Despite mounting expectations that artificial intelligence will unlock new efficiencies and revenue streams, the global insurance industry remains hesitant in fully embracing the technology. A new report by IDC, commissioned by analytics firm SAS, reveals that only a small minority of insurers have reached what they consider a truly transformative stage of AI adoption.
According to The Data and AI Impact Report: The Trust Imperative, just 7% of insurers describe their AI capabilities as “transformative”, while a further 14% continue to operate with siloed and fragmented data infrastructures that significantly constrain innovation. Although AI use is accelerating across the sector, the study finds that underlying data maturity, governance frameworks and organisational trust have yet to keep pace with business ambitions.
One of the report’s central findings concerns trust. Interestingly, respondents reported higher levels of trust in generative AI tools than in traditional AI systems. However, this confidence is often not supported by robust governance, risk controls or data management practices. As a result, insurers face the dual risk of either underutilising reliable AI systems due to scepticism, or over-relying on tools that have not been sufficiently validated.
Investment trends further illustrate this cautious stance. Only 8% of insurers expect to raise AI spending by 20% or more in the coming year. Nearly 60% anticipate more modest increases of between 4% and 20%, while around one-third foresee minimal growth of 3% or less, or even a reduction in AI budgets. This restrained approach suggests that many firms are still testing the value of AI rather than committing to large-scale transformation.
The trust gap is particularly striking. Just 9% of insurers reported having both high trust in AI and strong internal capabilities to support trustworthy AI deployment. More than 40% fall into categories characterised by misalignment between trust and capability, highlighting structural weaknesses in governance, skills and oversight.
Data-related challenges remain the most frequently cited obstacles. Over half of insurers pointed to weak data governance and fragmented data foundations as major barriers, while 44% identified a shortage of specialised AI talent as a critical constraint.
Kathy Lange, research director for AI and automation at IDC, noted that while insurers are broadly aligned with other industries on the principles of trustworthy AI, they lag behind in practical execution. Compared with banking, government and life sciences, insurance recorded the lowest overall level of AI maturity in the study, limiting its ability to scale AI initiatives across the enterprise.
Key findings from the report
| Indicator | Share of insurers |
|---|---|
| Consider AI adoption “transformative” | 7% |
| Operate with siloed data infrastructures | 14% |
| Expect AI spending to rise by ≥20% | 8% |
| Have high trust and strong AI capability | 9% |
| Cite weak data governance as a major barrier | Over 50% |
| Cite lack of AI talent as a major barrier | 44% |
The report concludes that insurers are at a critical inflection point: AI adoption is gaining momentum, but without significant improvements in data maturity, governance and skills, the industry risks falling further behind its peers.