By 2026, artificial intelligence is no longer a peripheral technology in financial services. For banks, insurers, and capital markets firms, AI has become a central capability shaping how risk is managed, how customers are served, and how operations are scaled. What has changed most is not the availability of AI tools, but the expectations placed on them.
Insights from NVIDIA’s State of AI in Financial Services Survey 2026, based on responses from more than 800 financial services professionals worldwide, suggest that the industry has moved well beyond experimentation. AI is now expected to deliver measurable business outcomes, operate reliably at scale, and support increasingly complex regulatory requirements.
AI Adoption is Widespread
The survey shows that the vast majority of financial institutions are already using AI or actively evaluating it. 65% of respondents say their organizations are actively using AI, up significantly from 45% in the previous year, while most of the remaining respondents are evaluating or piloting AI initiatives.
At this stage, AI adoption itself is no longer a competitive differentiator. What separates organizations is how deeply AI is embedded into core workflows and decision-making processes.
Risk Management and Fraud Remain Primary Drivers
One of the strongest areas of AI impact continues to be risk management. Financial institutions are using AI to detect fraud, monitor transactions, assess credit risk, and identify anomalies faster and more accurately than traditional systems.
According to the survey, fraud detection and cybersecurity are among the most common AI use cases across the industry. AI models can analyze vast volumes of transaction data in real time, enabling earlier detection of suspicious behavior and reducing false positives. For many organizations, these capabilities are no longer optional, especially as digital transactions continue to grow.
Driving Significant ROI Impact
A large majority of respondents report that AI is contributing to higher revenue and lower operating costs. Many organizations point to improvements in fraud detection and transaction monitoring, where AI helps reduce losses while minimizing false positives. Others highlight more accurate risk assessment and credit decisioning, enabling faster approvals without increasing exposure.
Beyond risk-related use cases, AI is also driving efficiency across both front- and back-office functions. Automation of routine processes, smarter data analysis, and AI-assisted decision-making are helping teams operate more efficiently, reduce manual workloads, and better allocate resources. Together, these benefits are translating into measurable financial impact rather than theoretical gains.
Driven by the significant return on investment delivered by AI, many institutions report plans to increase AI investment in 2026. The survey shows that nearly 100% of respondents say their AI budgets will either increase or remain unchanged in the coming year.
Generative and agentic AI move into focus
A notable shift highlighted in the 2026 survey is growing interest in generative and agentic AI. 61% of financial institutions are exploring generative AI for tasks such as document summarization, report generation, customer communication, and internal knowledge support.
Building on this foundation, financial institutions are also being evaluated agentic AI systems, which are designed to operate with a higher level of autonomy. These systems have the potential to automate complex workflows, monitor conditions continuously, and take predefined actions across systems. While adoption is still cautious, interest reflects a broader push toward efficiency and faster decision cycles.
Infrastructure and governance are now critical concerns
As AI systems become more central to financial operations, infrastructure and governance have emerged as key challenges. High-performance computing, data security, model explainability, and regulatory compliance are no longer secondary considerations.
Many institutions report that scaling AI from pilot to production remains difficult without the right foundation. Models must be trained efficiently, deployed securely, and monitored continuously. At the same time, organizations must ensure transparency and control to meet regulatory and risk-management standards.
Recognizing that organizations are actively seeking this level of AI infrastructure, FPT launched FPT AI Factory in Japan and Vietnam, equipped with thousands of cutting-edge NVIDIA GPUs, delivering exceptional computing power. With this computational strength, businesses are allowed to drastically reduce research time while accelerating AI solution development and deployment by more than 1,000 times compared to traditional methods. This creates vast opportunities for turning ideas into reality and applying AI to enhance efficiency and innovation across all areas.
Source: NVIDIA
