What's Happening?
Craig Weber, head of insurance strategy at Cognizant, has advised the insurance industry to temper expectations regarding artificial intelligence (AI) pilot projects. This comes in response to a Massachusetts Institute of Technology study indicating that
95% of AI pilots fail to show measurable return on investment. Weber suggests that the perceived failure rate is more about perspective, emphasizing that success in AI implementation should be measured by learning and skill-building rather than immediate results. He highlights challenges such as legacy data infrastructure and regulatory hurdles that contribute to the slow adoption of AI in the insurance sector. Weber argues that insurers should focus on building capabilities and experience, even if the application of AI is several years away.
Why It's Important?
The cautious approach recommended by Weber is significant for the insurance industry, which is grappling with integrating AI into its operations. The high failure rate of AI pilots underscores the complexity and challenges of implementing new technologies in a sector traditionally reliant on deterministic processes. By focusing on learning and skill development, insurers can better prepare for future technological advancements and regulatory changes. This approach could lead to a more sustainable and strategic adoption of AI, potentially giving companies a competitive edge in the long term. The emphasis on data management and regulatory understanding is crucial as these factors will likely shape the future landscape of AI in insurance.
What's Next?
Insurers are expected to continue experimenting with AI pilots, but with a renewed focus on learning and capability building. As regulators take time to understand and approve AI-driven decision-making processes, insurers may need to concentrate on areas less scrutinized by regulators, such as technology and marketing. The industry might also see increased collaboration with AI experts and technology partners to enhance internal capabilities. Over time, as AI tools mature and regulatory frameworks evolve, insurers could gradually integrate AI into more critical decision-making processes, potentially transforming the industry.
