.
The combination of hard market signals, including tighter underwriting margins, social inflation, and unpredictable jury verdicts, alongside the pressure to modernize creates real stakes for firms that fall behind on AI adoption. For brokers and risk managers, understanding where their carrier partners stand on AI readiness may increasingly inform placement strategy and program design.
— R&I Editorial Team at Risk & Insurance
The AI Coverage Denial Fight: States Move In, White House Pushes Back
A full-scale policy conflict over artificial intelligence in health insurance claims decisions is now playing out at the state and federal levels simultaneously, and the outcome will have far-reaching implications for how coverage determinations are made, challenged, and litigated. At its center is the question of who gets to set the rules: Washington or state capitals.
Across the country, at least nine states have passed or are actively advancing legislation to constrain how health insurers use AI in prior authorization and claims denial decisions. The coalition spans traditional partisan lines in ways that are politically unusual. Republican governors including Ron DeSantis in Florida have embraced AI oversight, with DeSantis introducing an AI Bill of Rights that includes insurer algorithm inspection requirements, while Democratic-led states like Maryland and Illinois enacted their own restrictions in prior years.
At the same time, the Trump administration has moved in the opposite direction. A December executive order sought to preempt state AI governance efforts, framing the issue as a national competitiveness imperative. The administration is also actively piloting AI-driven prior authorization within the Medicare program. Legal scholars have questioned whether that preemption is constitutionally grounded, noting that Congress has declined twice to pass such a provision, which traditionally has been the source of preemption authority.
For the insurance industry, the liability picture is sharpening. Class action lawsuits have accused major health insurers of using AI to deny claims at scale with insufficient physician review. New Stanford University research raises an additional concern: training AI on historical claims data means training it on a record of wrongful denials, potentially automating the same errors at far greater speed and volume.
Insurers, for their part, have been careful with their public framing. Major carriers have characterized AI as an efficiency tool that speeds approvals rather than drives denials, but those characterizations are being tested in congressional hearings and courtrooms. For underwriters in liability lines, D&O, and E&O, the litigation trajectory here warrants close monitoring.
— Darius Tahir and Lauren Sausser at KFF Health News
From Order-Taker to Trusted Advisor: How AI Is Remaking the Broker Role
The long-running debate about whether AI will replace insurance brokers is giving way to a more useful question: how is it changing what brokers actually do, and who will benefit from that change? Writing in Carrier Management, Tracie Thompson, Global Head of Strategic Clients at Cytora, argues that the firms positioned to win are those using AI to shift the broker function away from transactional renewal cycles toward continuous, data-driven advisory work.
The practical applications are already visible at larger broking organizations. AI is being applied to benchmarking, coverage gap analysis, and portfolio review in ways that allow brokers to deliver faster and more consistent insight to clients. In specialty lines, where placements are complex, involve multiple insurers, and require judgment about how risks should be layered and shared, AI is helping streamline how these structures are assembled and how appropriate capacity is identified. The result is reduced placement friction and shorter timelines to bind coverage, while still preserving the broker’s core judgment role in how deals are ultimately constructed.
Revenue implications are also taking shape. Brokers with better AI-enabled visibility into client exposures are identifying gaps in coverage and underinsurance more consistently, and using structured data to make prospecting activity more targeted and measurable. Managing general agents are adopting similar approaches, in some cases moving more quickly than traditional broking firms. Thompson points to Augmented UW Ltd. as an example of a model built around automated underwriting and end-to-end risk placement, demonstrating how newer entrants can scale without legacy operational constraints.
Challenges remain. Legacy systems continue to limit data quality at many firms, regulatory requirements still govern how AI can be applied where customer outcomes are directly affected, and there is a genuine skills gap in how brokers interpret and act on AI-generated outputs. Client trust also depends on transparency, particularly when AI-supported processes influence placement recommendations.
The article’s broader message is relevant for underwriters and risk managers alike: firms that combine data infrastructure, technology, and advisory capability are strengthening their competitive position. Those relying on fragmented information and manual processes will find it harder to differentiate at a time when the quality of insight increasingly drives client retention.
— Tracie Thompson at Carrier Management
URL: https://www.carriermanagement.com/features/2026/04/15/286761.htm
This Week’s TL;DR
The insurance industry entered the week with a clear signal from its own leadership: artificial intelligence is no longer a future-state priority but an immediate operational concern. The IIS Global Priorities Report confirmed that 71% of insurance executives have placed AI at the top of their strategic agenda, even as nearly one in five acknowledged their firms remain unprepared to fully address it. That tension between urgency and readiness defines the moment the industry finds itself in heading through the second quarter of 2026.
At the same time, AI in insurance is increasingly subject to scrutiny from outside the industry. The fight over AI-driven coverage decisions in health insurance is intensifying, with states pursuing regulation at a pace that the Trump administration is now actively working to slow. The constitutional questions are real and unresolved, but regardless of how the federal-state standoff plays out, the litigation environment is already shifting. Class action lawsuits targeting AI-assisted claim denials, combined with new academic research on the risks of training models on historically flawed data, are creating a liability landscape that casualty underwriters, D&O specialists, and E&O teams will need to factor into their thinking.
On the distribution side, the broker evolution continues. The technology tools now available are shifting the nature of the broker-client relationship from annual transactional touchpoints toward continuous engagement built on real-time data. This is an opportunity for firms that invest deliberately, and a structural challenge for those that do not. MGAs are also demonstrating that newer entrants can use automation to scale without the overhead burdens that constrain traditional broking organizations.
Taken together, this week’s coverage reflects an industry in which AI is simultaneously the dominant strategic priority, the source of growing legal and regulatory exposure, and the driver of competitive differentiation across distribution. Risk managers, brokers, underwriters, and analysts who stay close to all three dimensions will be better positioned to navigate what promises to be a consequential stretch ahead.