The 2026 Insurance Industry Trends Report: AI and the Foundations of Transformation

AI Moves from Experimentation to Enterprise Strategy 

For years, AI in insurance lived in innovation labs and analytics teams. Pilots showed potential but rarely scaled. That has now changed. Our research findings show that insurers expect AI’s impact on their operations to triple within the next year, driving conversations about machine learning, automated underwriting, and dynamic pricing from technical departments into boardrooms. 

The shift is clear in the data: 81% of insurers have integrated AI into workflows, with 43% using it across most functions. Pricing systems, risk assessment models, and customer platforms are all areas where AI now directly affects speed to market and accuracy. Leading insurers are treating AI as infrastructure, not innovation, and embedding it into core business processes rather than keeping it experimental. 

But urgency comes with caution. While insurers expect AI’s impact to triple, 56% favor gradual adoption that keeps human oversight in place for the next three years. This reflects a practical understanding: AI offers real potential, but poor deployment creates risk.  

The question isn’t whether to adopt AI, but how to do it responsibly while managing compliance, data quality, and organizational readiness. 

The Infrastructure Challenge That Determines AI Success 

Most insurers still run on technology built for a different era. Legacy systems that once powered underwriting, policy administration, and claims processing now slow everything down. They make it harder to deploy new models, update pricing, or share data across teams. As regulatory demands for transparency grow, these systems create more compliance risk.

Our research makes this clear: AI is an accelerant, not a solution on its own. When applied to clean data and modern systems, AI improves decision-making speed and risk assessment accuracy. Yet 83% of executives worry their AI models are trained on incomplete or inaccurate data. When layered onto fragmented legacy systems with poor data governance, AI amplifies problems instead of solving them. The insurers succeeding with AI are those who invested in modern systems, better data pipelines, and governance frameworks first.

This infrastructure gap explains why AI adoption is uneven despite executive commitment. Carriers that modernized their platforms deploy new models in weeks instead of months. Those who delayed are stuck: legacy constraints block AI’s potential while competitors move ahead.

The winners in 2026 won’t chase every new AI technique. Instead, they’ll build foundations designed for adaptability and continuous improvement. 

From Operational Efficiency to Strategic Reinvention 

Modernization isn’t just about upgrading systems. It’s about building organizations that can move fast. That means breaking down silos between actuarial, underwriting, IT, and customer-facing teams so insights flow freely. It means deploying new products in days, not months, and adjusting pricing models as new data emerges. 

The insurers making these investments now are creating advantages that compound over time. They can respond to market shifts while competitors struggle with system constraints. Standing still isn’t an option when climate risk, cyber threats, and customer expectations are all changing faster than traditional planning cycles can accommodate. 

Benchmark Your Organization 

AI’s potential is clear, but realizing it requires more than enthusiasm. The insurers that will lead in 2026 are those building the infrastructure, data practices, and governance frameworks that make AI work at scale. This report provides the benchmarks and insights to help you assess where your organization stands and what steps to take next. 

Download the 2026 Insurance Industry Trends Report to access the full findings and benchmark your organization against industry leaders.