P&C insurance leaders say AI success is a business problem, not a technology project
ReSource Pro, a trusted partner providing strategic operations and technology services for the insurance industry, published its 2026 AI Lessons Learned Report, a first-hand account of how insurance organizations across the U.S. property and casualty insurance ecosystem are navigating the opportunities and pitfalls of artificial intelligence adoption. The proprietary research, authored by ReSource Pro Senior Partner Mark Breading and Program Manager Heather Turner, draws on 40+ interviews with executives spanning the full insurance value chain, delivering an industry-wide picture of where P&C insurance stands in its AI journey.
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“What the industry is telling us loud and clear is that the organizations winning with AI are the ones treating it as a business transformation, not an IT initiative,” said Mark Breading, Senior Partner at ReSource Pro.
The proprietary research asked leaders across the insurance ecosystem three direct questions about AI implementation at their organization: what lessons have you learned, what challenges are you facing, and what comes next? The responses converge on a clear and provocative conclusion: success with AI has less to do with selecting the right model or tool, and far more to do with culture, data hygiene, governance, and sustained organizational change.
ROI from AI depends on the organization, not the system
The report’s central theme cuts against years of technology-first messaging that has dominated the industry. Across every segment, leaders agree that AI implementation is not a technology project; it is an operational transformation spanning people, processes, and behavior. The distinction changes how organizations must plan, invest, and lead.
“What the industry is telling us loud and clear is that the organizations winning with AI are the ones treating it as a business transformation, not an IT initiative,” said Mark Breading, Senior Partner at ReSource Pro. “The five lessons in this report are hard-won and remarkably consistent. No matter the segment, the same barriers and the same mindset shifts keep coming up.”
Five key lessons from the AI frontlines in insurance
ReSource Pro’s proprietary research distills industry experience into five foundational takeaways:
- AI adoption is a business problem and a cultural shift, not a technology implementation. Insurance businesses have learned that adopting AI effectively requires a behavioral and cultural shift, with employees continuously applying human judgment to validate and question AI outputs. Standard operating procedures related to workflow design, data management, and organizational change management must be well documented before AI can succeed.
- Securing executive buy-in remains a universal challenge. Across the ecosystem, organizations wrestle with cultural awareness, adoption, and acceptance. Executive sponsorship is often difficult to obtain when AI ownership is undefined and security concerns outweigh perceived operational gains. Moving past proof of concept requires executive commitment with ongoing, role-specific education built around real use cases.
- Establishing AI governance frameworks is a top priority. Governance is where many insurance companies are the most underprepared. As agentic AI takes hold and regulators further scrutinize insurance applications, the urgency to create formal AI committees and governance structures is accelerating. ReSource Pro’s research finds that AI capabilities are already outpacing the frameworks organizations have in place to manage them.
- Poor data quality is the single biggest barrier to AI success. Organizations across the insurance industry universally recognize that bad data inputs produce poor AI outputs. Many carry data scattered across legacy systems in different formats and at inconsistent quality levels, making a clean, standardized data foundation a mandatory prerequisite rather than an afterthought. This finding was echoed consistently across the full insurance value chain in ReSource Pro’s proprietary research.
- Human expertise and insurance domain knowledge remain essential. The insurance industry agrees: AI amplifies the work of skilled professionals, but it can’t replace the deep industry knowledge required to apply it wisely. ReSource Pro’s findings show that organizations that pair AI tools with experienced insurance practitioners consistently outperform those that deploy technology without sufficient domain context.
What comes next
When asked about their immediate priorities, leaders across the industry regularly cited two imperatives: enhancing data management infrastructure and building formal AI governance frameworks. Many also noted the need for more time to educate staff, build institutional knowledge, and identify business problems where AI delivers the clearest returns. The opportunity ahead is significant. ReSource Pro’s report notes that timelines for complex initiatives are already compressing, with tasks that once required six months to complete can now be done in six weeks. Across all segments, respondents expressed optimism that the industry is still early in uncovering the full potential of AI, and that foundational investments in data and governance will unlock substantially greater returns in the years ahead.
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