The adoption of AI in financial services has become virtually universal, but institutions that still treat AI as experiments are now outliers. Only 2% of financial institutions globally report not using AI at all, according to Finastra’s Financial Services Nation 2026 report, which surveyed 1,509 senior executives across 11 markets.
The discussion is over. The question is what happens next. For CIOs and technology leaders, the findings represent equal parts opportunity and pressure. Six in 10 institutions have increased their AI capabilities in the past year, and 43% cite AI as their most important innovation vehicle.
From fraud detection and document intelligence to compliance automation and customer engagement, AI is quietly being embedded across the financial value chain. However, near-universal adoption also means that adoption alone is no longer a differentiator.
From pilot to pressure
This report reveals a clear shift in how institutions think about AI. Initial conversations (whether to adopt or not, which use cases to try, how much to invest) have given way to more operational complexity. Agencies are now focused on scaling AI responsibly, managing it effectively, and ensuring it works across functions across the enterprise rather than in isolated departments.
The top four use cases in which institutions are running programs or experimenting with AI reflect their level of maturity. Risk Management and Fraud Detection (71%), Data Analysis and Reporting (71%), Customer Service and Support Assistant (69%), and Document Intelligence Management (69%).
These are not peripheral functions. They are at the center of financial institution operations and competition. Looking ahead, three priorities will govern the next phase: AI-driven personalization, agent AI for workflow automation, and AI model governance and explainability.
The last one is worth noting. As AI decisions become more important and come under more scrutiny, the ability to explain, audit, and uphold those decisions is becoming a regulatory and reputational imperative, not just technical beauty.
infrastructure issues
Large numbers of deployments can obscure the inconvenient truth that AI is only as good as the systems underlying it. Finastra’s data makes this connection explicit. Nearly nine in 10 institutions (87%) plan to invest in modernization over the next 12 months due to the need to effectively scale AI. Cloud adoption, data platform modernization, and core banking upgrades are all accelerating not as standalone efforts but as the foundational layer that will determine how far and how quickly AI can actually go.
But the barrier remains stubbornly human. Talent shortages are cited by 43% of institutions as a key barrier to progress, with challenges particularly acute in Singapore (54%), the UAE (51%), and Japan and the US (both 50%).
Budget constraints will soon follow. Leading institutions are increasingly turning to fintech partnerships (currently the default modernization strategy for 54% of respondents) to fill these gaps without incurring the full cost of building in-house.
Local situation
Across the Asia-Pacific region, the data reflects clear priorities. Vietnam leads the way in aggressive AI adoption with 74% due to the urgency of financial inclusion and the need for faster payment and loan processing. Singapore is aggressively increasing its investments in cloud and personalization, with spending set to increase by more than 50% year-on-year.
Meanwhile, Japan remains the most cautious market surveyed, with only 39% reporting active adoption of AI, reflecting traditional constraints and a culture that favors gradual rather than rapid change.
Governance is the next frontier
With 63% of institutions already running or piloting agent AI programs, the direction of this technology is clear. But so do the challenges it brings. Agentic AI (systems capable of autonomous decision-making and multi-step task execution) significantly raises the stakes for issues of accountability, transparency, and control.
For business leaders, next year will be less about whether to invest in AI and more about how to do so in a way that regulators, customers, and boards can trust. Chris Walters, CEO of Finastra, said: Financial institutions are being asked to act quickly and responsibly as regulatory oversight increases and customers demand financial services that work reliably, securely and privately at all times.
The tipping point has been passed. How institutions leverage that momentum, and how carefully they manage it, will determine the competitive landscape for the rest of the decade.
Finastra’s State of Financial Services 2026 report surveyed 1,509 managers and executives at banks and financial institutions in France, Germany, Hong Kong, Japan, Mexico, Saudi Arabia, Singapore, UAE, UK, US, and Vietnam. The study was conducted by Savanta in November 2025.
(Photo provided by: PR Newswire)
See: How financial institutions are incorporating AI decision-making
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