Rongchai Wang
Jan 22, 2026 15:04
NVIDIA survey of 800+ finance professionals shows 65% actively using AI, with open source models and AI agents driving adoption across trading and risk management.
Nearly every financial institution surveyed plans to maintain or increase AI spending over the next year, according to NVIDIA’s sixth annual State of AI in Financial Services report released January 22, 2026. The survey of more than 800 industry professionals found that 89% of respondents credit AI with boosting revenue and cutting costs.
The numbers tell a clear story of an industry that’s moved past experimentation. Active AI usage jumped to 65% of respondents, up from 45% in last year’s survey—a 20 percentage point swing that signals the pilot phase is over for most major players.
Open Source Becomes Strategic Priority
Perhaps the most significant shift: 84% of respondents now consider open source models and software important to their AI strategy. The appeal isn’t hard to understand. Financial institutions can fine-tune these models on proprietary transaction data and customer histories, building capabilities that competitors can’t simply license.
“Open source models are fundamentally changing the competitive dynamics in financial AI,” said Helen Yu, CEO of Tigon Advisory Corp. “The real value capture happens when institutions fine-tune these models on their proprietary transaction data.”
Alexandra Mousavizadeh, co-CEO of Evident Insights, offered a more nuanced take: “Open source models can help banks close the gap with early movers, unlock cost efficiencies and safeguard against vendor lock-in, but they’re not without their limitations.” Leading institutions, she noted, need proficiency in both open source and proprietary approaches.
The Money Numbers
The ROI data is striking. Among respondents reporting AI-driven revenue gains, 64% saw increases exceeding 5%, with 29% claiming gains above 10%. On the cost side, 61% reported savings greater than 5%, and a quarter achieved double-digit reductions.
Document processing, customer engagement, algorithmic trading, and risk management topped the list of use cases delivering measurable returns. Operational efficiency improvements ranked as the biggest win for 52% of respondents, while 48% pointed to employee productivity gains.
Dwayne Gefferie, payments strategist at Gefferie Group, highlighted a specific example: “Agentic AI systems can now autonomously route transactions to the most optimized payment networks, dynamically adjust retry logic based on real-time issuer signals and make routing decisions under 200 milliseconds.” Every basis point improvement in authorization rates, he noted, flows directly to revenue.
Agents Are Coming
The agentic AI wave is building momentum. Some 21% of respondents have already deployed AI agents, with another 22% planning deployment within the next year. These systems handle complex tasks autonomously—from back-office operations to investment research—rather than simply responding to prompts.
This aligns with broader industry forecasts. According to Capgemini Research Institute data, AI budgets in banking and capital markets are set to jump from 3% to 5% of total business budgets in 2026. The World Economic Forum projects financial services AI spending could hit $97 billion by 2027, up from $35 billion in 2023.
Where’s the money going? About 41% of respondents said investment would target optimizing existing AI workflows. A third are focused on identifying new use cases, while 30% plan infrastructure buildouts—whether on-premises or cloud-based.
The regulatory backdrop adds urgency. UK watchdogs received warnings this week about AI risks in financial services, while separate analysis flagged potential consumer harm from current implementation approaches. Institutions betting heavily on AI will need to balance speed-to-market against compliance requirements that are still taking shape.
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