Nvidia survey finds banks and insurers pressing ahead with AI spend as use moves beyond pilots
Financial institutions say open-source models and AI agents are driving wider adoption, with most firms reporting revenue gains, cost savings and plans to keep investing.
NVIDIA said a new survey of more than 800 financial-services professionals shows nearly all institutions plan to increase or maintain spending on artificial intelligence, as the technology shifts from experimentation to everyday use.
The findings are set out in Nvidia’s sixth annual State of AI in Financial Services report, which the company said reflects record-high levels of AI adoption across banks, insurers and investment firms. According to the report, organisations are moving beyond small pilots and beginning to deploy AI systems at scale across core operations.
Among the headline results, 65% of respondents said their organisation is actively using AI, up from 45% a year earlier. Nearly nine in ten, or 89%, said AI has helped to increase annual revenue or reduce annual costs, while 61% reported using or assessing generative AI tools, up sharply year on year.
For a lay reader, generative AI refers to systems that can produce text, code, images or other content, rather than simply analysing data. In finance, this can range from drafting customer communications and summarising documents to helping staff explore data or support trading decisions.
The report also highlighted the growing importance of open-source software. Open-source models are AI systems whose underlying code and design are openly shared, allowing firms to inspect, adapt and run them on their own infrastructure. Nvidia said 83% of respondents view open source as important to their AI strategy, with 43% describing it as very to extremely important.
“Open source models are fundamentally changing the competitive dynamics in financial AI,” said Helen Yu, chief executive of Tigon Advisory Corp. The implication, she said, is that firms no longer need to rely solely on expensive proprietary tools to innovate with AI.
The survey provided more detail on perceived financial returns. About 64% of respondents said AI had helped increase annual revenue by more than 5%, including 29% who reported revenue gains above 10%. On the cost side, 61% said AI reduced annual costs by more than 5%, with a quarter seeing reductions greater than 10%.
Respondents cited document processing, customer engagement, algorithmic trading and risk management as common use cases. More than half, 52%, said operational efficiency was the biggest area of improvement, while 48% pointed to gains in employee productivity.
Looking ahead, almost all respondents said their AI budgets would either rise or remain unchanged in the coming year. Around 41% plan to focus on optimising existing AI workflows and systems already in production, 34% said they will look for additional use cases, and 30% expect to expand underlying AI infrastructure such as computing power and data platforms.
The report also pointed to early but growing interest in AI agents. These are systems designed to carry out multi-step tasks autonomously, such as monitoring markets, preparing reports or coordinating processes across different software tools. Nvidia said 21% of respondents have already deployed AI agents, while a further 22% expect to do so within the next year or beyond.
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Taken together, the findings suggest AI is becoming a mainstream capability in financial services rather than an experimental add-on. While the survey reflects self-reported results rather than audited outcomes, it indicates strong confidence among industry leaders that AI is delivering tangible benefits.
As firms weigh rising costs, regulatory pressure and competition from fintech rivals, Nvidia’s survey suggests many see AI, particularly open and flexible systems, as a way to improve efficiency and stay competitive rather than a discretionary technology investment.
The Recap
- NVIDIA survey finds financial firms scaling AI and open source.
- 89% said AI increased revenue and decreased annual costs.
- 21% have deployed AI agents; 22% expect deployments.
