Global risk and claims management firm Sedgwick says the insurance industry is racing to adopt AI—but most carriers still struggle to turn that adoption into meaningful results.
In a new report examining the future of property claims, Sedgwick argues that insurers must move beyond AI experimentation and focus on scaling automation, orchestrating workflows, and integrating AI across the entire claims lifecycle.
The report arrives as AI investment in the insurance sector surges. Industry forecasts suggest AI in insurance could grow into an $80 billion market by 2032, yet the study indicates many carriers remain stuck in early adoption stages.
The Gap Between AI Vision and Reality
According to Sedgwick’s findings, nearly two-thirds of property insurers acknowledge a gap between their AI ambitions and what they have actually implemented.
While 58% to 82% of carriers are already using AI tools in some capacity, far fewer have successfully integrated those technologies into fully operational systems.
The maturity gap becomes even clearer in the report’s deeper data:
- Only 12% of insurers say they have mature AI capabilities
- Just 7% report achieving scalable AI success across claims operations
- 90% of carriers believe AI must be orchestrated across operations to deliver full value
The problem isn’t lack of experimentation—it’s the challenge of integrating multiple AI tools into cohesive workflows.
“AI is rapidly reshaping property claims, yet speed alone isn’t enough,” said Scott Richardson, President of Property for the Americas at Sedgwick. “Carriers must move beyond experimentation to strategically scale automation and realize AI’s full potential across the claims lifecycle.”
Why AI Adoption Hasn’t Translated Into Maturity
Many insurers have introduced AI into isolated processes—such as document processing, fraud detection, or claims triage—but these systems often remain disconnected from broader operations.
Fragmented data and incompatible platforms frequently limit the impact of those tools.
Without integrated workflows and consistent data governance, insurers struggle to scale AI beyond pilot programs.
This fragmentation is one reason AI initiatives sometimes fail to deliver the productivity gains executives expect.
Automation Works—But Humans Still Matter
The report also highlights a critical balance insurers must strike between automation and human expertise.
Automation proves highly effective for high-volume, low-complexity tasks, including:
- Initial claims intake and categorization
- Document extraction and data entry
- Basic fraud detection signals
- Routine claims communication
But for complex losses—such as major property damage, catastrophe claims, or sensitive customer interactions—human expertise remains essential.
That reality is reflected in industry sentiment: 75% of claims professionals believe AI systems require human oversight.
Strategy Is the New Competitive Advantage
For Sedgwick, the key differentiator between insurers that succeed with AI and those that struggle isn’t the technology itself—it’s strategy.
“AI is accelerating faster than any technology in our lifetime,” said David Gauragna, Managing Director of Property at Sedgwick. “Strategy isn’t optional. Long-term success and ROI depend on how carriers leverage this technology.”
That strategy typically includes several elements:
- Enterprise-wide data governance
- Integration of AI tools across claims systems
- Workforce training and change management
- Workflow orchestration and automation frameworks
Organizations that treat AI as an operational transformation—rather than a collection of standalone tools—are more likely to achieve scalable results.
The Future of Property Claims
Property insurance is one of the most promising areas for AI adoption.
Advances in computer vision, predictive analytics, and automation allow insurers to assess damage faster, detect fraud more accurately, and process claims more efficiently.
AI-driven systems can analyze photos of property damage, estimate repair costs, and prioritize claims during natural disasters—dramatically improving response times.
But the technology’s potential depends heavily on integration.
“Fully mature AI capabilities, in tandem with human expertise, will drive measurable improvements in speed, accuracy, and cost savings,” said Mason Bartleson, Vice President of Business Transformation at Sedgwick.
A Long Road to AI Maturity
The report ultimately paints a familiar picture across many industries adopting AI: enthusiasm is high, experimentation is widespread, but operational maturity remains rare.
For insurers, the next phase of AI adoption will likely focus less on new tools and more on connecting the systems they already have.
If Sedgwick’s findings are any indication, the carriers that succeed will be those that treat AI not as a technology project—but as a strategic transformation of the entire claims operation.
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