The insurance industry is at a critical inflection point. Long-standing operational challenges such as slow claims processing, manual underwriting workflows, fragmented data systems, and rising operational costs are becoming increasingly difficult to manage in a fast-evolving, digital-first world. At the same time, customer expectations have shifted dramatically, with policyholders now demanding faster decisions, real-time updates, and seamless digital experiences.

Traditional approaches, built on static risk models and legacy infrastructure, often struggle to keep pace with today’s dynamic risk landscape. Artificial intelligence is emerging as a powerful solution to these challenges. With AI, insurers can automate complex workflows, enhance risk assessment with real-time insights, detect fraud more effectively, and deliver faster, more personalized customer experiences. Reflecting this shift, even a Gartner® Survey found that 98% of insurers plan to deploy AI by the end of 2027.

However, despite the significant opportunities that AI offers, integrating it into core insurance operations remains a complex undertaking for many organizations. While majority of insurers are experimenting with AI, only a few have successfully scaled AI solutions enterprise-wide indicating a gap between experimentation and full operational deployment. 

The 2026 Guide to AI in Insurance: 50+ Real-World Use Cases Across the Value Chain from Everforth Quinnox is a comprehensive resource designed to bridge that gap, offering practical insights into where AI is delivering real impact and how insurers can scale it effectively.