Will generative AI prove itself a bane or boon to the insurance industry? A new study exploring the use of generative AI in insurance suggests that 9 in 10 insurers plan to invest in GenAI in the next year. The enthusiasm is palpable – but survey data also shows that the ethical and regulatory implications of innovation continue to vex many insurers, even as analytic ingenuity promises to help the sector address its biggest challenges.

The study, Your journey to a GenAI future: An insurer's strategic path to success, comes from a global multi-industry survey by SAS, a data and AI company serving 47 of the world's 50 largest global insurers, and Coleman Parks Research Ltd. Its findings offer an insider's look at how insurance companies worldwide are implementing, budgeting for and strategizing around GenAI, based on survey insights from 236 industry decision makers. Additional insurance and cross-sector results from industries like banking, health care, life sciences and government can be compared and contrasted via SAS' interactive GenAI survey data dashboard.

"Insurance is a notoriously slow-moving industry, but insurers are proving to be GenAI trailblazers, showing remarkable GenAI investment and excitement," said Franklin Manchester, Principal Global Insurance Advisor at SAS. "We're not looking at an AI bubble set to burst, and that's a good thing – but it's clear that the insurance sector, like other industries, has obstacles to overcome.

1. Insurers are jumping into GenAI…budget and strategy first.
With 89% of insurance sector respondents planning to invest in GenAI in 2025, 92% of that number have a dedicated GenAI budget in the works.

Among the industry's goals for investing in GenAI, the top three emerged as:

1. Improvement in customer satisfaction and retention (81%, the highest of any industry segment).
2. Reduction in operational costs and time savings (76%).
3. Enhanced risk management and compliance measures (72%).

Already, two-thirds (68%) of insurance professionals surveyed reported using some form of GenAI in their professional roles at least once a week. About 1 in 5 (22%) professed they use the technology daily. While only 11% of respondents said their organization had fully implemented GenAI, another 49% indicated they were already in the process of implementing it.

"GenAI is not a silver bullet, but insurers are finding it can provide many more pieces of the jigsaw puzzle, including in areas that have previously proven quite difficult, like the ingestion of unstructured data," said Joe Rowe, Data and AI Insurance Lead for UK, Ireland and Africa at Accenture. "Claims and underwriting are prime examples where GenAI is helping the human in the loop extract insights and make better decisions."

2. Insurance expressed more concern about GenAI ethics than other industries.
Insurance decisionmakers showed themselves modestly more anxious about GenAI ethics than their counterparts in other industries. Among insurance respondents, 59% indicated concern about the ethical implications of their organization's GenAI; that's in contrast to a cross-industry average of 52%.

Despite insurers' deeper ethics worries, their plans for governance and monitoring – efforts that would include the creation, implementation and maintenance of ethical frameworks – remain works in progress:

• Only 5% of insurance respondents described their organization's GenAI governance framework as "well-established and comprehensive."
• 57% reported that their organization's frameworks were "in development."
• 27% called their organization's frameworks "ad hoc or informal."
• 11% said their ethical frameworks were "nonexistent."

"The use of GenAI is progressing quite rapidly, but to develop it responsibly, insurers must have an alignment of people, processes and technology, all working together to drive use cases from experimentation into operations and production," said Rowe. "Proper governance requires focus and investment."

In alignment with other industries, insurance pros named data privacy (cited by 75%) and data security (73%) as their foremost concerns related to their organizations' use of GenAI. It's little wonder; citizen fraudsters who employ GenAI – and career criminals employing the technology for larger scale frauds and financial crimes like money laundering and terrorism financing – are on the rise. In the fraud tech arms race, GenAI may well become table stakes to keep pace with bad actors.

3. Insurers look for answers for the data drought.
Complementing concerns about AI ethics are regulatory compliance worries. Only 1 in 10 (11%) of insurance respondents reported that their organization is fully prepared to comply with current and upcoming GenAI regulations. Ethically deployed GenAI use cases are drawing interest among insurers.

For instance, large language models (LLMs) require huge amounts of data which may not be available in existing productions systems to properly treat edge cases. There's a serious lack of large datasets, combed for bias and checked for data quality, in insurance – a veritable data drought.

Why is this important? The quality and quantity of data used to train GenAI and other AI models can make or break the accuracy, fairness and equity of the model's results in claims and policy decisions.

Furthermore, insurers, as fiduciaries, safeguard significant volumes of sensitive personal identifiable information. With data privacy anxiety growing, synthetic data ­– artificial data manufactured to realistically mimic real-world data, used to enrich existing datasets without compromising customer privacy – could provide an answer.

More than a quarter (27%) of insurance industry survey respondents reported using synthetic data; nearly a third (30%) said they were actively considering it, and 22% reported they might consider it.

"Many insurance decisionmakers are actively working on GenAI projects that could transform how carriers do business," said Manchester. "Innovative spark is alive and well in insurance, and we can only nurture that flame when we embrace the tenets of responsible innovation. This includes establishing and maintaining policies and processes that protect customers and the integrity of the data we use."

"The next step is clear: Insurers must embrace ethical frameworks and data rigor as their true north to realize the transformative potential – and full value – of GenAI technology."