The insurance industry finds itself at a fascinating crossroads. While AI dominates board meetings across every sector, the claims space tells a more nuanced story: one of cautious optimism tempered by legitimate concerns about trust, accuracy, and regulatory compliance. A recent survey commissioned by our team at Wisedocs and conducted by PropertyCasualty360 reveals this paradox in detail, offering insights into how claims professionals view AI adoption and what it will take to gain trust across the industry.
The 2025 survey, "AI in Claims: The 4x Trust Effect of Human Oversight," polled claims professionals from PropertyCasualty360's audience, including adjusters, carrier-side claims managers, and third-party service providers. What emerged was a clear picture of an industry ready for technological transformation, but only under the right conditions.
Key Insight #1: The Trust Deficit
The survey's most striking finding centers on trust, or, rather, the lack thereof. Only 16% of respondents expressed medium or high trust in AI-generated outputs when used independently, with a mere 2% indicating high trust. This skepticism isn't born from technophobia but from practical concerns rooted in the high-stakes nature of claims work.
The primary barriers to AI adoption reveal why claims professionals remain cautious. Accuracy concerns topped the list at 54%, followed closely by compliance and regulatory risks at 49%, and integration challenges with existing systems at 45%. These aren't abstract worries – they reflect the reality that claims decisions carry significant legal, financial, and reputational consequences.
This cautious approach becomes even more apparent when examining current adoption patterns. A substantial 58% of respondents either don't use AI in their claims process or are uncertain whether their organization employs AI tools. This uncertainty itself is telling, suggesting that AI implementation in many organizations remains fragmented or poorly communicated.
Yet this trust deficit doesn't reflect a wholesale rejection of technology. Instead, it reveals an industry that understands the stakes involved and demands proven reliability before embracing new tools.
Key Insight #2: The Human-in-the-Loop (HITL) Solution
The survey's most compelling discovery lies in how dramatically trust levels shift when human oversight enters the equation. When respondents were asked about their confidence in AI outputs validated by expert reviewers, the percentage expressing medium or high trust jumped to 60% from 16%. Those reporting high trust soared from just 2% to 22%.
This trust multiplier effect varies by current AI usage. Among occasional AI users, 33% report medium or high trust in the technology, compared with 0% among those who don't use AI and have no adoption plans. This suggests that familiarity breeds confidence, but only when paired with appropriate oversight mechanisms.
Key Insight #3: Efficiency Over Everything
While trust in AI's decision-making capabilities remains limited, its value as a productivity enhancer is widely recognized. An overwhelming 75% of respondents believe AI can boost efficiency through improved speed and resource optimization, with nearly half (49%) also citing productivity gains via increased work volume capacity.
The areas where claims professionals see the most potential for AI impact align with administrative processing tasks rather than strategic decision-making. Document automation and data extraction led the way at 69%, followed by operational efficiency and workflow automation at 57%. Claims decision support, while still significant at 31%, ranked lower – a telling indication that professionals want to handle the groundwork, not the judgment calls.
This pattern extends to perceived benefits for claimants, as well. Respondents believe AI's primary contribution will be reducing administrative delays (71%) and enabling faster claims resolution (60%). They're less optimistic about AI improving accuracy (25%) or transparency (18%), suggesting a realistic understanding of current AI capabilities and limitations.
Key Insight #4: Industry Readiness for Adoption
Several broader trends emerge that paint a picture of an industry poised for significant change, albeit on its own terms. The claims sector's approach to AI adoption reflects a mature understanding of both the technology's potential and its limitations. The emphasis on efficiency gains over accuracy improvements reveals a pragmatic strategy. Claims professionals recognize that AI's current sweet spot lies in handling repetitive, time-consuming tasks that don't require complex judgment. By automating document processing, data extraction, and workflow management, AI can free human experts to focus on the nuanced work that genuinely requires their expertise.
This division of labor – AI for processing and humans for decision-making – represents a sustainable path forward. Rather than replacing claims professionals, AI becomes a force multiplier, enabling teams to handle larger caseloads while maintaining quality standards. The survey data suggests this approach resonates strongly with practitioners who see AI as a tool to enhance rather than replace their capabilities.
Key Insight #5: The Regulatory Reality Check
The highest ranking of compliance concerns (49%) in the survey reflects the claims industry's unique regulatory environment. Unlike consumer-facing applications, where AI adoption can move quickly, claims processing operates under strict regulatory oversight. Any AI implementation must meet not only operational requirements but also legal and compliance standards that vary by jurisdiction and line of business.
This regulatory awareness actually strengthens the case for HITL approaches. Expert oversight provides a vital compliance layer, ensuring that AI-driven efficiency gains don't come at the expense of regulatory adherence. The combination offers a way to modernize operations while maintaining the defensibility and auditability that regulators demand.
Key Insight #6: Building Toward a Broader Adoption
The survey reveals an industry transition, with 37% of respondents occasionally using AI and a further 38% considering adoption. This represents a significant cohort of organizations actively evaluating how AI fits into their operations. The key to converting consideration into implementation lies in addressing the trust concerns identified in the survey.
Organizations that lead in AI adoption will likely be those that successfully implement HITL processes from the start. Rather than viewing human oversight as a temporary bridge to full automation, successful adopters will likely embrace it as a permanent feature that enables both efficiency and trust.
Looking Forward to a Collaborative Future
The survey findings point toward a future where AI and human expertise can work in tandem. This collaborative model addresses both the operational pressures facing the claims industry and the trust requirements necessary for sustainable adoption. As AI continues to advance and demonstrate reliability in controlled environments, we can expect to see a gradual expansion of its role in claims processing. However, the HITL principle identified in this survey is likely to remain a priority in AI implementation in the claims space.
The claims industry's thoughtful approach to AI adoption may well serve as a model for other high-stakes sectors grappling with similar questions about balancing innovation with responsibility. By insisting on human oversight and focusing on efficiency gains over decision-making authority, claims professionals are charting a course that could accelerate AI benefits while maintaining the trust and reliability that the industry demands.
The survey data make clear that the question isn't whether AI will transform claims processing but how that transformation will unfold. The answer appears to lie not in choosing between human expertise and AI, but in finding the optimal combination of both.
