Many people in insurance want AI, but they're having a hard time using it effectively in the workplace.
Their AI struggles stem from many factors, such as an absence of clear policies and training; and some job-hunting underwriters even look into potential employers' AI capabilities when making a decision.
But AI is creating untapped opportunities beyond what it can deliver directly to employees. The AI-driven boom in data-center construction — with an estimated $750 billion in projects this year according to Swiss Re — creates potential business for insurers that want to combat some of the changes that are eroding their revenue. Read below to learn more.
68% of agents want AI but only 8% use it, survey finds
Independent agents are bullish on AI but struggling to act on it: 68% of agencies report strong interest, yet only 8% are currently using the technology, according to the Big I Agents Council for Technology trends report. More pressing, 56% have no written AI policy in place, and 44% rely solely on peer-to-peer training. Carriers can capitalize by building flexible distribution infrastructure that supports diverse agency models — from main street shops to AI-driven operations — rather than betting on a single channel strategy. Agencies that adopt AI report gains in marketing, legal review and analysis functions previously inaccessible to small shops.
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AI strategy is now a retention tool for underwriting talent
Insurers without a clear AI roadmap risk losing underwriting talent to competitors that have one, according to a Sixfold survey of 543 underwriters and executives across the U.S. and Europe. Seventy-seven percent of executives worry underwriters will defect to firms with stronger AI capabilities, and 72% of underwriters say a structured AI strategy would factor into their next job decision. Sixty-nine percent say their current organization's AI approach makes them more likely to stay. With 71% of organizations already using AI regularly in underwriting workflows and 70% of hiring leaders prioritizing AI-comfortable candidates, lagging firms face compounding risk — both operational and human capital.
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60% of insurers expect AI transformation within 3 years
Despite 66% of insurers planning increased AI spending over the next 12 to 24 months and projected industry investment reaching $80 billion by 2032, operational scaling remains limited — only 30% of insurers have scaled AI in claims and 23% in underwriting. The gap between visible AI activity and genuine transformation is widening. Closing it requires four priorities: establishing clean, governed data and clear process ownership before deploying tools; redesigning workflows rather than layering AI onto existing ones; treating adoption as a change management effort from day one; and building explainability into AI outputs to earn trust from adjusters, underwriters and regulators alike.
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Aerial imagery gaps leave AI property assessments flawed
Near Space Labs combines drone-level resolution with satellite-scale coverage to give insurers fresher property data — images no more than one to two quarters old, versus the two-year-old data common in current workflows, according to Rema Matevosyan, the company's founder and CEO. That currency matters most in high-risk states like California and Colorado, where vegetation health around wildland-urban interface properties directly drives wildfire exposure. The platform also extends coverage to rural and smaller markets typically bypassed by airplane-based solutions. A key limitation to flag: current AI struggles with visual data interpretation — misidentifying ash-filled pools as undamaged, for instance — meaning human review remains essential until multi-step AI workflow models mature.
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AI data centers offer insurers growth opportunity
AI data center investments are projected to reach $750 billion in 2026, creating substantial underwriting opportunities in construction, operational and accumulation risk — some facilities carry asset values exceeding $20 billion before technology installation. Swiss Re's annual world insurance report recommends combining risk engineering, alternative risk transfer and financing rather than relying on traditional coverage alone. The opportunity comes as overall real global premium growth is forecast to drop from 3.9% in 2025 to 1.3% in 2026, with non-life real premium growth hitting a cyclical bottom. Geopolitical instability and supply-chain fragmentation are accelerating demand for specialist trade and business-continuity solutions.
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Lloyd's Lab: 60% of incubator startups now using AI
Lloyd's Lab, the Lloyd's insurtech incubator now in its 16th edition, reports that 50% to 60% of participating startups are using AI — either as a core focus or to augment existing capabilities. Conducted with The Hartford and Google Cloud, the program gives insurtechs access to Google DeepMind systems and hands-on mentorship from carriers already deploying AI in production. The Hartford is integrating IoT home-sensor data into AI models via Google Cloud; Lloyd's is applying AI to global regulatory reporting and plans to expand it into underwriting decisions. For carriers evaluating AI partnerships, the program illustrates a structured model for translating startup innovation into operational deployment.
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This roundup was created with AI assistance. A Digital Insurance editor reviewed each item before publication.
