EXL’s research indicates that approximately 89% of UK banking and insurance companies have integrated AI solutions in the past year, though data optimization issues could dampen their impact.
The survey, focusing on executives from leading UK insurers and banks, reveals that 44% have applied AI across eight or more business areas, particularly in marketing, business development, and regulatory compliance.
Significantly, about 9 out of 10 executives in the financial sector have invested over £7.9 million in AI during their last fiscal year, with more than a third allocating £39 million or more. This demonstrates the industry’s commitment to substantial investments in AI technology.
Despite these advancements in AI adoption, the report points out a potential neglect in the area of data management. About 47% of respondents confessed their organizations are only “minimally data driven,” highlighting concerns about the success of AI applications without a strong data basis.
Kshitij Jain, EMEA Practice Head at EXL, remarked, “It’s clear industry leaders recognize AI’s potential, but external pressures to implement quickly can lead to unchecked investment. The risk is that ensuring operations are truly data driven gets deprioritised, which can prove very costly.”
The research also identified a segment known as “Strivers,” making up 45% of those surveyed, who are selectively deploying AI in about four functions. This concentrated strategy has enabled them to efficiently use AI for cost reduction, outperforming their early adopter counterparts by 23 percentage points.
Furthermore, more than half of the respondents are increasing their AI investments, especially in light of advancements in generative AI. Nevertheless, 70% have expressed serious concerns regarding the risks associated with generative AI, such as potential brand damage and the spread of inaccurate data.
“The key with any AI rollout is a measured, strategic approach—getting the data architecture right, testing solutions, and training employees,” Jain concluded. “For enterprise adoption to succeed, boards must buy into AI’s capabilities and ensure investment is being used effectively.”
