State of AI in Financial Services: 2026 Trends

Table of Contents Survey Overview AI in Financial Services: Key Trends for Industry Leaders3Executive Summary4 An In-Depth Look at the Results Financial Services Is Embracing the AI-Enabled Future6The Industry Is Embracing Open Source7AI Agents Off to a Solid Start in Financial Services8AI Is Seeing Widespread Adoption Across Operations9Operational Efficiency and Employee Productivity Top AI ROI for Financial Services10Financial Institutions Planning to Increase AI Investment in 202612Financial Services Is Choosing Hybrid Architecture for AI Workloads13Looking Forward13Methodology14 Survey Overview AI in Financial Services: Key Trends forIndustry Leaders The AI revolution has just begun, but it’s already had a profound impact onfinancial institutions. From transforming algorithmic trading to acceleratingdocument processing and analysis, from reimagining fraud detection withtransformer-based payments foundation models to modernizing legacy codewith coding agents, AI has been a major boon to the industry, providing newavenues for growth, productivity, and cost management. In the sixth annualState of AI in Financial Servicesreport, NVIDIA examines theimpact of AI on the industry, how it’s changing the way the sector operates, andhow organizations big and small are beginning to scale new AI capabilities. The use of generative AI in financial services has grown every year since itsintroduction to the market in 2022, with 61 percent of survey respondentssaying they’re using or assessing it in 2025. This evolution continues as interestshifts toward specific business use cases with clear return on investment, suchas agentic AI. The reason for this rapid adoption and investment in AI is clear: Executives ofleading institutions have publicly acknowledged the significant ROI, especially inthe realms of operational efficiency and employee productivity. It’s no surprisethen that nearly 100 percent of respondents confirm that their AI spending willincrease or stay the same in 2026, with 44 percent saying it’ll rise by more than10 percent. The 2026State of AI in Financial Servicesreport had the highest number ofrespondents in the survey’s history. It explores the growing adoption of AI in thefield, top AI use cases, goals and challenges of financial organizations, plans forinvestment in solutions and infrastructure, impact and return on investment,infrastructure and development trends, and, in a new section this year, adoptionand use of AI agents. Executive Summary 73% The moment to invest in AI in financial services is now, with 73 percentof respondents in leadership roles believing that AI is important to theircompany’s future success. Why? Because AI creates intelligence from data,and no industry is better at—or more dependent on—monetizing intelligencethan financial services. of respondents in leadershiproles believe that AI isimportant to their company’sfuture success. Here are some of the other top highlights from this year’s report. AI Has Moved From Pilot to Prevalence 42% 65% said their organization is activelyusing or assessing agentic AI. said their organization is activelyusing AI, up from 45% in 2024. AI combines the power of big data with advanced machine learningtechniques—from deep learning and reinforcement learning to generative andpredictive models—to drive a wide variety of use cases across the financialservices industry. More organizations are actively using AI than ever, withabout 90 percent of respondents saying their organizations are either activelyusing or assessing AI solutions or pilot projects. Agentic AI is the next frontier,with 42 percent of organizations saying they’re already using or assessing AIagents in their operational workflows. The Importance of Open Source 84% Enterprise-grade AI requires models tuned for specialized use cases thatmanaged services and generalized large language models (LLMs) can’t handle.Because of this, organizations have been turning to open source modelsto build solutions that are fine-tuned toward specific use cases. Overall, 84percent of respondents rated open-source software from moderately toextremely important, including nearly half (48 percent) of respondents inmanagement roles saying that open source is very to extremely important. reported open-sourcesoftware as moderately toextremely important to theirorganization’s AI strategy. Large organizations like banks and other financial firms are moving frommanaged services to open-source foundation models for their most importantAI use cases. As reasoning models grow more advanced and cost-per-tokenpricing continues to rise, the economic pressure to reduce ongoing costsby owning models rather than relying on third parties has intensified. Thisapproach not only delivers more accurate and useful outcomes at a lower totalcost but also ensures that proprietary data remains secure and that enterprisevalue isn’t shared externally. AI’s ROI Is Clear 52% 89% cited operational efficiency