You probably don’t think much about the technology behind your insurance policy. You pay the premium, file a claim when something goes wrong, and hope for a fair outcome. That routine hasn’t changed much in decades.
But behind the scenes, the insurance industry is undergoing one of the most significant technological shifts in its history. And this time, the changes won’t just affect how insurers operate internally. They’re likely to change what you pay, how fast your claims get processed, and how your next policy gets priced.
A February 2026 report from McKinsey & Company lays out exactly how AI is reshaping insurance across four major subsectors: brokers, managing general agents, software providers, and third-party administrators.
The consulting firm estimates that generative AI alone could unlock $50 billion to $70 billion in insurance industry revenue, with the biggest gains in marketing, sales, customer operations, and software engineering.
The real question is: What does this mean for you, the person actually buying and using insurance?
McKinsey’s ‘AI staircase’ explains how insurance is evolving
McKinsey describes the insurance industry’s AI adoption as a three-step progression it calls the “AI staircase.” The first step, traditional AI in the form of predictive analytics, is already well established. Insurers have been using it for fraud detection, pricing models, and risk assessment for years.
The second step is generative AI, which is beginning to reshape document-heavy tasks such as policy issuance, claims handling, and submissions processing. If you’ve ever filed a claim and wondered why it took so long to hear back, gen AI is designed to accelerate exactly that kind of bottleneck.
The third step could change everything
The third and most disruptive stage is agentic AI, systems that can autonomously manage entire workflows. McKinsey suggests these systems may eventually handle end-to-end processes, from purchasing a policy to certain types of risk assessment, with limited human involvement.
That doesn’t mean your insurance agent is disappearing tomorrow. McKinsey is clear that AI is more likely to reshape existing models than to replace them entirely.
But for you as a policyholder, the shift means faster responses, more personalized pricing, and potentially lower costs as insurers reduce their operational overhead.
Your insurance broker is about to get a powerful new tool
If you buy insurance through a broker, AI is already changing how that relationship works behind the scenes.
McKinsey reports that early gen AI use cases are improving efficiency by automating submission ingestion, matching carrier appetites, and enabling renewal copilots that help brokers cross-sell products.
McKinsey notes that AI-driven digital lead generation and targeting have reduced customer churn by up to 50% in some cases, by engaging clients with the right message at the right point in their journey.
Insurance brokers who adapt will serve you better
For you, this means a broker equipped with AI tools can spend less time on paperwork and more time giving you tailored advice. McKinsey points out that AI is reducing administrative friction by simplifying interactions across carrier websites for quoting, prefilling applications, and processing endorsements.
The brokers who adopt AI effectively will build bigger books of business and gain access to better data, which in turn should mean more competitive options for their clients. The ones who don’t adapt will fall behind, and their clients may notice the difference at renewal time.
AI could cut your policy quoting time from weeks to hours
Managing general agents, the specialized firms that underwrite and distribute insurance on behalf of carriers, are where some of the most dramatic AI gains are already showing up.
McKinsey reports that U.S. premium volumes channeled through MGAs have grown at about 14% annually over the last decade, with direct premiums nearly doubling from $47 billion in 2020 to $97 billion in 2024.
That explosive growth is now colliding with AI’s ability to make underwriting dramatically faster.
The speed gains for insurance quotes are measurable
McKinsey cites that specialty risk engineering tools can now generate initial risk assessments that cut quoting times from more than one month to just days. Commercial and specialty property and casualty models incorporating predictive win rates now deliver quotes in one to two hours instead of two to three days.
If you’ve ever waited weeks for a commercial insurance quote or dealt with a painfully slow renewal, those timelines are about to compress. Early forms of agentic underwriting “work cells” are already beginning to quote and bind simpler policies with minimal human intervention.
What AI underwriting means for your insurance premiums
Faster underwriting doesn’t automatically mean cheaper premiums. But it does mean more granular risk assessment. AI can perform highly detailed segmentation and risk scoring, which should mean you pay a premium that more accurately reflects your actual risk profile rather than a broad average.
For low-risk policyholders, that could be good news. For others, more precise pricing could mean higher premiums if your risk factors have been underpriced in the past.
Claims processing is getting faster, but there’s a catch
Third-party administrators (TPAs), the companies that handle claims processing for insurers, are another area McKinsey highlights for AI disruption. TPA deals have grown at about 15% annually over the past five years, according to PitchBook data cited by McKinsey.
These firms sit on transaction-level servicing data that makes them well-positioned to deploy AI for speed, consistency, and better service levels.
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The Evident AI Use Case Tracker backs this up. Insurance AI use cases grew 87% year over year, with about 40% of insurers now reporting tangible business outcomes, noted Insurance Edge.
Agentic AI also accounted for 21% of public AI deployments in the sector in Q4 2025, with the majority focused on claims management.
The revenue model problem you should know about
Here’s where it gets complicated. McKinsey flags an important tension: Many TPA arrangements are still based on headcount or activity-based pricing. Under those models, automation can actually pressure the TPA’s top-line revenue, even when performance improves.
Better outcomes and higher accuracy don’t always translate to higher compensation. Faster claims processing is good, but if the companies handling your claims aren’t incentivized to invest in AI because their pricing models penalize efficiency, the benefits may take longer to reach you.
Wall Street is already pricing in the AI disruption for the insurance industry
The financial industry isn’t waiting around to see how this plays out. Bank of America identified more than $15 billion in commissions paid to independent agents in 2025 across just six major carriers, largely in low-complexity personal lines and small commercial business, per Fortune.
BofA’s thesis is that these routine policies are exactly where AI chatbots can effectively replace human agents.
Insurance broker stocks dropped roughly 9% after news broke in early 2026 that digital insurance companies had launched ChatGPT-powered assistants for personalized home insurance quotes.
Analysts at multiple firms, including Berenberg and UBS, called the sell-off overdone, but the signal was clear: The market sees AI as a real force in insurance distribution.
The bigger picture for insurance investors
McKinsey’s report identifies four priorities for insurance investors: embedding AI evaluation across the deal lifecycle, building a firm-wide AI playbook, running scenario plans for different adoption curves, and projecting how AI will change talent models.
The firm estimates that current technologies could theoretically automate more than half of current U.S. work hours, with two-thirds of those hours devoted to nonphysical work similar to what’s common across insurance.
If you own shares in insurance companies or financial services ETFs, these shifts should factor into your investment thesis.
The companies that integrate AI effectively will likely see margin expansion. Those that don’t could face competitive erosion.
How to navigate your insurance decisions as AI reshapes the industry
The AI transformation of insurance is happening now, not five years from now. Here are specific steps you can take to stay ahead of the curve as a consumer and policyholder.
- Compare quotes more frequently: As AI enables faster and more personalized pricing, your current premium may not reflect the best available rate. Shop your auto, home, and health insurance at every renewal, not just when costs spike.
- Ask your broker about their technology: Brokers who use AI-powered tools for carrier matching and risk assessment can offer you more competitive options. If your broker can’t explain how they’re using technology to find you better coverage, consider one who can.
- Expect faster claims, but review outcomes carefully: AI-driven claims processing can resolve straightforward cases faster, but complex claims still need human judgment. Don’t accept an AI-generated settlement without reviewing it against your actual damages and coverage.
- Understand that “personalized pricing” cuts both ways: AI lets insurers assess your risk more precisely. If you maintain good credit, a clean claims history, and updated home or vehicle maintenance, more granular pricing should work in your favor. If not, you may see higher premiums than before.
- Watch for embedded insurance products: AI is enabling insurers to offer coverage at the point of purchase, built into things like e-commerce, ride-sharing, and banking platforms. These micro-policies can fill gaps in your coverage, but read the terms before you buy.
The insurance industry’s AI race is just getting started
McKinsey’s report makes one thing clear: AI in insurance is not a future possibility. It’s a current reality with measurable results. Industry AI spending is expected to grow by more than 25% in 2026, and the global AI in insurance market is projected to grow at a 32.3% compound annual growth rate through 2035, according to InsightAce Analytic.
For everyday policyholders, the shift will unfold gradually. You probably won’t wake up one morning to an AI agent managing your entire insurance portfolio. But the small changes, faster quotes, more precise pricing, quicker claims, and new product options are already accumulating.
Insurers, brokers, and MGAs that invest in AI now will likely offer better products at more competitive prices. The ones that don’t will struggle to keep up.
And as a consumer, the best thing you can do is stay engaged, compare your options, and treat your insurance decisions with the same attention you give to your investment portfolio.
Related: When AI meets law enforcement: The future of predictive policing
