The generative AI boom is set to accelerate digital transformation throughout a range of industries and breathe fresh life into a banking ecosystem that still struggles with overcoming legacy processes. With payments already a focal point for challenger banks and fintechs, GenAI can help to deliver efficiency on a broader scale. 

Bloomberg data suggests that generative AI is set to grow into a US$1.3 trillion industry by 2032, and this will see use cases emerge throughout the field of finance. 

Crucially, the rise of generative AI will aid fintech in delivering more open finance services for customers in an impactful way. 

The emerging technology will also breathe new life into payment management and processing through the use of embedded finance, super apps, metaverse payments, decentralised wallets, cryptocurrency integration, and buy now pay later (BNPL) services, among many more functionalities. 

But how exactly will generative AI transform the payments landscape for consumers and institutions alike? Let’s take a deeper look at five key ways in which the GenAI boom will change the payments ecosystem forever:

Next-generation payments management

The natural ability of generative AI to operate alongside algorithms that can utilise complex structured and unstructured data is a key asset for driving transformation in the payments ecosystem. 

Generative AI can help stamp out instances of human error and deliver more accuracy throughout operations on a wider scale. 

Artificial intelligence can also help to streamline the routes taken throughout payment processing to add greater efficiency through each interaction in the process — whether the payments are actioned domestically or internationally. 

With the help of analysing data and generative algorithms, AI models can autonomously select the most efficient and cost-effective methods, helping to drive more value for all parties concerned.

This added element of digitalisation paves the way for faster payment processing and stronger cash flow management. 

Also Read: Unleashing the power of specialised AI startups in the era of generative AI

By mitigating instances of human error, artificial intelligence models can also prevent costly mistakes due to payment inaccuracies and deliver greater levels of customer satisfaction as a result.

Invoicing autonomy

One jarring legacy process that’s still prevalent in the world of payments revolves around invoicing. With paper invoices and email attachments still commonplace among billers requesting payments, this crucial financial service remains largely inefficient. 

Legacy billing involves the manual input of bank details which is prone to both delays and human error. However, generative AI can help to automate this process in its entirety by extracting payment information from invoices, removing the risks attached with manually inputting bank details. 

Through machine learning algorithms, AI systems can also actively monitor invoices and payments for any errors between the biller and the customer to assist any manual tasks within the payment process. In practice, this would help to match invoices to payments and reconciling accounts. 

Automating payouts can transform trust in a range of industries. Throughout supply chains with vendor payouts and marketing with AP automation, it’s possible to leverage payments through flexible international route payments based on structured analytical performance insights.

Stamping out fraud

Because of the seamless ability of AI to analyse significant volumes of data almost instantaneously, the emergence of generative AI can be an excellent tool in preventing instances of fraudulent activity in payments. 

All card transactions generate significant volumes of data points, and much of it has the potential to identify and stamp out fraud among transactions online. 

Whenever a payment is processed, generative AI can automatically analyse data alongside a machine learning (ML) algorithm that’s trained to spot trends surrounding fraud to make a rapid decision to approve or flag the transaction for suspicious activity. 

As digital transformation continues to transform how payments are made, fraudulent activity can be a challenging prospect for many fintech firms and traditional institutions alike. It’s through advanced GenAI solutions that all institutions can actively monitor and protect against fraud in real-time to a safer financial ecosystem for all.

Advanced product prototyping

Another area of finance that holds great potential due to the arrival of generative AI is product prototyping. Large language models (LLMs) like GPT-3 are capable of generating sample code for virtually any purpose. This opens the door to GenAI tools seamlessly generating code for prototype products and services. 

Also Read: Why AI needs context and curiosity, not toxic positivity

In a financial landscape that’s already actively embracing open finance services, generative AI is capable of accelerating the growth of this industry subsector by producing efficient coding for brand-new features in the space for fintechs to pioneer. 

Additionally, the programs can take on board feedback to improve its own code to improve the product and fine-tune its capabilities. 

For fintech startups, this means more innovation for fewer resources that can serve a variety of functions and are rapidly tested. In terms of payment integrations, this prototyping landscape could significantly improve the time to market for new payment features and efficiencies.

Embracing personalised marketing

Generative AI can also help payments providers to market their products more effectively. From in depth market research powered by the interpretation of large data sets by artificial intelligence to the creation of marketing materials for hyper-specific audience segments, it’s possible to market directly to leads in an unprecedented manner. 

Because LLMs have the ability to automatically generate content based on simple prompts, it’s possible for payments providers to produce customer-specific generative AI content in a way that perfectly matches the expectations of the customer, no matter where they are in the world, and can help to be a driving force in converting leads into conversions on a larger scale. 

Timely boost to payments transformation

The arrival of generative AI will have a major impact throughout a vast range of industries, but its implications for the payments landscape can’t be underestimated. 

Open finance will be built on the foundations of the free flow of data and its conversion into efficient services and actionable insights. Generative AI will drive this transformation and help to make payments more efficient no matter who the parties involved are or where they are in the world. 

Additionally, the combination of ML and LLMs will introduce a new level of security and personalisation to the landscape that can help customers feel more valued and safe when making payments on a global scale. 

The age of generative AI is upon us, and its positive implications in the world of finance will be felt by everyone.

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How do you turn a napkin sketch into a global product with a lean budget, and do it on a lean budget?

It’s a question many early-stage founders wrestle with, especially when resources are tight but ambitions are sky-high. A few years ago, I found myself in the middle of one such journey. A founder with a bold fintech idea and limited funds reached out, unsure how to bring his vision to life without breaking the bank. What followed was a cross-border collaboration that not only solved his problem but launched a product now used across the world.

Here’s a case study from my own experience: a founder with a big idea teamed up with a Vietnam tech team, and together we launched something the world uses today.

The challenge

A couple of years ago, I met a founder from the UK with an ambitious idea in the fintech space. He had deep industry knowledge and a solid business plan, but one major hurdle: a limited budget to build the product. Local development quotes were sky-high and threatened to sink the project before it even started. That’s when I suggested a different path: build his tech team in Vietnam.

He was intrigued but cautious. Would a remote team understand the complex fintech requirements? Could they build a world-class product from halfway across the globe? I introduced him to a small squad of Vietnamese engineers I knew – smart, young, eager developers who had worked on similar projects. After one video call (and a lot of tough technical questions from the founder!), we decided to give it a go.

Building the team

We started with a core team of five developers in Ho Chi Minh City, plus the founder and me on the product side. From day one, we ran it like a unified team. Daily stand-ups bridged the four-hour time difference.

The founder shared his vision and industry insights with the Vietnam team, and in turn, the developers offered clever solutions to localise the app for global markets. I remember waking up to Slack messages at three AM – not with problems, but with prototypes of new features the team had built while I slept! Their enthusiasm was off the charts.

Also Read: Why founders should train like runners

Within three months, this cross-border team built the first MVP of the fintech platform. We rolled out a beta to a small group of users in Europe simultaneously to gather diverse feedback. After a quick iterative cycle (thanks to the team’s rapid turnaround), we launched globally in our 6th month. The result? Users from over three countries signed up in the first week.

Scaling to global product

Over the next year, the Vietnam team grew to 15 strong as user demands and feature requests expanded. Because of the cost savings, the startup had funds to scale marketing and customer support. The product kept improving every sprint. Founder flew to Vietnam and spent a month with the team, aligning the roadmap and soaking up domain knowledge.

By the end of year one, that little startup had 50,000+ users worldwide and attracted a round of venture capital that valued it in the eight figures. And yes, the entire development team was still proudly based in Vietnam.

Key takeaways

• Talent and dedication win: The Vietnam team’s skill and dedication were the linchpin. They weren’t just contractors; they felt like co-founders. They often suggested features to make the product better for global users, not just blindly coding tasks. This ownership mentality accelerated innovation.
• Speed via time zones: Our 24-hour development cycle (UK/Vietnam overlap) became a secret weapon. While the founder slept, code got written; by morning, things had progressed. We turned what could have been a challenge into a speed advantage.
• Cost efficiency = longer runway: Building the team in Vietnam saved an estimated 60 per cent on development costs. That money went straight into user acquisition and cloud infrastructure to handle growth. The extended runway meant we could focus on refining the product instead of constantly worrying about the next fundraise.
• Cross-cultural team, one vision: We treated the Vietnam developers as equal partners in the mission. The founder held virtual town-halls with the whole team, ensuring everyone understood the why behind the product. This cross-cultural unity – European domain expertise and Vietnamese technical talent – was key to creating a product that appealed to users globally.

What started as an idea and a tight budget turned into a global fintech product success – largely because we leveraged the power of Vietnam’s tech talent through a partnership approach. It’s a model I’ve now seen work multiple times, in different industries, not just fintech.

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Asia-Pacific’s cross-border payment volume is on track to hit US$23.8 trillion by 2032, nearly doubling from US$12.8 trillion in 2024. But behind the headline growth lies a fragmented payment infrastructure where regional scale remains a costly ambition rather than a given.

A new report from Money20/20 and FXC Intelligence, launched at Money20/20 Asia in Bangkok, lays out the numbers – and the growing urgency – for interoperability across Asia’s diverse markets.

“Asia’s payments landscape is evolving quickly, but also with remarkable complexity,” said Daniel Webber, Founder and CEO of FXC Intelligence. “This report underscores the need for intentional collaboration across borders, sectors, and technologies to create truly inclusive financial ecosystems. Interoperability isn’t just a tech challenge—it’s a regional opportunity.”

Growth masks fragmentation

Asia-Pacific’s share of global cross-border flows is expected to rise from 32.2 per cent to 36.8 per cent by 2032. But volume alone does not mean market readiness.

“Growth figures reflect strong momentum but hide deep market disparities,” says Fernanda De Fino, Director of Global Risk & Compliance at EBANX, a global fintech specialising in payments in 29 emerging markets across Latin America, Africa, and Asia. “What works in Singapore doesn’t port over easily to markets like Indonesia or Vietnam”, she adds.

EBANX’s Beyond Borders 2025 report highlights the recent growth of new payment methods, largely driven by emerging economies, and signals significant changes in global consumer behaviour. These methods, characterised not only by their real-time transfer capabilities but also by their seamless, mobile-born, and digital-first operations, are redefining how people engage with financial transactions and fostering the growth of digital commerce.

Though many of these alternative payment methods (APMs) weren’t initially designed for paying merchants, their deep integration into daily life makes them the dominant choice for online purchases in many countries. 

Also Read: How to build deep tech startups across borders

Southeast Asia and India together are projected to see a 122 per cent increase in consumer spending over the next decade, outpacing Latin America (57 per cent) and Africa (103 per cent). According to Statista data in Beyond Borders, online sales are projected to grow by 14 per cent annually across emerging Asian countries over the next two years, with India leading the charge.

Regional players—both large and small—looking to expand must adapt to diverse consumer behaviors and fragmented tech ecosystems. Success hinges on understanding markets shaped by peer-to-peer (P2P) payment habits, which are now accelerating the shift toward digital commerce among new users.

Why interoperability is the next big fintech battleground

Startups looking to win in cross-border payments need a dual approach: deep local integration paired with regional interoperability.

Despite 88 per cent of industry stakeholders rating interoperability as “very or extremely important,” there’s little consensus on how to achieve it.

Real-time payment systems are seen as the most likely driver of integration (66 per cent), followed by digital wallets (59 per cent). But regional fragmentation persists, with no dominant cross-market infrastructure gaining real traction.

“We’re seeing a significant acceleration in how cross-border money moves, and the next decade will be crucial in shaping the infrastructure that powers it,” said Scarlett Sieber, Chief Strategy and Growth Officer at Money20/20. “Asia’s future lies not in a one-size-fits-all model, but in interconnected systems that balance innovation with regional adoption.”

QR codes: A missed opportunity?

Take QR codes, hailed as the low-cost rails for financial inclusion. Thailand’s PromptPay, Singapore’s NETS QR, and Indonesia’s QRIS were all built with similar aims. Yet they run on incompatible specs.

Efforts like ASEAN’s Project Nexus aim to link these systems, but progress has been slower than fintech founders hoped. Even successful efforts like Singtel’s VIA alliance remain limited in adoption beyond core territories.

Meanwhile, China’s WeChat Pay and Alipay continue expanding in the region, adding pressure on local players to compete, or connect.

What founders need to know about Asia’s regulatory maze

The report singles out regulatory complexity as a top barrier to scale. 86 per cent of respondents cite policy discrepancies, from KYC requirements to data localisation, as a persistent challenge.

Also Read: Learn the ropes around scaling your startup across borders

“E-wallet rules in markets like Indonesia and Vietnam are constantly evolving, which demands higher compliance standards,” says De Fino. “These changes may create new challenges for fintechs entering these markets.”

Singapore’s sandbox model is seen as a bright spot, but elsewhere, inconsistent rules slow expansion and discourage early-stage fintechs from attempting cross-border moves too soon.

Partnerships: Fintech’s real-world solution to fragmentation

91 per cent of fintech leaders agree that partnerships will shape the region’s infrastructure future. But making those partnerships work is easier said than done.

“The successful ones are balanced, technically, commercially and regulatorily,” says De Fino. “You need clear value for all parties, not just the biggest player.”

Past attempts at integration show the pitfalls: enthusiasm at launch, but little traction when business models aren’t aligned.

Don’t forget inclusion

A major blind spot in the race for scale? Financial inclusion. The unbanked and underbanked still make up a significant portion of the population in Southeast Asia.

Agent banking and cash-in/cash-out points remain critical in countries like the Philippines and Indonesia. Any real cross-border solution must account for these users, or risk leaving millions behind.

Bottom line

Cross-border payment volume in Asia is booming — but founders and fintechs should resist the hype cycle. Regional expansion won’t be plug-and-play. It’ll require local-first design, regulatory foresight, and above all, partnership.

The US$23.8 trillion opportunity is real. But the rails to get there are still under construction.

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The APAC travel sector is booming — airports are packed, hotel bookings have surged, and tourism numbers in countries like Thailand, Japan, and Indonesia are surpassing pre-COVID-19 levels. According to the Pacific Asia Travel Association (PATA), international visitor arrivals in APAC are expected to exceed 500 million by 2026.

But behind this growth story lies an unsolved operational problem: payments.

While the front end of travel has become frictionless — with intuitive mobile apps, AI-driven recommendations, and 24×7 booking — the payment infrastructure that powers these experiences remains fragmented, and often invisible until it fails. And it fails often, especially across borders.

The hidden complexity of travel payments

Travel isn’t like other verticals. It’s inherently time-sensitive, emotionally charged, and cross-border. That makes the role of payments uniquely critical. In my conversations with airlines, hotels, and OTAs, I identified these key pain points:

• Fragmented payment ecosystem

For travel merchants — airlines, OTAs, or hotel chains — the payment process isn’t a simple swipe. It involves a labyrinth of interconnected players: GDS platforms like Amadeus and Sabre, IATA settlement systems, payment gateways and acquiring banks, card networks and local wallets, Property Management Systems (PMS), travel agents, and B2B settlement intermediaries. Each plays a critical role in the transaction journey, yet no one is fully in control.

• Cross-border complexity

A traveler in Kuala Lumpur may use GrabPay, one in Tokyo prefers cards, and another in Sydney pays via Apple Pay. Add to that dynamic currency conversion, foreign exchange fees, and country-specific payment regulations. With travellers coming from different countries and using different currencies and methods, cross-border payments must be seamless.

Also Read: Asia’s cross-border payment surge: A US$23.8 trillion opportunity with fragmented solutions

• Reconciliation across markets and channels

Managing payouts, commissions, and settlements across countries and systems — whether online, in-app, or point-of-sale — is operationally heavy. Without unified reporting and reconciliation, finance teams are left to piece together fragmented data manually, risking errors and delays.

• High drop-off risk at checkout

Unlike retail, where a failed transaction might lead to a later retry, travel purchases are often time-sensitive. If a customer can’t use their preferred method or faces a failed payment, they’re more likely to abandon the booking and switch platforms — costing businesses immediate revenue and long-term loyalty.

• Refunds, cancellations, and disputes

The volatility of travel – weather delays, visa issues, changing plans – means refund handling and reversals need to be just as smooth as payments themselves. A clunky refund process creates friction and erodes trust.

• Missed opportunities for loyalty and up-sell

When payments are treated as a backend function, opportunities to drive loyalty, bundle ancillary services, and personalise offers at the point of payment are often lost.

• Fraud risk, compliance, and data control

Travel payments are high-risk by nature — with large transaction values, frequent international bookings, and elevated fraud potential. At the same time, travel merchants must navigate country-specific compliance mandates, data localisation rules, and privacy regulations. Without unified oversight and controls, the result is false declines, audit gaps, and lost trust.

Simply put: payments have become a bottleneck to growth. Travel brands need payment infrastructure that’s not just reliable, but also smart, flexible, and built for global-local realities.

One emerging approach to these challenges is payment orchestration, which unifies diverse payment systems into a central infrastructure

Orchestration platforms serve as a middleware layer, aiming to improve coordination between different parts of the payment system. Think of it as a “control tower” for payments — overseeing, optimising, and routing every transaction for maximum efficiency.

How orchestration platforms are changing the payments landscape

Modern orchestration platforms are purpose-built for complex, multi-market industries like travel. Here’s how orchestration helps travel brands simplify operations and unlock growth:

• Single unified platform

Travel payments involve many moving parts: from GDS and IATA systems to acquiring banks, card networks, PMS platforms, and POS systems. An orchestration platform connects them all into a single interface, helping travel merchants centralise control while preserving flexibility.

Also Read: Taking control of your payments: Why payment orchestration is becoming a necessity

• Seamless cross-border payment acceptance via local integrations

Activating region-specific payment options — like GCash in the Philippines, Dana in Indonesia, or UPI in India — is critical to conversion in diverse APAC markets. Orchestration simplifies cross-border payment acceptance with plug-and-play integrations for local methods, cards, BNPL, and bank transfers — helping merchants deliver preferred payment experiences to global travellers.

• Streamlined omni-channel reconciliation

Travel merchants often juggle payments across direct websites, mobile apps, offline counters, and partner channels — spanning multiple countries and currencies. Orchestration unifies these data flows into one system, enabling automated reconciliation across geographies and touchpoints. This reduces manual effort, speeds up settlements, and ensures financial accuracy at scale.

• Intelligent routing for improved success rates

By dynamically selecting the optimal payment path for each transaction — based on issuer preferences, network costs, customer geography, or real-time performance data — orchestration platforms reduce failures and false declines. Add in network tokenisation and intelligent retries, and merchants can boost success rates by up to 5–10 per cent.

• Automation for complex workflows

Travel payments are filled with edge cases — partial cancellations, no-shows, split payments, and refund reversals. Orchestration platforms handle these complexities with automated workflows, reducing manual overhead and ensuring faster, error-free resolutions.

• Payments as a growth lever

For travel merchants, orchestration platforms offer potential operational benefits when expanding into new markets

By linking payment identity with CRM systems, they also unlock personalised checkout experiences: from loyalty points redemption to upsell opportunities and pricing innovations like “price lock.” This future-proofs the payment infrastructure while turning it into a lever for customer satisfaction and revenue growth.

More importantly, orchestration platforms bring the agility travel companies need to scale internationally, adapt to regulatory shifts, and reduce dependency on multiple partners.

The road ahead

Some companies in APAC have begun exploring orchestration platforms to improve cross-border payment operations to build future-ready payment stacks that can streamline operations, improve payment success rates, and build checkout experiences that convert.

As travel becomes increasingly digital, personalised, and embedded across channels, payments can no longer be treated as an afterthought. They are not just a backend function; they are a strategic layer that drives customer loyalty, conversion, and profitability.

So, is the future of travel payments already here? Not quite. But with orchestration, we now have the blueprint.

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Boards in Asia have long been seen primarily as oversight bodies – monitoring management, reviewing reports, and approving major decisions. That model worked in a more stable, predictable era. But the landscape has changed: disruption is constant, stakeholders demand transparency, and the speed of decision-making has accelerated. The future of governance requires boards to move beyond oversight toward genuine strategic partnership with the C-suite.

Boards that embrace this shift strengthen resilience, accelerate innovation, and create sustainable shareholder and stakeholder value.

Why traditional board-management interaction is insufficient

Historically, boards received information from executives and provided approval or challenge. This model has three limitations:

• Delayed insights: By the time reports reach the board, critical opportunities or risks may have passed.
• Reactive decision-making: Boards react to what has already occurred rather than shaping strategy in real time.
• Limited value-add: Directors with deep expertise often spend most of their time reviewing compliance reports rather than influencing strategic decisions.

In today’s environment, this approach undermines agility. Boards must actively engage in forward-looking dialogue that informs, challenges, and guides executive strategy.

The strategic partnership model

The boards that excel in Asia are adopting a collaborative framework while maintaining independence. Key elements include:

• Structured engagement

Boards and executives should establish clear communication rhythms – monthly strategic briefings, quarterly deep-dives, and scenario workshops. These sessions focus on emerging risks, market opportunities, and strategic options, not just historical performance.

• Role clarity

While partnership is essential, boundaries must remain clear:

• The board sets strategic direction, risk appetite, and governance principles.
• The C-suite executes strategy, manages day-to-day operations, and recommends capital and resource allocation.

Clear delineation prevents overreach and ensures accountability.

• Joint scenario planning

Boards and executives should co-create scenarios for market disruption, regulatory change, technological innovation, and talent shifts. These exercises allow both parties to anticipate shocks and stress-test assumptions before crises occur.

• Risk integration

Strategic decisions and risk management must converge. Boards should engage with management to understand enterprise-wide risk, including emerging risks in AI, cybersecurity, climate, and geopolitics. Together, they can align risk appetite with strategic goals.

Also Read: Cybersecurity and data governance in the boardroom: A strategic imperative for Asian boards

Benefits of close board — C-suite collaboration

Boards that partner effectively with executives enjoy several advantages:

• Faster decision-making: Timely insights from the board accelerate strategy execution.
• Better risk management: Shared understanding of potential disruptions reduces blind spots.
• Stronger innovation: Constructive challenge drives creative solutions and identifies new market opportunities.
• Enhanced organisational resilience: Coordination between governance and execution ensures adaptability under stress.
• Improved trust and accountability: Clear communication strengthens relationships between directors, executives, and stakeholders.

Collaboration does not dilute independence — when done correctly, it amplifies oversight effectiveness.

Building a collaboration-ready board

To move from oversight to partnership, boards must:

• Upgrade capabilities: directors need skills in technology, ESG, human capital, and geopolitics to engage meaningfully.
• Invest in board education: workshops, executive briefings, and site visits ensure directors understand business dynamics and emerging trends.
• Embed collaboration in culture: encourage open, constructive debate while maintaining respect for executive decision rights.
• Use data-driven insights: dashboards and scenario modelling allow directors to challenge assumptions based on facts, not intuition.
• Regularly review collaboration effectiveness: survey executives, assess board contribution to strategy, and adjust engagement rhythms.

Boards that systematically implement these practices strengthen both governance and enterprise performance.

Also Read: From classroom to boardroom: How Singapore’s universities nurture future investment leaders

The future role of the independent director

Aspiring independent directors must recognise that their value lies not just in oversight but in strategic contribution. The best directors:

• Ask tough questions while fostering a collaborative dialogue
• Bring cross-industry perspectives and expertise
• Anticipate emerging risks and opportunities alongside management
• Help align long-term strategy with operational execution

Independent directors who excel in this collaborative model will become highly sought-after assets on Asian boards navigating uncertainty.

Partnership without compromise

The future of board-C-suite collaboration is not about blurring governance lines. It is about structured, disciplined, and forward-looking engagement. Boards must maintain independence while actively shaping enterprise strategy, risk posture, and long-term value creation.

Boards that successfully transition from passive oversight to strategic partnership will position their companies to thrive in complexity, disruption, and uncertainty – turning governance into a source of competitive advantage.

This article was first published on The Boardroom Edge.

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Southeast Asia’s startup ecosystem continues to mature rapidly, with founders increasingly building companies that operate across multiple markets from day one. Expansion into hubs such as Singapore, Hong Kong, the UAE, and the United Kingdom is often a natural next step, but navigating incorporation requirements, compliance obligations, accounting standards, and corporate governance can quickly pull focus away from innovation and growth.

As digital business infrastructure evolves globally, companies are looking for streamlined, technology-enabled solutions that reduce administrative overhead while maintaining regulatory confidence. This need is particularly pronounced in Southeast Asia, where regulatory environments vary widely. Osome addresses these challenges by combining AI-enabled software with expert human support, helping businesses manage incorporation, accounting, compliance, and corporate secretarial requirements so founders can focus on building and growing their businesses instead of financial admin.

Meeting Osome at Echelon Singapore 2026 offers founders and operators a chance to explore how streamlined business infrastructure can support faster expansion. Whether entering Singapore for the first time, scaling regionally, or preparing for international growth, practical guidance on compliance and operational setup can make a measurable difference in execution speed and confidence.

Osome: Leading the way in digital business services

Osome is a digital business service provider focused on helping entrepreneurs start, manage, and grow companies across Singapore, Hong Kong, the United Kingdom, and selected international markets. Its mission centres on making entrepreneurship more accessible by removing administrative and compliance barriers that often slow early stage and growth stage companies.

The company combines AI and automation with professional expertise to deliver incorporation support, accounting services, corporate secretarial solutions, and compliance management through an integrated digital platform. This hybrid approach allows businesses to benefit from efficiency and transparency while still having access to experienced professionals when navigating regulatory requirements.

Osome’s regional relevance is particularly strong in Southeast Asia, where cross-border expansion is increasingly common. Partnerships with venture capital firms, accelerators, incubators, co-working spaces, and other ecosystem enablers further strengthen its role as a practical support layer for founders scaling across markets.

Also read: Scaling Southeast Asia: Who to meet at Echelon Singapore 2026

Meet Osome at Echelon Singapore 2026

Osome joins Echelon Singapore 2026 as a preferred incorporation partner, alongside other ecosystem leaders, founders, investors, and innovators gathering at Suntec Singapore CEC on 3-4 June 2026. The two-day event brings together the region’s startup community through content stages, exhibitions, networking sessions, and knowledge-sharing opportunities designed to support Southeast Asia’s innovation economy.

Attendees can connect with the Osome team to discuss incorporation strategies, compliance planning, and cross-border expansion considerations. The company will offer consultation packages and discounted incorporation services tailored for startups and SMEs attending Echelon, creating a practical entry point for businesses preparing to scale regionally or internationally. Book a call with Osome here to get started.

As Southeast Asia’s innovation economy continues to evolve, strong operational foundations are becoming essential to sustainable growth. Collaboration between founders, infrastructure providers, investors, and ecosystem enablers helps ensure that companies can scale efficiently while remaining compliant and resilient. Platforms like Echelon play a key role in enabling these connections and supporting the next phase of regional innovation.

The region is evolving quickly, and Echelon Singapore 2026 offers the right place at the right moment to be part of what comes next. Register here to join the conversation.

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When global researchers predicted that speech recognition for low-resource languages wouldn’t be commercially viable until 2030, we had already achieved 97 per cent accuracy in 2020. This isn’t a story about one company – it’s about how developing nations can build AI sovereignty by solving real problems, building infrastructure patiently, and getting creative with talent.

After 25 years of building language technology in Mongolia – from basic character rendering to complex reasoning systems – I’ve learned that the path to AI independence requires three things: sustainable development, pragmatic focus on real missions, and a bigger vision. Here’s what actually works.

Start where problems challenge society

Silicon Valley starts with solutions looking for problems. Developing nations must start with problems demanding solutions. Mongolia’s AI journey began with frustrations that might sound trivial to outsiders but were paralysing daily life:

• The typing crisis: We literally couldn’t type in our traditional vertical script. Eight centuries of written culture were becoming digitally extinct. This wasn’t a market opportunity – it was cultural death in slow motion.
• The dictionary that wasn’t: No comprehensive digital Mongolian-English dictionary existed. Students and professionals relied on dusty paper editions from the 1960s. Every missing translation represented a lost opportunity.
• The spellcheck absence: Mongolian text had no spell-checking. Government documents, business contracts, and academic papers were riddled with errors that undermined credibility and caused actual legal disputes. That was one of the biggest social problem until 2017.
• The language corruption crisis: Here’s something that keeps me awake at night – we’re raising a generation that speaks broken Mongolian. Young people unconsciously rely on Google Translate for homework, social media, and daily communication. But Google Translate’s Mongolian support is so poor that it’s literally corrupting our language. Students write essays in grammatically incorrect Mongolian, thinking it’s proper because “Google said so.”
• The speech recognition gap: Parliament and government operate through meetings, making transcription a critical function. Without speech recognition, protocol-keeping consumed enormous human resources. And solutions had to be on-premise for security.
• The service crisis: Banks and telecoms haemorrhaged money on customer service. Without automated Mongolian language support, every query required human agents.
• The procurement corruption: At Erdenet Mining, Mongolia’s largest company, manual tender evaluation enabled systematic corruption. Millions disappeared into rigged contracts or excessive delays in purchase completion.

Each problem we solved provided data, experience, and credibility for the next challenge. Our fully automatic tender evaluation system at Erdenet didn’t just save money and reduce corruption – it generated the revenue and trust that funded our speech recognition and language model research.

This problem-first approach built our capabilities organically. By the time we tackled large language models, we had accumulated 20 years of linguistic data, domain expertise, and customers who trusted us.

Harness your diaspora’s expertise

Mongolia has more software engineers in Silicon Valley, Berlin, Seoul, and Tokyo than in Ulaanbaatar. This brain drain, common across developing nations, became the cornerstone of our talent strategy.

The diaspora advantage

We couldn’t compete with FAANG salaries. Instead, we offered something money can’t buy: the chance to build their homeland’s technological future. Our pitch was simple: “Your skills + our mission = your legacy.”

AI Engineers from Germany, Switzerland, Italy, and the US were invited to work on-site, fostering knowledge exchange with local talent. They mentored, contributed code, and validated technical decisions, creating a sustainable talent flow instead of a one-way brain drain. This approach assured young engineers that they could venture out, gain experience, and return to impactful work.

Also Read: On-chain data and Web3 security: Insights from industry experts

Build infrastructure with extreme patience

Infrastructure has been our greatest challenge from day one. We move slowly, but we move forward. Our datacenter evolution tells the story of patient building:

We started in 2017, purchasing two gaming GPUs (RTX 2090 Ti). By 2019, we had received angel investment to buy our own L40S GPUs. In 2021, we added A6000 units. Today, we run our own infrastructure with local hardware for sensitive data. We use cloud resources from AWS and Google to train bigger models.

We manage everything ourselves – not by choice, but by necessity. No managed services exist for our use cases. This forced us to develop deep infrastructure expertise that later became a competitive advantage.

The lesson? Start with whatever computer you can access. Our first speech recognition model was trained on two gaming GPUs for one year. Perfect infrastructure is a luxury, developing nations can’t afford to wait for.

Competitive advantage

Cultural localisation

The assumption that AI models can simply be “translated” fundamentally misunderstands how language and culture intertwine.

The mixed language reality

Mongolians don’t speak “pure” Mongolian. Never have, never will. Real conversations flow like this:

• Mongolian grammar structures with English tech terms embedded
• Russian expressions from the Soviet era sprinkled throughout
• Chinese trade phrases when discussing business

Our models had to understand “Kodoo push hiigeed product ownertoo мэдэгдчихлээ.” (I’ve pushed the code and notified the product owner.). When we insisted on linguistic purity, our models failed spectacularly. When we embraced messy reality, they worked.

Release strategy that makes sense

While big tech companies focus on the “top 20 languages” and throw everything else into an “other” bucket, we take a different approach. For each market, we focus on the languages that actually interact. For Mongolia, that means:

• Mongolian (obviously)
• English (global connectivity)
• Russian (historical ties)
• Chinese (trade relationships)

This connected-language approach delivers 10x better results than generic multilingual models.

Also Read: High adoption, low understanding: The Philippines’s blockchain knowledge gap

Data sovereignty

Your data will be securely stored within your country’s territory, allowing you to use it with peace of mind. If governments fail to actively embrace and utilise artificial intelligence, they risk falling behind, potentially leading to significant social inequality within their societies.

Digital sovereignty through pragmatic building

True sovereignty means controlling critical layers while pragmatically using what works.

What we built ourselves:

• Character encoding and input methods (100 per cent local)
• Finate state automata and transducers as language complexity (100 per cent local)
• Speech recognition and synthesis (100 per cent local)
• Core language models (100 per cent local)
• Application frameworks (80 per cent local, 20 per cent open source)
• Infrastructure management (60 per cent local, 40 per cent standard tools)

The honest trade-offs:

• We use NVIDIA hardware (no alternative yet)
• We leverage open-source frameworks (why reinvent PyTorch?)
• We adapt international research (standing on the shoulders of giants)
• But we control all critical paths and data

Economic sustainability:

Sovereignty without economic sustainability is just expensive nationalism. Our model evolved through necessity:

• Government as first customer, not sugar daddy
• Enterprise solutions funding research
• Open source contributions building global goodwill

The uncomfortable truths

Let me be honest about what building AI in a developing nation really means:

• You’ll never have enough resources. We have 1/1000th of OpenAI’s budget. Make constraints drive innovation. Our GPU shortage forced us to optimise models that now run on minimal hardware
• Technical debt is inevitable. Plan refactoring cycles from day one. We still maintain code from 2017 because it serves critical government systems.
• International competition will arrive. Build cultural moats early. By the time OpenAI or Google supports Mongolian properly, we’ll have ten years of local context they can’t replicate.
• Talent will always be scarce. Create compelling missions. We can’t match Silicon Valley salaries, but we offer something better: the chance to preserve their culture through technology.
• Trust is your biggest challenge. When we first claimed 97 per cent accuracy in Mongolian speech recognition, nobody believed us. International researchers said it was impossible. Now, the customers and government say, “Why not just use ChatGPT?” You need rock-solid local success stories. Building credibility took years of consistent delivery.

Also Read: Asia rises in the AI chip race: China to outgrow US by 30 per cent by 2030

The future is distributed

The era where a few companies in a few countries control global AI is ending. The future belongs to distributed, culturally-rooted AI systems serving specific populations with a deep understanding.

Mongolia’s journey from missing keymaps to billion-parameter models proves that developing nations don’t need charity. Don’t blame Silicon Valley for ignoring your market – they don’t owe you anything. Build it yourself.

With sustainable development focused on real problems, pragmatic building strategies, and a vision for digital sovereignty, any nation can achieve AI independence. Don’t be discouraged if someone says you can’t compete with OpenAI or Anthropic. While they are currently reducing their model parameters, we are increasing ours. In the near future, we will converge in the middle. The first to reach that point could be the winner, but nevertheless, business applications using models under 30B parameters will capture 90 per cent of the whole AI market share.

The question isn’t whether to build homegrown AI, but whether your problems are painful enough to sustain the decades-long journey to solve them. For us, watching our youth lose their mother tongue to bad machine translation was painful enough.

But when a nomadic herder can speak to AI in their own language and get help accessing government services? When corruption drops because algorithms can’t be bribed? When does your culture live digitally for future generations? Egune AI is making it possible.

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Over the past two quarters, I’ve been teaching digital transformation in the era of 5G and AI, which is something new to me, but deeply rewarding. One of my first questions to every new class is simple: “What brought you here?”

Surprisingly, more than half the class often says they’re here because their SkillsFuture credits are expiring soon. They’re not chasing certificates or career pivots — they simply don’t want to waste the opportunity to learn something relevant in a fast-changing world.

Many of them are staff from SMEs, people who didn’t come in with big expectations but with an open mind. By the end of the course, they often walk away feeling genuinely proud — not just for learning new skills, but for discovering that they can.

It made me reflect on something remarkable about Singapore’s ecosystem. While we often talk about being a “Smart Nation” in terms of infrastructure and innovation, what’s truly smart is how the government has quietly built a learning mindset into the fabric of society. Every citizen has access to resources to up-skill, re-skill, or simply stay curious, and that creates a compounding effect across the workforce.

The ripple effect on startups and SMEs

When we think of innovation, the spotlight naturally falls on the usual suspects — the Y Combinators, the Antlers, the tech founders experimenting with Claude 4.5 for code generation, Meta’s AI glasses, or OpenAI’s agents. These are the pioneers pushing the frontier.

But real transformation happens when AI and digital literacy reach the everyday office worker — the operations executive, the logistics coordinator, the sales manager. The future isn’t just being built in accelerators or venture labs; it’s being sustained by people in SMEs who are now using digital tools, automating manual processes, and thinking differently about their work.

Technology only fulfils its potential when it becomes widely usable. No matter how advanced a model is, if only a few understand it, it remains an elite game. But when the broader population starts to experiment — even in small ways — that’s when innovation scales.

Also Read: Building the future: Up-skilling and empowerment in India’s real estate boom

Giving the “back row” a front-row seat

In every learning journey, there’s a simple truth: we don’t know what we don’t know. AI is evolving so fast that even tech professionals struggle to keep up. For non-tech professionals, programs like SkillsFuture create an entry point — giving them a shared vocabulary, a way to join the conversation instead of being left behind by it.

Owning an AI tool today is like owning a smartphone 15 years ago. You might not use every feature, but it changes how you live, work, and connect. The same applies to AI – it’s becoming the new baseline for digital fluency.

The dual movement of a smart nation

What I find admirable about Singapore’s approach is its two-speed innovation model: one that accelerates frontier technologies through startups and MNCs, and another that ensures the entire society moves along with it. The front-runners may be building the future, but the rest are being equipped to live and thrive in it.

That’s what makes the ecosystem resilient. Startups can scale faster when the broader workforce is digitally competent. SMEs can adopt innovation without fear. And individuals, regardless of age or industry, can adapt rather than resist change.

A shared momentum

Whether you’re at the front driving innovation, at the back learning to catch up, or somewhere in between enabling the system, we’re all part of the same movement.

The next wave of transformation won’t just be about smarter technologies; it’ll be about smarter people using them with confidence. And if there’s one thing Singapore’s story shows us, it’s that when everyone learns, the nation moves forward together.

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Today’s workforce is undergoing rapid transformation. As AI reshapes every industry, organisations and employees are discovering new ways of working, creating a need for different professional skills and knowledge. For employees, this has both opened opportunities and sparked anxiety.

Many are experiencing FOBO (Fear of Being Obsolete), with nearly half of professionals worrying their skills will be outdated within five years. At the same time, 94 per cent say they would stay longer at an organisation that invests in career development, showing that up-skilling opportunities are a top priority for professionals.

Yet, despite the necessity and demand for learning, skills gaps remain from digital fluency to problem-solving and adaptability. This work landscape is proving to be particularly challenging for Gen Z, who are newer to the workforce and must learn foundational professional skills at a time of rapid change. Older employees may also find this integration of new technology overwhelming and need support with digital skills.

The challenge for organisations is clear: provide employees with the learning support they need to prepare for the future of work. Edutech offers a pathway to achieving this goal by delivering scalable, engaging, and personalised learning opportunities tailored for modern employees.

Drive continuous up-skilling and adaptability with micro-learning

With AI accelerating the pace of change, organisations can no longer afford to only deliver employee training in all-day sessions once or twice per year. Instead, edutech tools enable managers to embed learning into the flow of everyday work with micro-learning. Mobile-friendly and bite-sized training formats ensure learning can happen anytime, anywhere, and are especially appealing to Gen Z as digital natives. These sessions are easier to fit into employees’ busy schedules without disrupting work routines, while also making learning a continuous process that can be quickly adapted according to changing needs.

Micro-learning can be designed to help employees build skills and knowledge step-by-step as they need it. This lets employees see the relevance of the training right away, which is a key factor in keeping learners engaged and helps employees avoid information overload.

Also Read: The future of edutech: Personalising learning for all

Edutech can also make it easier for employees to track their learning progress, filling knowledge gaps and developing new skills at their own pace. For employers, integrated reporting helps track participation across training sessions, identify skill gaps, and refine future learning strategies. With full visibility of their workforce’s strengths and weaknesses, and how they respond to the training in real time, trainers can continuously adapt their approach to be more efficient and impactful.

Add interactivity to make learning engaging and effective

Traditional training methods like long modules, static slide decks, and one-way seminars often fail to keep employees motivated. With edutech, trainers can design learning experiences that are interactive, using gamification, real-time feedback, and adaptive learning paths that make sessions memorable and effective.

In fact, research has shown that interactive learning lowers employee attrition rate by 37 per cent.

A new innovative approach to training doesn’t need to take a lot of extra time or effort, either. Organisations can use AI to transform existing training materials into interactive or even gamified experiences. AI-enhanced edutech can also make it easier to personalise learning, giving employees highly relevant training that’s suited to their needs and learning styles. With the right tools, even compliance training or technical refreshers can become experiences employees look forward to.

Encouraging collaboration and knowledge sharing

Beyond individual learning, an AI-ready workforce requires collaboration and collective problem-solving. Peer-to-peer learning and knowledge exchange sessions can be a powerful way to connect teams while promoting learning. However, many employees would hesitate to give a presentation to their colleagues even with valuable information, simply for fear of boring their coworkers.

Edutech platforms can help professionals turn these dry sessions into exciting and energising activities by using friendly competition or collaborative challenges. Session hosts can test their coworkers’ knowledge with gamified quiz questions, and use live polls, Q&As, and brainstorming to ensure everyone has a voice, even in hybrid or global teams. Employees can also use AI tools to create these peer learning sessions, helping them build AI skills at the same time.

Also Read: Edutech in SEA is ripe for acceleration. This is why they can help build a more inclusive society

Preparing today for tomorrow’s workforce

As AI transforms industries at a lightning-fast pace, the workforce must evolve just as quickly. Edutech can play a crucial role in this transformation by making learning engaging, accessible, and collaborative, and enabling organisations to deliver it at scale across their workforces.

Organisations that invest now in embedding edutech into their talent strategies will not only be better equipped to future-proof their workforce; they can also unlock new levels of productivity, retention, and innovation. Ultimately, the intersection of AI and edutech is about empowering people with the confidence, curiosity, and collaboration skills they need to thrive in the years ahead.

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In the creator and startup world, “community” has become a buzzword.

Everyone wants one. Creators launch Telegram groups. Founders open Slack channels. Professionals start networking circles.

But most communities don’t monetise. And it’s not because of low engagement. It’s because there is no economy running behind them.

At our recent “Community That Converts” session, this pattern became obvious. The room was filled with creators, early-stage founders, and corporate professionals trying to pivot. They didn’t lack ambition. They didn’t lack skill. Many of them already had audiences.

What they lacked was structure.

A group is not an ecosystem

There’s a misconception that if you gather enough people in one place, value will naturally circulate.

It doesn’t. A group is a container. An ecosystem is infrastructure.

An ecosystem has:

• Defined roles.
• Defined value propositions.
• Defined price points.
• Defined outcomes.
• Defined pathways for exchange.

Without these, what you have is a connection. Not commerce.

And connection alone is not sustainable.

Even charities need funding to operate. Even volunteer-driven movements require resources. In today’s economy, value is transacted through money. If no monetary exchange exists, sustainability becomes fragile.

The hard truth is this: If your community has no internal economy, it will eventually stall.

The “more content first” trap

One recurring belief we encountered was this: “I need more content first.” More posts. More reach. More followers. But content amplifies what already exists.

If the value proposition is unclear, more content amplifies confusion. If the offer is undefined, more visibility magnifies the gap. People cannot pay for what they do not understand.

And many community builders avoid pricing not because they are unsure of their audience, but because they are unsure of their own value.

Also Read: Customer churn analysis: How can startups get it right?

Monetisation is not hard selling — it is a measurement

Monetisation is often framed emotionally, as something uncomfortable or aggressive. But monetisation is simply an exchange of value transacted through money. Money measures clarity.

If no one is willing to pay, one of three things is usually happening:

• The outcome is vague.
• The positioning is weak.
• The offer is undefined.

You cannot expect payment without a price tag. You cannot expect sustainability without structure.

Consider this in professional terms. You do not pay an intern a manager’s salary. You do not pay a junior consultant a partner’s rate. Price is determined by positioning, experience, outcome, and brand equity.

The same applies to communities.

If members do not know:

• What they are offering,
• What problem do they solve?
• What outcome do they deliver?
• What they charge,

There can be no internal economy. And without economy, there is no conversion.

From individual hustle to layered ecosystems

A monetisable community is not about everyone paying one central figure. It is about enabling structured value exchange within the ecosystem.

Imagine a business-focused environment that includes:

• A strategist.
• A videographer.
• A photographer.
• A PR consultant.
• A lead generation specialist.
• A copywriter.

Each has a defined value proposition. Each has pricing. Each understands positioning.

When someone in the ecosystem needs support, they do not go outside. They transact within. That is when a community becomes infrastructure. That is when it converts. The platform itself becomes the enabler of value exchange.

Belonging is necessary, but directional

Belonging matters. But belonging without direction becomes noise.

Communities thrive when members share a similar outcome. An investment-focused group works because members aim for capital growth. A health-driven group works because members prioritise wellbeing. A business-focused ecosystem works because members want leverage, revenue, and growth.

The shared ambition defines the economy. Not just shared interests, shared direction.

Also Read: From bridge rounds to global awards: Startups across Asia keep building

Why most communities fail

Most communities fail because they are built emotionally, not structurally.

They prioritise:

• Inclusiveness without tiers
• Engagement without offers
• Networking without pricing
• Connection without defined outcomes

It feels good initially. But without an economic layer, energy dissipates. The most sustainable communities are both inclusive and exclusive. Inclusive in knowledge-sharing and access. Exclusive in-depth, commitment, and paid tiers.

Open the front door. Structured inner rooms. Free distribution. Paid progression.

That structure is what enables revenue, confidence, clarity, and leverage — not just for the founder, but for the members themselves.

The blueprint: What makes a community convert

A converting community requires five foundational elements:

• Clear value proposition: Members must know exactly what they offer and to whom.
• Defined outcomes: The community must rally around a specific ambition or transformation.
• Structured pricing: Offers must be priced clearly. No ambiguity. No hidden discomfort.
• Tiered access: Free access for exposure. Paid tiers for depth and accountability.
• Facilitated exchange: The platform actively enables members to transact within the ecosystem.

When these layers exist, monetisation is not forced. It becomes natural. Because value is visible.

The bigger shift

The creator economy is maturing. Visibility is abundant. Content is easy. AI compresses execution.

What differentiates sustainable founders now is not output. It is ownership. Ownership of:

• Audience channels.
• Pricing structures.
• Ecosystem design.
• Internal economies.

A large audience without structure is fragile. A smaller, well-architected ecosystem is durable.

A community that converts is not about building a room full of people. It is about building a marketplace of defined value.

And once value can be exchanged clearly, sustainably, and repeatedly, conversion is no longer accidental. It is engineered.

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