# Asia is leading the Agentic revolution by helping SMBs. What organizations around the world can learn.

- Link: https://www.thailand-business-news.com/pr-news/asia-is-leading-the-agentic-revolution-by-helping-smbs-what-organizations-around-the-world-can-learn
- Published: 2026-09-15T10:00:00+07:00
- Author: PR Newswire

SINGAPORE, Sept. 15, 2026 /PRNewswire/ — Asia’s financial institutions are rethinking
their approach to AI. The following is an article by Maxim Afanasyev at Google, 
and Zack Yang, Co-Founder at FOMO Pay, exploring that shift, and how FOMO Pay and
Google are working together to bring autonomous, agent-initiated payments to Asia’s
SMBs.

Asia has emerged as a digital and AI adoption leader, outstripping developed markets
that are weighed down by technical debt and legacy bureaucracy. This leadership 
is grounded on a foundational shift in how the region approaches change management
and the meaning of AI innovations.

Asian financial institutions, for example, initially rushed into AI just like their
peers in developed markets — by treating AI as a standard IT project with a pipeline
of use cases, which were often prioritized using profit margin versus ease of deployment
assessment. But then Asian organizations quickly realized that the right approach
to AI success looks different. 

Today, most Asian financial institutions start their AI journeys by studying how
their customers, partners and competitors adopt AI, and how such adoption changes
the meaning of the industry ("new economy").

Say you’re running a small business, like a cozy neighborhood restaurant, a sporting
goods retailer, or an automotive mechanic shop. The way your market operates is 
changing, and the reason is agentic AI. So financial institutions in Asia are shifting
their AI strategies towards helping small and mid-size businesses (SMBs) to adapt
to these changing markets.

This ‘aha’ moment for Asian financial Institutions happened a couple years ago when
they realized that treating AI transformation as a set of isolated IT use cases 
means joining the 95% of organizations getting no positive returns from AI ([MIT, 2025](https://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Business_2025_Report.pdf),
[BCG, 2025](https://www.bcg.com/publications/2025/are-you-generating-value-from-ai-the-widening-gap)).
Indeed the use case pipelines might be convenient for developers but the approach
ignores changes in business context, incentives, value proposition and even dependencies
between use cases. Productivity use cases frequently top under margin vs ease of
deployment criteria – scare employees about their jobs or outsource basic services
to unpaid customers ([Frey, 2026](https://www.nytimes.com/2026/05/11/opinion/ai-jobs-chores-work.html),
[Moradi et al, 2025](https://dl.acm.org/doi/10.1145/3711051)). Organizations focused
on AI use case pipelines struggled because motivations of employees and customers
were ignored. Or think about a bank deploying AI Agents to identify SME prospects
and send messages to them about its legacy financial products. The competing banks
are also using AI Agents for sending similar messages, and overloaded with content,
prospects not only get upset with the banks but lose motivation to act ([Iyengar, 2020](https://www.researchgate.net/publication/361083854_How_much_choice_is_good_enough_Moderators_of_information_and_choice_overload)).

As Asian organizations navigated through their journeys, leadership realized that
AI Agents assessed for productivity gains without the human context risk bringing
challenges instead of value. On the other hand, they observed that as AI adoption
among people spreads across Asia, it is transforming not just our economies but 
how our society thinks and acts. In this new world, financial firms focused on solving
pre-Agentic ("old economy") use cases are at risk of their offerings becoming irrelevant
to the wider market, similar to Kodak’s and Blockbuster’s a couple decades ago. 
The need to pivot AI strategy from focusing on internal optimizations to new value
propositions for customers became obvious.  

Reasons which helped Asian financial institutions to embrace this new way of thinking
include supportive and progressive regulatory environments (think about [Project Mindforge](https://www.mas.gov.sg/schemes-and-initiatives/project-mindforge)
in Singapore), a young and mobile-first population quickly adopting AI Agents for
daily routines (the average age in Asia is about 30 years, compared to 40 to 45 
in developed markets), regional diversity promoting new ideas, inherent agility 
due to rapid economic change over the past two decades, and an extensive fintech
community. With AI adoption reaching 60%+ of population in certain Asian markets(
[Stanford University, 2026](https://hai.stanford.edu/ai-index/2026-ai-index-report)),
local Financial Institutions have learned first that AI transformation thrives when
organizations move beyond viewing it as a technical IT project and instead foster
a decentralized culture capable of rapid, business-driven adaptation ([Afanasyev, 2026](https://cloud.google.com/transform/what-japac-banks-learned-about-ai-transformation)).
Such culture naturally includes guardrails grounded on AI governance principles 
and human-in-the-loop. The new way of thinking has accelerated AI successes in Asia,
and the highlights include "AI for good cause" case studies such as Thai [SCB Abacus](https://www.youtube.com/watch?v=0V8bDXYc8LM&list=PLWYw-NqNglu4kSAJtT2ZP6_gry7gY4fjF&index=8),
which is utilising data to expand credit access to more people, or Indonesian [Amar Bank](https://www.youtube.com/watch?v=VRFg76FOwFA&list=PLWYw-NqNglu4kSAJtT2ZP6_gry7gY4fjF&index=10),
which opens access to digital banking for underserved customers. One of the lessons
learned is that AI pays back best when used for a good cause such as helping SMBs
to grow their businesses. And this pivot in the AI agenda of leading financial organizations
is good news for ~200mn SMBs powering Asian economies. 

Let’s think through an example: Consider the payments process at a small restaurant
in the Holland Village neighborhood of Singapore. When an AI agent decides to reorder
ingredients for a restaurant, creating just a purchase order is not enough. The 
agent needs to pay. Automatically, without a need for a human in the loop to decide
whatever rail works best: card, bank transfer, or stablecoin. Most payment systems
today were not built for this. They were built for humans who analyze, click, confirm,
and authenticate. As AI agents become active participants in commerce, the infrastructure
underneath needs to catch up in order for small businesses to remain competitive.

It’s for this kind of use case that FOMO Pay and Google Cloud are building solutions.
In March 2026, FOMO Pay launched the FOMO AI Soundbox, Singapore’s first single 
device to accept cards, PayNow, e-wallets, and stablecoins at a single point of 
sale (POS). But the device itself is only part of the story. Beneath it sits a merchant
portal that captures the patterns of every transaction across the platform, and 
an AI layer in development that will surface real business insights for merchants,
without requiring them to hire analysts or build complex systems. For SMEs that 
have been running on manual processes and gut feel, that is a meaningful shift. 
The shift provides SMBs with capabilities previously available to large corporations
only. FOMO Pay believes that payment rails should not just be fast and connected,
but intelligent enough to support a world where AI agents, businesses and consumers
move as one.

To take the solution a step further, FOMO Pay has adopted Google’s Agent Payment
Protocol (AP2), an emerging open standard for autonomous, agent-initiated payments.
[In an early implementation demo](https://youtu.be/eYx4AyRTP8E?si=zLdUZQo_UpRnXmxB),
the restaurant sets a simple rule: when cabbage stock drops below 10 units, the 
system automatically identifies the right supplier, reorders and pays. The agent
monitors inventory, places the order, and completes the payment with minimal human
intervention. When merchants and suppliers are both participants in FOMO Pay, settlement
occurs as a direct internal transfer. This is an early glimpse of how entire procurement
and payment workflows can run on their own. The next generation of payment infrastructure
should not just move money. It should make decisions: programmable, intelligent,
and ready for a world where agents transact on behalf of businesses.

Agentic payments, however, require clear guardrails. AP2 addresses this through 
cryptographically signed mandates, user-approved authorizations that bind an agent
to predefined merchants, amounts, and conditions. Before any mandate is issued, 
explicit human consent is required. Each transaction then produces a signed audit
trail to support verification and dispute resolution. In this model, transactions
are anchored to deterministic proof of intent, not the probabilistic outputs of 
an AI system.

This work sets an example of a "customer needs first" approach to AI adoption and
contrasts with IT-led AI use cases that still exist at some legacy financial institutions.
FOMO Pay’s approach is grounded on the Business, Transformation, and Technology 
framework ([Afanasyev, Milind, 2026](https://www.technologyreview.kr/ai-%ec%93%b0%eb%82%98%eb%af%b8%ec%9d%98-%ec%b2%ab-%eb%ac%bc%ea%b2%b0%ec%9d%80-%ec%9d%b4%eb%af%b8-%ec%8b%9c%ec%9e%91%eb%90%90%eb%8b%a4/)).
For Business — analyzing changed context and redefining the company’s model, value
to customers, and competitive edge in an Agentic AI world. For Transformation — 
building the right processes and ways of working within and outside the organization.
Finally, for Technology identifying tools and technology partners to make it all
work.   

Asian organizations such as FOMO Pay have moved away from AI use case pipelines 
for "old economy" towards analyzing how AI adoption by customers, partners and adversaries
is changing the business model. This approach, which naturally focuses on customer
needs, good causes and needs of "new economy", is a secret source for Asia leadership
in AI – a sharp contrast with legacy organizations struggling with AI in developed
markets.

 

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**Read the original article :** [Asia is leading the Agentic revolution by helping SMBs. What organizations around the world can learn. ](http://www.prnasia.com/story/archive/5039111_AE39111_0?rand=184833)
