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, 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,” says 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.”
Franklin Manchester, global insurance strategic advisor at SAS, adds: “AI is an imperative for businesses, but it’s not a magic pill. For AI to generate value throughout the enterprise, it needs to be supported by talented people and fuelled with robust, connected data.
“The insurers who can infuse AI into their existing operations – and who establish the governance necessary to deliver safe and responsible AI at scale – will have a competitive advantage for growth, innovation and creating value for their customers.”
Insurers taking a 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 underutilisation (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.
“Making processes more efficient is still important,” says Manchester. “But the most competitive insurers will focus on using AI for innovation to drive premium growth through outstanding customer experiences.”