A new study exploring the use of GenAI in insurance suggests that nine in 10 insurers plan to invest in GenAI in the next year.
Despite this enthusiasm, 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 and Coleman Parks Research. Its findings offer an insider’s look at how insurance companies worldwide are implementing, budgeting for, and strategising around GenAI based on survey insights from 236 industry decision-makers.
“Insurance is a notoriously slow-moving industry, but insurers are proving to be GenAI trailblazers showing remarkable GenAI investment and excitement,” says 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.”
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:
- Improvement in customer satisfaction and retention (81%, the highest of any industry segment).
- Reduction in operational costs and time savings (76%).
- 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 one in five(22%) professed they use the technology daily. While only 11% of respondents said their organisation 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,” says 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.”
Insurance decision-makers 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 organisation’s GenAI – 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 organisation’s GenAI governance framework as “well-established and comprehensive”.
- 57% reported that their organisation’s frameworks were “in development”.
- 27% called their organisation’s frameworks “ad hoc or informal”.
- 11% said their ethical frameworks were “non-existent”.
“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,” says 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 organisations’ 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.
Complementing concerns about AI ethics are regulatory compliance worries. Only one in 10 (11%) of insurance respondents reported that their organisation 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 and 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 decision-makers are actively working on GenAI projects that could transform how carriers do business,” says 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 rigour as their true north to realise the transformative potential – and full value – of GenAI technology,” Manchester says.