Design Highlights
- Many insurers remain in the exploration phase, struggling to identify suitable AI use cases for effective implementation.
- Insurers need to focus on training teams to develop the necessary skills for successful AI deployment.
- Regulatory standards pose challenges, requiring careful navigation to ensure compliance during AI integration.
- Transitioning from pilot projects to full-scale adoption is complex, hindering readiness for broader AI implementation.
- Increasing cybersecurity risks necessitate robust measures to manage evolving threats associated with AI technologies.
In a world where technology is advancing faster than a speeding bullet, insurers are scrambling to keep up with the AI wave. It’s a frenzy out there. A staggering 90% of insurers are knee-deep in evaluating Generative AI. Talk about a gold rush! Yet, only 55% have actually taken the plunge into early or full adoption.
Progress is being made, though—77% of insurance firms are now incorporating AI into their value chains, up from just 61% the previous year. That’s a noticeable leap, even if it still feels like they’re sprinting just to catch up.
Progress is palpable—77% of insurers are weaving AI into their value chains, a significant jump from last year’s 61%.
The numbers tell a story of rapid transformation. Full AI adoption skyrocketed from a mere 8% in 2024 to 34% in 2025. For health insurance, about 37% have generative AI tools in full production—whatever that means—while others are still tiptoeing around the technology, unsure of their footing.
Half of the insurers—yes, nearly 49%—are implementing AI at scale. Not too shabby, right? But with 90% planning to adopt AI in the next year, one can’t help but wonder: what’s the hold-up?
Claims processing is the darling of AI adoption, leading the charge at 64%-65%. This isn’t just for show; it saves time and cuts costs. Fraud detection is also getting a makeover, with AI improving detection by 65% and slashing overpayment rates. That’s significant, folks.
Yet, underwriting is still lagging, with only 14% on board. Predictions say it’ll hit 70% by 2028. A long wait, isn’t it? In fact, 44% of insurers use AI for fraud detection, indicating a significant focus on enhancing operational efficiency.
The operational efficiency gains from AI are staggering. Claims processing time? Cut down by 55%-75%. Routine claims can go from a drawn-out week to just 24-48 hours. That’s a game changer. Employees can finally ditch the mundane tasks and focus on the complex stuff that actually matters—like growing the business and keeping customers happy.
But hold the applause. Not everyone is ready to jump on the AI train. Many insurers remain stuck in the exploration phase. Cautious much? Identifying the right AI use cases is tricky, and firms are scrambling to train their teams on new skills. Similar to how claims handling procedures must follow state-specific requirements, AI implementation demands careful adherence to regulatory standards and proper training protocols. Conning’s investment centers in Asia, Europe, and North America provide valuable insights into how to navigate this evolving landscape.
Cyber risks? Don’t get started. As AI integration expands, so do the security headaches. Scaling from pilot projects to full-blown enterprise adoption? That’s a whole other beast.
