Building Trust in AI: Insurers Navigate the Complex Landscape of Technology

Understanding the Trust Imperative in Insurance AI

The concept of trust has always been integral to the insurance sector. As technology evolves, particularly with artificial intelligence (AI), the challenges of maintaining that trust have become increasingly apparent. A recent study by SAS delves into how insurers are approaching AI adoption, aiming to build trust among users and consumers.

The Role of Trust in AI

Trust is a two-way street; for AI systems to function effectively, both consumers and insurance professionals must believe in the reliability and accuracy of the technology. The study indicates that while there is a general inclination towards utilizing generative AI, users often rely more on traditional AI systems without the proper governance in place.

In the insurance sector, trust in AI is experiencing significant scrutiny. According to the SAS findings, only a small percentage of insurers, about 9%, exhibit high trust in AI capabilities while also demonstrating strong governance measures in their operations. This lack of confidence can stem from a combination of historical underutilization and overreliance on unproven technologies.

Insights from the Study

The study outlines five key findings impacting the adoption of AI within the insurance industry:

1. Modest AI Maturity: The insurance industry's maturity in terms of AI and data infrastructure lags behind other sectors. Just 7% of insurers consider themselves transformative, which is notably low compared to government, life sciences, and banking industries.

2. Conservative Investment Trends: With only 8% anticipating a notable increase in AI spending within the next year, the majority of insurers are hesitant. Nearly 60% predict modest growth of 4% to 20%, while about one-third expect stagnant or decreased investments in AI.

3. Trust Gaps: The delineation between trust and capability is stark. While some insurers exhibit faith in AI, their actual systems may fail to inspire confidence, resulting in a disconnect that could hinder broader adoption.

4. Challenges in Data Governance: A significant 51% of insurers recognize inadequate data governance as a pressing concern. In tandem, the centralization and optimization of data foundations remain areas for growth and pivotal for leveraging AI's full potential.

5. Talent Shortages: Finding skilled professionals in AI is critical. Over 44% of participants perceive a shortage of specialized talent in their organizations, which further complicates effective AI integration.

The Future of AI in Insurance

As the industry looks ahead, there's a clear need for insurers to adapt their strategies regarding AI. The focus will shift towards integrating AI technologies that directly generate value—especially those that enhance customer experience and operational efficiency. Franklin Manchester, a global insurance strategic advisor at SAS, emphasizes that while efficiency is key, insurers should prioritize utilizing AI to innovate and create exceptional customer experiences.

Insurers must rationalize their AI adoption strategies to enhance trust and governance in the coming year. A live webinar hosted by industry experts from SAS, AWS, and IDC will delve into emerging trends impacting the insurance sector on February 4, 2026. This session aims to equip industry professionals with insights into building trust and improving operational performance amidst economic and technological changes.

Conclusion

The challenges posed by AI in the insurance sector are far from insurmountable. With a comprehensive approach focused on governance, talent acquisition, and infrastructure maturity, insurers have the opportunity to not only embrace AI but to foster a foundation of trust essential for the industry's future growth and innovation. As these systems evolve, so too will the relationship between insurers, consumers, and the technology that supports their evolving needs.