Only Small Group of Banks Are Turning AI into Revenue, New Research Finds

SINGAPORE, Feb. 5, 2026 /PRNewswire/ -- Dyna.Ai, a global provider of AI solutions, today released a new executive insights report, developed in collaboration with GXS Partners and Smartkarma, examining why most banks struggle to translate AI investment into revenue, and how a small group is breaking through. The report highlights how financial institutions across Southeast Asia, Latin America, and the Middle East are unlocking revenue through a small number of AI capabilities, while emphasizing the operational conditions required to scale these in production.

The research finds that banks successfully operationalizing AI personalization are achieving up to a 6% revenue uplift in the banking, financial services, and insurance (BFSI) sector. With BFSI AI spend projected to surge over 10x from $35 billion in 2023 to $368 billion by 2032, success will not be determined by the most pilots, but by those that move fastest to production-scale deployment with accountability for measurable outcomes.

Despite growing BFSI AI investments, most financial institutions remain in the pilot phase. New research confirms that while 77% of financial services executives report positive ROI within the first year, meaningful enterprise-wide impact remains elusive with accountability for operational outcomes lacking. Leading financial institutions across emerging markets are now closing this gap by anchoring AI to specific revenue outcomes, building responsibility from deployment to operational results, structuring partnerships for shared accountability and measurable impact.

"Most banks believe they are progressing with AI, yet research shows only 10% of the organizations using agentic AI are seeing significant, measurable ROI," said Tomas Skoumal, Chairman and Co-founder of Dyna.Ai. "This report shows where revenue is being created, and why many institutions are still stuck despite years of pilots -- a gap that is far wider than most executives expect."

"One thing that kept coming up in our executive interviews was how hard it is to scale AI entirely in-house," said William Hahn, Director at GXS Partners. "Many executives told us they underestimated the effort required beyond the pilot stage, and were increasingly open to partnering where execution and ownership could be shared."

Mobile-first markets and AI-driven wealth management in Southeast Asia

In Southeast Asia, a young mobile-first population and supportive regulatory frameworks are translating AI investment into measurable revenue impact. DBS Singapore generated $565M from 350 AI use cases in 2024, targeting $745M by 2025. Across the region, banks are applying AI across revenue-generating activities through mobile and digital customer channels, supported by the scale of the region's $300B MSME financing gap.

Sovereign AI ambitions and cross-border payments in the Middle East

Sovereign-led AI ambition and fintech momentum are accelerating AI adoption across financial services in the Middle East. PwC estimates AI could add $320 billion to the Middle East economy by 2030, with financial services at the core. Early impact is emerging in wealth management and cross-border payments, where financial institutions are deploying AI to scale relationship management, strengthen compliance, and enable faster, more reliable regional transactions.

Alternative data and fraud prevention unlocking Latin America inclusion

In Latin America, scale and risk remain the greatest constraint as financial exclusion and fraud risk continue to rise. With over 200 million adults remaining outside formal financial services in Latin America, AI-driven credit decisioning and fraud prevention are increasingly being applied to extend access to lending while maintaining risk discipline. Institutions such as BBVA Mexico demonstrate how AI-enabled decisioning can support broader inclusion without compromising risk controls.

Emerging market BFSIs are already unlocking AI revenue at scale

Across all three regions, organizational challenges such as data fragmentation, governance uncertainty, and adoption friction plague most BFSI implementations. Financial institutions that anchor AI to revenue outcomes and embed governance from day one are moving past experimentation into production-scale impact. BFSI organizations are now partnering on a Results-as-a-Service model where providers are paid for outcomes, not tools. As a global provider, Dyna.Ai operates with full-stack execution responsibility from domain-specific AI models through agentic AI agents and applications to operational results.

"The issue isn't experiments, it's accountability," said Tomas Skoumal. "Results-as-a-Service means tying AI deployments to measurable business outcomes, not tool adoption. That shift changes how enterprises think about execution when moving from pilots to production."

The full report, From Pilots to Production: How Banks Turn AI into Revenue, is available for download here.

About Dyna.Ai

Dyna.Ai is a leading AI-as-a-Service company headquartered in Singapore, delivering enterprise-grade AI solutions that turn advanced AI into measurable business results. The company provides AI-powered products and services that enhance customer experience (CX), improve employee experience (EX), and optimize core business operations, with solutions designed for practical enterprise deployment. With a global presence across Asia, the Middle East, and the Americas, Dyna.Ai powers financial institutions, contact centers, and enterprises worldwide. For more information, visit www.dyna.ai.