‘An imperative, not a magic pill’: Study finds insurers looking to build trust and value in AI

Research shows insurers are cautious to ramp up AI investment

The insurance business is built on trust. Likewise, AI cannot work without trust; users and consumers have to believe that it’s providing accurate answers based on sound data. But as a new SAS report shows, trust in AI is a tricky subject with users placing more trust in generative AI than traditional AI, such as machine learning, but not always investing in the governance to ensure that trust is warranted.

As the industry enters a year in which many expect AI to produce a spike in business value, insurers face an inflection point: AI adoption is accelerating, but businesses must address questions around governance and data maturity before they can realise its full potential.

“Our research shows the insurance industry in line with other sectors – if not slightly ahead of them – in terms of delivering trustworthy AI,” said Kathy Lange, Research Director of the AI and Automation Practice at IDC. “However, when it comes to the level of maturity of AI and data infrastructures, insurers lag behind.”

“AI is no longer an experimental technology – it’s becoming central to how insurers operate and compete,” said Sanjay Nursing, Insurance Specialist at SAS. “To unlock its full potential, insurers need more than isolated tools; they need robust, connected data, skilled teams, and strong governance. Those who integrate AI responsibly into their operations will not only drive innovation and growth, but also build the trust in AI needed to support a resilient and successful insurance business.”

Insurers taking measured approach to AI

The Data and AI Impact Report: The Trust Imperative – an IDC report commissioned by SAS – reveals a number of themes indicating that the insurance industry, at least compared to other sectors, is taking a cautious, deliberate approach to adopting AI:

• Modest overall AI maturity. The report notes that, among the four industries analysed (the others being government, life sciences and banking), “insurance presents the most modest profile in terms of both AI and data infrastructure maturity.” Only 7% of insurers consider themselves “transformative” – the lowest of all industries. And 14% remain siloed in their data infrastructure, slowing innovation and limiting enterprise-wide adoption.
  
• Conservative investment profile. About 8% of insurers expect to increase their AI spending by at least 20% in the next year, with nearly 60% saying they expect an increase of between 4% and 20%. About one-third said they expected an even smaller increase (3% or less), if not an outright decrease in investment.
• Trust gaps. Only 9% of insurers combine a high level of trust in the technology with strong trustworthy AI capabilities. Over 40% fall into the categories of either under-utilisation (low trust in reliable systems) or overreliance (high trust in unproven systems).
• Challenges to AI modernisation. Over half of insurance respondents (51%) said their organisation lacked effective data governance, and the same percentage said their data foundations were not centralised or optimised. Almost as many (44%) also perceived a shortage of specialised AI talent.

The move toward AI value

As insurers move toward AI maturity, expect to see them focus on the uses that generate the most value – which are those that drive growth. The study found that cost-reduction measures produce the lowest return of any AI use. The bigger opportunities include improving customer experience, expanding market share and strengthening resilience.

“Improving efficiency will always be important,” said Nursing. “But the insurers who gain a real edge will focus on using AI to innovate – driving growth, enhancing customer experiences, and building trust across every part of their business.”