Financial services firms are finding their strongest artificial intelligence results in the parts of the business customers rarely see.
The May installment of “The Enterprise AI Benchmark Report” from PYMNTS Intelligence found that banks, insurers and other financial companies have reached high AI adoption in 27 of 75 tasks examined. High adoption means at least half of surveyed firms use AI for that activity. Healthcare reached that threshold in 10 tasks while media and advertising did so in 16. The findings came from a March survey of 60 senior technology executives at companies in the United States with at least $1 billion in annual revenue.
The results suggest that financial firms are scaling AI fastest where the rules are clear, the data can be checked, and the outcomes can be measured.
- Back-office work led adoption. Revenue recognition topped financial services use cases at 65%. Credit risk assessment and sales forecasting followed at 60% each. Like a new engine installed first in the most reliable part of a machine, AI is gaining ground where firms can test the output and trace how decisions were made.
- Customer-facing uses were less developed. AI adoption reached 30% for churn prediction, 20% for identity verification and 10% for A/B testing. The gap indicated that banks and insurers remain more comfortable applying AI to controlled internal processes than to decisions that directly shape customer acquisition, retention or personalization.
- Spending is set to keep rising. The share of financial services firms that expect to increase their AI budgets during the next 12 months was 85%. Productivity and competitive positioning were each cited by 65% of firms as reasons for further investment, while 55% pointed to risk reduction and compliance.
The outlook is encouraging, but the next stage will depend on better foundations. The report found that 30% of financial services leaders named fragmented or poor-quality data as their biggest barrier to wider deployment.
Most respondents also said they expect AI to support human judgment rather than replace it. That creates a practical path forward. Improve the information feeding existing systems, expand proven uses and keep people responsible for the decisions that carry the greatest consequences.
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