AI adoption in financial services reaches point of no return, says Finastra report

Artificial intelligence has moved from experimentation to essential infrastructure in global financial services, with nearly all institutions now using AI in some form. According to a new industry report by Finastra, the focus has decisively shifted from whether to adopt AI to how to scale, govern, and trust it across core banking and financial operations.

Artificial intelligence adoption in financial services has reached a critical inflection point, with institutions that still treat AI as a pilot initiative now firmly in the minority. According to Finastra’s Financial Services State of the Nation 2026 report, only 2% of financial institutions globally say they do not use AI at all, underscoring how deeply embedded the technology has become across the sector.

The report is based on a survey of 1,509 senior executives and managers from banks and financial institutions across 11 global markets, including the US, UK, Germany, Japan, Singapore, and Vietnam. It shows that six in ten institutions enhanced their AI capabilities over the past year, while 43% now identify AI as their single most important innovation lever.

AI is already operating across core financial functions — from fraud detection and risk management to document intelligence, compliance automation, and customer engagement. However, near-universal adoption means that simply deploying AI is no longer a competitive advantage.

From Pilots to Enterprise Pressure

The findings reveal a clear shift in mindset among financial institutions. Early-stage questions around whether to adopt AI or which use cases to test have largely disappeared. Instead, organisations are grappling with the operational challenge of scaling AI responsibly across the enterprise.

The most common AI use cases currently being run or piloted include risk management and fraud detection (71%), data analysis and reporting (71%), customer service assistants (69%), and document intelligence management (69%). These functions sit at the heart of financial operations, highlighting how central AI has become to daily decision-making.

Looking ahead, institutions are prioritising AI-driven personalisation, agentic AI for workflow automation, and stronger governance frameworks to ensure explainability and regulatory compliance. As AI-driven decisions increasingly affect customers and balance sheets, the ability to explain and audit outcomes is emerging as a critical requirement.

Infrastructure Becomes the Bottleneck

Despite high adoption rates, the report highlights a major constraint: legacy infrastructure. Nearly 87% of financial institutions plan to invest in modernisation over the next 12 months, focusing on cloud migration, data platform upgrades, and core banking modernisation to support scalable AI deployments.

However, the biggest barriers are human and financial. Talent shortages were cited by 43% of respondents as the primary obstacle to progress, particularly in markets such as Singapore, the UAE, Japan, and the US. Budget constraints remain another key challenge.

To bridge these gaps, institutions are increasingly turning to fintech partnerships, with 54% of respondents identifying collaboration as their preferred modernisation strategy rather than building capabilities entirely in-house.

Regional Differences in AI Maturity

The report also highlights varying levels of AI maturity across regions. Vietnam leads among surveyed markets, with 74% of institutions actively deploying AI, driven by financial inclusion needs and demand for faster payments and lending processes. Singapore is accelerating investment in cloud infrastructure and personalisation, with planned spending increases exceeding 50% year-on-year.

Japan remains the most cautious market, with just 39% reporting active AI deployment — reflecting a combination of legacy systems and a more incremental approach to technological change.

Governance Emerges as the Next Frontier

As AI systems grow more autonomous, governance challenges are intensifying. Around 63% of institutions are already running or piloting agentic AI — systems capable of executing multi-step tasks and making decisions with limited human intervention.

Such systems raise fundamental questions around accountability, transparency, and control. For boards, regulators, and customers, trust is becoming as important as performance. Financial institutions are now under pressure to move quickly on AI adoption while ensuring robust oversight and compliance.

Chris Walters, CEO of Finastra, said institutions must balance speed with responsibility as regulatory scrutiny increases and customer expectations rise. The report concludes that while the tipping point for AI adoption has been crossed, how effectively institutions govern and operationalise AI will shape competitive outcomes for the rest of the decade.

The research was conducted by Savanta in November 2025 and covered financial institutions across France, Germany, Hong Kong, Japan, Mexico, Saudi Arabia, Singapore, the UAE, the UK, the US, and Vietnam.