APAC fintech leaders flag agentic commerce & AI costs

Fintech executives across Asia-Pacific are highlighting agentic commerce, cross-border interoperability and AI cost governance as the next fault lines for the region's financial technology sector.

The comments come as industry leaders mark World FinTech Day and assess how rapidly shifting technologies are reshaping payments and financial infrastructure in APAC.

Michele Fung, Head of APAC at Unlimit, said artificial intelligence agents are beginning to alter the foundations of digital commerce. She leads the company's regional expansion strategy, focusing on market entry, local insight and partnership development across Asia-Pacific.

"Agentic commerce is set to become one of the most significant shifts in the next phase of fintech. As AI agents move from assisting consumers with discovery and recommendations to taking actions on their behalf, the way transactions are initiated, authenticated and completed will fundamentally change.

"For the fintech industry, this creates both a major opportunity and a new infrastructure challenge. Traditional payment journeys have largely been designed around a human actively moving through checkout. In an agentic environment, financial infrastructure will need to support transactions initiated by intelligent agents, potentially across platforms, markets, currencies and payment methods, while still ensuring every transaction is secure, authorised and transparent.

"This challenge is particularly important in APAC, where the payments landscape is highly fragmented. Consumer preferences, local payment methods, regulatory requirements and financial ecosystems differ significantly across markets. For agentic commerce to scale, the underlying infrastructure cannot rely on a one-size-fits-all model. It needs to connect global capabilities with deep local payment and financial infrastructure.

"The next stage of fintech innovation will be about more than making payments faster or more convenient. It will be about creating financial infrastructure that is intelligent, interoperable and flexible enough to support a new generation of commerce, where consumers, merchants and AI agents can transact seamlessly across borders.

"The fintech companies that solve this infrastructure challenge will play a critical role in determining how quickly agentic commerce moves from an emerging trend to a trusted, scalable part of everyday commerce," Fung said.

Infrastructure demands are also sharpening in traditional payments. Arun Kini, Managing Director, Payments, APAC at Finastra, said the spread of real-time payment rails has set the stage for a new interoperability race.

"APAC's payment future will not be defined by uniformity, but by interoperability. Across the region, real-time payment systems have developed at breakneck speed, reflecting each market's unique needs and regulatory environment. There is a massive, untapped opportunity to connect these systems seamlessly across borders, enabling faster, more transparent and more efficient movement of money. As real-time payments and atomic settlement become the norm, BFSIs must modernise legacy infrastructure, embrace API-enabled ecosystems and build platforms that can adapt to emerging technologies. APAC's diversity is no longer a constraint; it is proof of concept for global payments innovation," Kini said.

Payment fragmentation, regulatory differences and the rise of AI agents are converging with a third pressure point inside finance teams. Damien Passavent, Chief Product Officer and Head of Mid-Market Growth at Aspire, said AI has shifted from experimental spend to a material operating cost that demands new governance models.

"The conversation around AI is changing. Twelve months ago, most organisations were asking whether they should invest. Today, the more pressing question is how to control the cost of that investment without slowing innovation. Our Startup Signals data shows businesses are increasingly adopting multiple AI models for different tasks rather than relying on a single provider. That flexibility creates better outcomes, but it also introduces a new level of complexity for finance teams. Unlike traditional software, AI costs fluctuate with usage in a market evolving at extraordinary speed, making spending and forecasting significantly more complex.

"For CFOs, three priorities stand out. First, build visibility before trying to reduce costs. You can't optimise AI spending if you don't understand which teams, workflows or agents are driving it. Second, define value before measuring ROI. Productivity gains alone aren't enough. The real return comes from AI capabilities that can be trusted, scaled and reused across the organisation. Finally, protect an experimentation budget. Demanding immediate returns from every AI initiative risks discouraging the learning needed to identify the few use cases that ultimately deliver outsized value. The organisations that manage AI costs most effectively won't necessarily be those spending the most or the least. They'll be the ones that know where to exercise discipline and where to invest in building lasting organisational capability," Passavent said.