Choco Up, the Singapore- and Hong Kong-based alternative financing platform, has launched an accounts payable (AP) financing product aimed at small and medium-sized enterprises (SMEs) facing widening cash flow gaps between supplier payments and customer collections.

The product allows businesses to access up to approximately SGD2 million (~US$1.56 million) in credit for supplier payments. It sits alongside Choco Up’s accounts receivable (AR) financing product, which can advance up to 90 per cent of unpaid invoices, with funding limits of up to approximately US$3.9 million per business.

Also Read: Choco Up taps US$30M to tackle Asia’s SME funding squeeze

The company is positioning the combined offer as a supply-chain financing suite for SMEs that need to pay suppliers before they receive payment from customers. That is a familiar pressure point across Southeast Asia, where SMEs often operate with limited collateral, thin cash buffers and payment cycles that can stretch well beyond 60 days.

The cash-flow problem behind SME growth

For many SMEs, the challenge is not simply winning contracts. It is financing the execution of those contracts.

Businesses in manufacturing, logistics, marine and offshore, engineering, healthcare supplies, wholesale, B2B technology and professional services often need to buy inventory, pay subcontractors or mobilise teams before revenue is collected. Suppliers may demand payment within 30 days, while customers can take 60, 90 or even 120 days to settle invoices.

That mismatch can turn growth into a working-capital problem. A company may have signed orders and a credible revenue pipeline but still struggle to fund procurement, payroll or project delivery. Traditional bank financing does not always move quickly enough for these situations, especially for SMEs without substantial fixed assets or long credit histories.

Choco Up said delayed settlements have become more pronounced, citing slow payments rising year-on-year to 44.39 per cent in the fourth quarter of 2025. The figure underlines a broader reality: SMEs are increasingly being asked to absorb financing pressure across the supply chain.

“These businesses often have to commit significant upfront resources to procure materials, fulfil orders, or deliver projects, while receiving customer payments only months later,” said Percy Hung, CEO and founder of Choco Up. “They also frequently require access to sizeable amounts of working capital at short notice, which traditional financing channels may not always be able to provide quickly or predictably.”

Why this matters in Southeast Asia

The product launch comes as SME financing remains one of the largest unresolved gaps in the region’s financial system.

MSMEs account for about 97 per cent of enterprises in ASEAN and contribute a major share of employment across the region, according to ASEAN policy research. Yet access to credit remains uneven, particularly for smaller firms that lack collateral, audited financials or established banking relationships.

Also Read: Choco Up to invest up to US$5M in social startups developed by Dream Impact of Hong Kong

The Asian Development Bank has estimated the global trade finance gap at around US$2.5 trillion, with SMEs disproportionately affected. While that is a global figure, the implications are acute in Southeast Asia, where cross-border trade, fragmented supplier networks and extended payment terms are common features of business.

Singapore has a more developed financial infrastructure than many neighbouring markets, but SMEs still face pressure from rising costs, cautious lenders and slower customer payments. In markets such as Indonesia, Vietnam, the Philippines and Malaysia, the issue can be more severe because of fragmented credit data and less standardised invoicing practices.

This is where alternative lenders, embedded finance players and supply-chain finance platforms have tried to build a wedge. Instead of underwriting only against historical financial statements or hard collateral, they increasingly use transaction data, invoices, payment history, platform integrations and bank account flows to assess creditworthiness.

A crowded financing market

Choco Up is not entering an empty category. Across Southeast Asia, SME financing has attracted a wide range of fintech players, including Funding Societies, Validus, Capital C, Aspire and regional invoice-financing providers. Globally, supply-chain finance and receivables platforms such as C2FO, Taulia, Stenn and PrimeRevenue have built models around improving cash conversion for suppliers and buyers.

The competitive question for Choco Up is whether it can deliver speed and risk control at the same time. SME lending is attractive because the financing gap is large, but it is also difficult because default risk can rise quickly when economic conditions soften or when businesses use short-term financing to cover structural cash-flow weakness.

Choco Up said the new AP and enhanced AR financing products will use AI tools to streamline applications and underwriting. The company said its systems automate client document checks and flag potentially fraudulent submissions for human review. In theory, that should reduce manual processing time and improve credit assessment.

But AI does not remove credit risk. In SME finance, the quality of underlying data matters more than the sophistication of the model. Fraud detection, invoice verification, counterparty checks and repayment monitoring are likely to determine whether the product scales safely.

From growth capital to working capital

Choco Up has historically positioned itself around alternative financing for growth companies, offering non-dilutive capital to SMEs and digital businesses. The AP financing product shifts the emphasis more clearly towards working capital and supply-chain liquidity.

That is a pragmatic move. Equity funding has become harder to secure across Asia since the funding correction, and many SMEs do not fit venture capital’s return profile in any case. Debt and revenue-based financing providers have therefore sought to serve businesses that are growing but not necessarily venture-scale.

For SMEs, the appeal is straightforward: preserve cash, pay suppliers on time and continue fulfilling orders while waiting for customers to settle. For Choco Up, the opportunity lies in becoming part of a company’s operating finance stack rather than a one-off capital provider.

Also Read: Choco Up, Wonder Capital join forces to launch US$50M private credit funds for APAC SMEs

The next test will be execution. If Choco Up can underwrite quickly without loosening credit standards, its combined payables and receivables product could find demand among procurement-heavy SMEs in Singapore and beyond. If payment delays worsen, the market need will only grow.

The post Choco Up moves deeper into supply-chain finance as SMEs battle delayed payments appeared first on e27.

Momentum Works has released a new report on East Asia’s food delivery sector, arguing that the region is entering its biggest leadership shift in more than a decade as Delivery Hero’s acquisition-led expansion model comes under pressure from Asian operators with deeper operating playbooks.

The Singapore-headquartered venture outfit said in its “Food Delivery Platforms in East Asia 2026” report that Hong Kong, Taiwan, South Korea and Japan generated an estimated US$38.6 billion in food delivery platform gross merchandise value in 2025. South Korea accounted for US$28.3 billion, or about 73 per cent of the total. Japan, Taiwan and Hong Kong generated US$4.1 billion, US$3.6 billion and US$2.6 billion, respectively.

Also Read: How mobile marketing is powering the next phase of food delivery growth in Southeast Asia

The headline finding is not simply market size. Momentum Works argues that East Asia shows how food delivery penetration is shaped less by income, urban density or restaurant culture alone, and more by how aggressively operators build supply, manage subsidies, improve logistics density and integrate delivery into broader consumer ecosystems.

That matters for Southeast Asia because the region’s dominant delivery platforms — particularly Grab, GoTo’s Gojek, ShopeeFood and LINE MAN Wongnai — face similar questions around profitability, competitive intensity and regulatory scrutiny. Google, Temasek and Bain estimated Southeast Asia’s online transport and food segment at US$28 billion in gross merchandise value in 2023, making it one of the region’s largest internet economy verticals. But growth has increasingly shifted from land-grab spending to unit economics, cross-selling and ecosystem retention.

Delivery Hero’s Asia model hits limits

For years, Delivery Hero built one of the broadest delivery portfolios in Asia by acquiring local leaders and consolidating fragmented markets. That approach gave the German company meaningful positions in Hong Kong, Taiwan and South Korea, while it also operated in Japan before exiting the market.

Momentum Works argues that this model is now reaching an inflexion point. Foodpanda Taiwan is being sold to Grab, Baemin in South Korea is on the market, foodpanda has lost leadership in Hong Kong, and Delivery Hero has already pulled out of Japan.

The issue is not that acquisitions failed to create scale. In several markets, they did. The problem is that consolidation alone has proved insufficient against rivals that continue to invest in operational depth. These competitors are not merely buying share; they are shaping demand through pricing architecture, merchant density, rider efficiency, subscription programmes and adjacent services.

“People often assume food delivery success is determined by how developed a market is. East Asia shows that isn’t true,” said Jianggan Li, CEO of Momentum Works. “These four markets look remarkably similar on paper, yet their outcomes are completely different. Market readiness is only the precondition. But markets don’t grow by themselves; operators’ relentless push grows markets.”

Also Read: SEA’s food delivery wars heat up: Market hits US$19.3B as TikTok enters arena

That point is visible in the stark difference between Japan and South Korea. Both are wealthy, urbanised and have sophisticated foodservice sectors. Yet Momentum Works estimates food delivery penetration at around 3 per cent in Japan, compared with more than 20 per cent in South Korea.

Keeta’s Hong Kong lesson

Hong Kong offers the clearest example of how an aggressive entrant can change a market that once appeared settled.

Meituan’s Keeta entered Hong Kong in 2023 and focused on subsidised one-person meals, rapid merchant onboarding and network density. Within 29 months, according to Momentum Works, it became profitable and overtook foodpanda. The report says Keeta shifted the battleground from blanket subsidy spending to operational efficiency, a familiar pattern for Meituan, which endured years of intense competition in mainland China before expanding overseas.

The Hong Kong case is relevant to Southeast Asia because it shows that incumbent delivery positions can be vulnerable even in dense, high-income cities. Singapore, Bangkok, Jakarta and Ho Chi Minh City all have entrenched players, but the economics remain sensitive to fee structures, rider supply and restaurant participation. A well-capitalised entrant with a sharper single-market playbook can still unsettle the hierarchy.

Keeta’s expansion is also being watched because Meituan has become one of Asia’s most sophisticated local services platforms. Globally, its closest reference points are not only food delivery peers such as Uber Eats, DoorDash and Deliveroo, but also superapp ecosystems that use delivery to reinforce broader consumer frequency.

Taiwan gives Grab a test outside Southeast Asia

Taiwan may be the most important market in the report for Southeast Asian readers because of Grab’s planned acquisition of foodpanda Taiwan. Momentum Works describes Taiwan as a profitable but comfortable duopoly where food delivery penetration has been stuck around 10 per cent for years and growth slowed to 5.5 per cent as competitive pressure faded.

Taiwanese regulators blocked Delivery Hero’s earlier attempt to sell foodpanda Taiwan to Uber Eats, reflecting the antitrust concerns that now surround food delivery consolidation across Asia. Grab’s entry therefore raises a different question: whether a Southeast Asian operator can reignite growth in a mature North Asian market rather than simply inherit an existing platform.

Grab’s experience is relevant. In Southeast Asia, it has fought Gojek, ShopeeFood, Foodpanda and local challengers across markets with different labour rules, payment habits and restaurant structures. It has also pushed delivery towards profitability by bundling services with mobility, financial products, subscriptions and advertising.

Still, Taiwan will not be a simple replication of Singapore or Malaysia. Consumer expectations, merchant relationships and regulatory treatment of platform labour differ. Grab will need to prove that its regional operating muscle travels beyond its home geography.

Korea and Japan show two extremes

South Korea remains East Asia’s heavyweight. Its US$28.3 billion food delivery market was built on long-standing consumer habits rather than platform invention alone. Baemin, owned by Delivery Hero, remains the leader, but Coupang Eats has gained share by leveraging Coupang’s broader commerce, logistics and membership ecosystem.

That creates a strategic dilemma for any future owner of Baemin. The asset is large, but it competes against a company that can use grocery, e-commerce, payments and membership to subsidise frequency and deepen loyalty. The same ecosystem logic is increasingly visible in Southeast Asia, where Grab, GoTo and Sea Group all treat food delivery as part of a wider consumer stack.

Japan sits at the other end of the spectrum. Despite its density and wealth, food delivery penetration remains low. Convenience stores, affordable prepared meals and a deeply embedded solo-dining culture reduce the frictions that food delivery solves elsewhere. Coupang’s Rocket Now is testing whether affordable solo delivery can unlock demand, but Japan has repeatedly frustrated global and regional platforms.

Also Read: How mobile marketing is powering the next phase of food delivery growth in Southeast Asia

Momentum Works’s broader argument is that Asia’s next phase of food delivery competition will be led by operators shaped by difficult home markets, not by financial consolidators alone.

“Ownership changes the balance sheet. It doesn’t change the competitive dynamics,” Li said. “Whoever owns these assets will still have to compete against operators that have spent years learning how to win in highly competitive markets.”

For Southeast Asia, the message is direct. The food delivery market is no longer about who can buy the most assets or spend the most on discounts. The winners will be those that can build density, defend margins, manage regulators and turn delivery into part of a larger consumer ecosystem. East Asia is becoming the testing ground for that transition.

The post Food delivery’s old consolidation model is cracking in East Asia appeared first on e27.

There is a fond joke in Singapore’s startup circles: give us a bold idea, and we will hand it back with a business plan, a risk register, and a steering committee, all before anyone has shipped version one. It is told with affection, and like the best jokes, it carries a grain of truth. We are world-class at getting ready.

That is only half the story; the better half is what we choose to do next. Preparation is a genuine strength, not a flaw. The next leap is to pair it with the courage to begin. What our system has unfortunately not yet produced is enough world-class founders.

By every structural measure, Singapore should be minting breakout companies at speed. It ranks among the world’s top startup ecosystems. It is home to some of Asia’s finest universities. It has deep technical talent and generous public funding. The foundations are not the problem. The opportunity now is to build the culture that turns those foundations into bold, breakout companies, and that is exactly the work we have set out to do at NUS Enterprise.

The ingredients are already here

Let me be clear: Singapore is no startup backwater. It is one of the world’s wealthiest economies by GDP per capita, and Asia’s richest. It has a well-capitalised venture market with more than 500 active VC firms, one of the highest densities in Asia, alongside a fast-growing set of deep tech programmes. Our leading universities, including the National University of Singapore (NUS), Nanyang Technological University, and Singapore Management University, all run dedicated innovation and entrepreneurship platforms.

Singapore now ranks fourth globally in StartupBlink’s 2026 Global Startup Ecosystem Index, up from tenth in 2021, the fastest five-year climb of any top-ten ecosystem.

What Silicon Valley gets right

Silicon Valley has sat at the top of the global startup map for decades. Its rise was not an accident. It was built on students who think beyond the brief, a willingness to explore unproven ground, and faculty who mentor rather than merely grade.

Walk into a Stanford classroom, and you are not just absorbing theory. You are defining problems, building prototypes, defending decisions to real stakeholders, and being pushed by professors who back potential over credentials. Failure is not a red mark. It is part of the curriculum.

I experienced this firsthand. When I was first rejected from Stanford’s master’s programme, a senior professor advocated for my admission because he had seen my work and believed in me, not in what appeared on paper. That is the culture in a single decision: bet on the person, not the paperwork.

Also Read: Singapore, AI, and the rise of emotional outsourcing

In Silicon Valley, investors back founders through repeated rejection, and students ship before they feel ready, because the ecosystem rewards the attempt, not only the outcome. The results compound. Companies founded by Stanford alumni now number close to 40,000 and generate some US$2.7 trillion (SG$3.5 trillion) in annual revenue. That is not a programme. That is a culture compounding over generations.

Compare that with the reflex that still greets many unconventional ventures here: “We need to study this further.” This response delays momentum, dampens ambition, and quietly shelves the long-horizon, research-intensive ideas that tend to change the world.

The Munich model and why it matters

Silicon Valley is not the only reference point worth studying.

The Technical University of Munich, through UnternehmerTUM, has been ranked Europe’s leading startup hub by the Financial Times for three years running. Since 2002, it has supported more than 1,000 startups and currently helps spin out over 100 high-growth technology companies a year. In 2024 alone, its ventures raised more than €2 billion (SG$3 billion). Its alumni include Celonis, Germany’s first decacorn, alongside companies such as Personio, FlixMobility, and Isar Aerospace.

It built all of this not by imitating Silicon Valley, but by making entrepreneurship the third pillar of the university, alongside research and teaching: embedded in degrees, credit-bearing, and wired into a dense network of corporates, investors, and operators. Not a module, not an elective, not an optional enrichment activity.

The lesson is simple: you do not need Sand Hill Road to build great companies. You need a university that treats entrepreneurship as core to its mission and means it.

A different strategy at NUS Enterprise

This is the gap we have set out to close, and we are doing it through a deliberately different approach.

We start with immersion. The NUS Overseas Colleges programme places students inside high-growth startups around the world for up to a year. The results make the point we keep returning to: Our cohort based in Sweden has produced founders at close to Silicon Valley’s rate, clear evidence that entrepreneurial outcomes are not geography-dependent. They are culture-dependent.

We have paired that with capital built for deep tech. NUS Enterprise has launched a S$150 million Venture Capital Programme, the first of its kind by a university in Asia, alongside a co-investment framework of up to S$20 million. The partners we brought on, Granite Asia, 4BIO Capital, Playground Global, and Matter Venture Partners, were chosen for how they build and scale research-based companies, not simply for how they write cheques.

Also Read: Founders think they win on nerve. In Singapore, they win on foresight

And we have planted a flag abroad. NUS Enterprise has opened its first global outpost in Silicon Valley, at The Studio, Playground Global’s incubation facility. Our team there will connect Singapore’s innovation ecosystem to one of the world’s most demanding markets bi-directionally.

We are also moving into the frontier where deep tech now matters most. Building on a decade-long partnership with Munich, we are collaborating with TUM Venture Labs, with a focus on defence and dual-use technology. For the first time, Singapore will host the Singapore Defence Tech Hackathon, co-organised with the European Defence Tech Hub and TUM Venture Labs, extending a platform that builds defence startups in Europe to Singapore. Our reference point here is Israel: a nation of comparable size that turned deep technical talent and hard necessity into one of the world’s most productive venture engines. The lesson we take from it is not about any single sector. It is that a small country with serious talent and serious resolve can build globally significant companies, provided it backs its founders early, decisively and without flinching.

None of this sits at the edge of the system. It is a deliberate redesign of the core: embed entrepreneurship into the institution, back founders through uncertainty, and give Singapore’s best ideas a global runway from day one.

The real shift is what we measure

Singapore has a world-renowned education system, and that is precisely where the next opportunity lies. It has been optimised for certainty. Assessments reward correct answers over interesting questions. Students learn to reduce risk rather than manage it, and many enter the workforce trained to wait for complete information before they act.

Entrepreneurship sits at the other end of that spectrum. It is forged in uncertainty: talking to users before you are ready, shipping imperfect prototypes, and iterating fast rather than waiting for every answer. When institutions optimise only for certainty, they do not remove risk. They postpone the learning. And in a global race, postponed learning is the most expensive choice of all.

The evidence is clear. The Global Entrepreneurship Monitor’s 2023/24 report found that in 31 of 49 economies surveyed, experts rated entrepreneurial education at school as the weakest of 13 framework conditions. Singapore scores strongly on overall startup conditions, but the global pattern is unmistakable: the thinnest layer everywhere is experiential, mindset-building education. That is a gap we can lead in closing.

Also Read: Singapore’s AI opportunity is no longer about adoption, it’s about discipline

From capability to courage

The pattern is familiar. In its early days, Google was turned away by the major internet portals and passed over by several prominent venture investors. The search market looked crowded, the founders looked unproven, and the commercial case looked unclear. A number of those who passed later admitted they had underestimated both the technology and the team.

That story repeats across every generation of breakthrough companies. Early-stage innovation rarely fits a conventional evaluation framework. It looks uncertain because it is uncertain, and the ecosystems that back it anyway are the ones that win.

Singapore has built a well-oiled system for entrepreneurs to survive and thrive. What it needs next is the institutional courage to treat curiosity, resilience, and bold attempts as real measures of success, not footnotes to flawless execution.

The goal is not to clone Silicon Valley. It is to build a Singaporean model of entrepreneurship where discipline and daring coexist, where ideas move from classroom to market with confidence, and where we stop asking “what if it doesn’t work?” long enough to find out.

Entrepreneurial ecosystems are not built on perfect plans. They are built on imperfect experiments, repeated at speed.

Singapore has every ingredient. At NUS Enterprise, we have stopped studying the recipe and started cooking.

—

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of e27.

Join us on WhatsApp, Instagram, Facebook, X, and LinkedIn to stay connected.

The post Singapore already has the ingredients for world-class founders, now we need the culture to match appeared first on e27.

The Southeast Asia Health Innovation Hub (SEA HI Hub) has joined the SPARK GLOBAL network to launch SPARK Southeast Asia, a translational health innovation programme aimed at helping academic medical research move from laboratories into clinical and commercial use.

The announcement was made at the SEA Health Summit 2026 in Bangkok. The programme will work with researchers, clinicians, hospitals, pharmaceutical companies, investors, and government health agencies across the region.

Also Read: The most-funded healthtech startups in Southeast Asia: A decade in review

The launch gives SPARK GLOBAL its first affiliated translational health innovation programme in the region. SPARK GLOBAL grew out of the SPARK programme founded at Stanford University in 2006 by Dr Daria Mochly-Rosen, with the goal of helping academic discoveries cross the difficult gap between early research and patient-ready medical products.

SEA HI Hub, a non-profit platform, currently claims to reach more than 25 million patients through its partner network. It has set a target of reaching 100 million patients by 2028.

Filling Southeast Asia’s translation gap

The new programme is not a healthtech accelerator in the usual sense. Southeast Asia already has a long list of digital health startups tackling telemedicine, hospital software, insurance access, pharmacy delivery, and chronic disease management. Companies such as Halodoc in Indonesia, Doctor Anywhere in Singapore, Alodokter in Indonesia, and MyDoc in Singapore have focused largely on service delivery and access.

SPARK Southeast Asia is addressing a different problem: how to turn university and hospital research into drugs, diagnostics, devices, and clinical interventions that can survive regulatory, clinical, and commercial scrutiny.

That gap remains significant across the region. Southeast Asia has strong clinical demand, rising healthcare expenditure, large patient populations, and increasingly capable research institutions. But translational infrastructure remains uneven. Many academic projects fail before they reach validation, not necessarily because the science is weak, but because researchers lack access to development expertise, regulatory advice, intellectual property strategy, clinical trial design, and early commercial guidance.

“For years, a lot of promising research has stayed within academia, not because the science was not good, but because there was no clear path to turn it into solutions for patients,” said Dr Kid Parchariyanon, founder of SEA HI Hub and Co-Director of SPARK Southeast Asia. “Joining SPARK GLOBAL gives us that path.”

Under the partnership, SPARK Southeast Asia will operate under the SPARK GLOBAL framework. Researchers and clinicians will be able to access mentorship in drug development, diagnostics, and commercialisation, as well as global industry experts and volunteers connected to the SPARK network.

The programme also plans to support the region’s investigator-initiated trial community by linking clinical researchers with academic networks, regulatory guidance, and trial development support.

Why Southeast Asia matters

The timing is notable. Southeast Asia has a population of more than 680 million, with rapidly ageing societies in Thailand, Singapore, and Vietnam, and a growing burden of non-communicable diseases across the region. Diabetes, cardiovascular disease, cancer, and chronic respiratory illness are placing pressure on public health systems that were not designed for such demand.

Also Read: Profit with purpose: Bridging the digital divide in healthcare

World Bank data show that out-of-pocket healthcare spending remains high in several markets in this region, particularly in countries such as the Philippines, Cambodia, and Myanmar. Thailand, by contrast, has one of the region’s more developed universal health coverage systems, making it a logical base for a programme seeking to connect clinical demand, hospital networks, and public sector engagement.

The region also remains underrepresented in global clinical research compared with its population and disease burden. Singapore has built a stronger biomedical research base through institutions such as A*STAR, Duke-NUS Medical School, National University Health System, and SGInnovate-backed initiatives. Thailand has deep clinical capacity and strong medical tourism infrastructure. Indonesia and Vietnam offer scale but face regulatory and infrastructure constraints. Malaysia has tried to position itself as a clinical research hub through Clinical Research Malaysia.

The challenge is that these strengths are still fragmented. Unlike the US, where translational ecosystems benefit from dense clusters of universities, hospitals, venture investors, specialist lawyers, contract research organisations, and experienced biotech executives, Southeast Asia’s biomedical innovation landscape is spread across markets with different rules, reimbursement systems, languages, and institutional capacities.

That makes a regional network potentially useful, but also difficult to execute.

From mentorship to measurable outcomes

SPARK GLOBAL says its model combines education, mentorship, and financial support for selected translational research projects. Its network includes more than 40 academic institutions worldwide.

Mochly-Rosen said Southeast Asia has “strong clinical expertise, clear unmet medical needs, and a growing innovation ecosystem”, adding that the partnership fits SPARK GLOBAL’s original purpose of supporting translational scientists across borders.

The value of such a programme will depend on more than brand association with Stanford. Translational medicine is expensive, slow, and failure-prone. Drug development timelines can stretch beyond a decade. Diagnostics and medical devices may move faster, but still require clinical validation, regulatory approval, reimbursement strategy, and adoption by hospitals or physicians.

For SPARK Southeast Asia, early credibility will likely depend on the quality of projects it selects, the seniority of mentors it can attract, and whether it can help researchers make hard decisions about which ideas are commercially and clinically viable.

There is also a funding question. Southeast Asia’s venture capital market has cooled since the peak of 2021, with investors becoming more cautious about long development cycles and uncertain exit routes. Healthtech funding has continued, but much of it has gone into care delivery, insurance enablement, and enterprise health software rather than deep biotech or translational therapeutics.

That creates both a constraint and an opportunity. If SPARK Southeast Asia can de-risk academic projects before they reach investors, it may help expand the pool of investable healthcare science in the region. If it cannot connect research projects to capital, regulatory pathways, and industry partners, it risks becoming another well-intentioned platform with limited downstream impact.

A regional test case for health innovation

SEA HI Hub’s broader ambition is to build a connected health innovation ecosystem across Southeast Asia. The SPARK partnership adds a research translation layer to that agenda.

The immediate focus appears to be Thailand, where SEA HI Hub has been building its network. But the stated ambition is regional. That will require engagement beyond Bangkok, particularly with institutions in Singapore, Malaysia, Indonesia, Vietnam, and the Philippines.

Also Read: Solving multiple medtech problems with a single device powered by AI

The competitive context is also changing. Global pharmaceutical companies are looking for more diverse clinical trial populations. Regional hospitals are digitising. Governments are exploring healthcare sovereignty after the COVID-19 pandemic exposed supply chain vulnerabilities.

At the same time, AI-enabled drug discovery, decentralised trials, and precision diagnostics are creating new possibilities for countries that historically lacked large biotech clusters.

SPARK Southeast Asia sits at the intersection of these trends. Its task is practical rather than rhetorical: identify promising science, impose translational discipline, and help projects reach patients.

For Southeast Asia, that would be a meaningful shift. The region does not lack unmet medical needs or entrepreneurial energy. What it has lacked is a consistent bridge between academic discovery and clinical deployment. SPARK Southeast Asia is now attempting to build one.

The post Stanford-born SPARK enters SEA through health innovation hub partnership appeared first on e27.

Singapore’s enterprise AI adoption is moving faster than the data infrastructure required to support it, according to a new Confluent report that points to a widening gap between experimentation and production readiness.

The company’s “2026 Data Streaming Report” found that 78 per cent of the city-state’s IT leaders say a lack of real-time data infrastructure is stalling their ability to scale AI.

Also Read: AI is eating the world and startups are riding the infrastructure wave

The finding is notable because Singapore is among Southeast Asia’s most aggressive adopters of AI policy, enterprise digitisation, and data governance frameworks. Yet the survey suggests that the next phase of AI adoption may depend less on model access or boardroom appetite, and more on whether companies can modernise their underlying data systems.

Confluent, an IBM company, surveyed 4,625 IT leaders across 14 markets, including Singapore, Indonesia, Thailand, India, Japan, Australia, the US, Canada, the UK, Germany, France, Spain, Saudi Arabia, and the UAE. Respondents worked in companies with at least 500 employees and held roles ranging from C-suite executives to senior contributors and consultants.

The report was conducted with Freeform Dynamics and Radma Research.

The survey comes as companies across Southeast Asia are moving beyond generative AI pilots into more operational use cases, including customer support automation, fraud detection, logistics optimisation, financial risk analysis, and software development. Singapore, in particular, has positioned itself as a regional AI hub through initiatives such as the National AI Strategy 2.0 and its Model AI Governance Framework. But enterprise adoption remains uneven, especially among companies operating on legacy infrastructure or fragmented data estates.

From model hype to data constraints

According to Confluent, 75 per cent of Singapore organisations are already deploying or piloting agentic AI solutions. Agentic AI refers to systems that can take actions or complete multi-step tasks with limited human intervention, rather than simply generate text or images in response to prompts.

That shift raises the stakes for data reliability. Unlike standalone chatbots, agentic systems need access to timely, accurate, and contextual business data. If the data is stale, incomplete, poorly governed, or locked in silos, the risks move beyond inaccurate answers to faulty actions.

The report found that 78 per cent of Singapore IT leaders have encountered at least three challenges when scaling AI. The most common barriers include insufficient infrastructure for real-time data processing, cited by 78 per cent of respondents; fragmented data ownership, cited by 73 per cent; and insufficient skills in managing AI, also cited by 73 per cent.

These figures broadly reflect what many technology leaders in Southeast Asia are encountering as AI pilots collide with production realities. Large banks, telcos, retailers, and logistics operators in Singapore, Indonesia, Malaysia, Thailand, and Vietnam have accumulated years of customer, transaction, and operational data. But much of it sits across separate systems, cloud environments, on-premise databases, and departmental platforms.

That makes it difficult to feed AI applications with consistent and governed data streams. It also complicates compliance in a region where data protection rules vary significantly, from Singapore’s Personal Data Protection Act to Indonesia’s Personal Data Protection Law and Thailand’s PDPA.

Greg Taylor, Senior Vice President for APAC at Confluent, said Singapore’s AI momentum needs to be matched by stronger data foundations.

Also Read: How to capture AI’s gains without wrecking your company

“Businesses across Singapore are rapidly embracing AI, strengthening the country’s position as a global leader in AI governance. But as AI systems become more embedded in business processes, trust cannot come from regulation alone, especially given the different regulatory approaches across APAC,” he said.

Agentic AI exposes legacy weaknesses

The report suggests that agentic AI is where infrastructure weaknesses become most visible. About 95 per cent of Singapore IT leaders said they experience or expect struggles with data infrastructure and quality, while the same proportion pointed to legacy system integration. Another 93 per cent cited large language model reliability as a concern.

These constraints are already affecting projects. More than 73 per cent of Singapore respondents said agentic AI initiatives had stalled, with half saying projects had been completely abandoned. Across APAC, the figures were similar: 74 per cent reported stalled projects and 53 per cent said work had been abandoned.

The findings should be read with some caution. Confluent is a data streaming company, and the report naturally frames the problem through the lens of streaming infrastructure. Still, the broader diagnosis is consistent with enterprise technology trends in the region. AI adoption is increasingly constrained by the quality, latency, and governance of the data layer.

This is also why infrastructure vendors have been repositioning around AI. Confluent competes in a market that includes open-source Apache Kafka deployments, Redpanda, StreamNative, Aiven, and cloud-native services such as Amazon Kinesis, Google Cloud Pub/Sub, and Azure Event Hubs. Broader data infrastructure players, including Databricks and Snowflake, are also pushing AI-oriented data platforms as enterprises look to unify analytics, governance, and machine learning workloads.

In Southeast Asia, the competitive context is shaped by both cloud adoption and regulatory caution. Banks and insurers in Singapore and Malaysia, for example, face stricter requirements around data lineage, explainability, and outsourcing risk. Digital banks, e-commerce platforms, and ride-hailing companies need low-latency data flows to support fraud monitoring, personalisation, and real-time pricing. These use cases make batch processing increasingly inadequate.

Governance becomes part of AI infrastructure

Confluent’s report found that 86 per cent of Singapore IT leaders rate continuous and up-to-date business visibility as a top priority. The same proportion said effective data sovereignty management is important, while 82 per cent valued data provenance and tracking capabilities. Across APAC, those figures stood at 91 per cent, 90 per cent, and 86 per cent respectively.

That emphasis reflects a shift in how enterprises think about AI governance. Earlier debates focused heavily on model behaviour, bias, and regulatory compliance. Those issues remain important, but companies are increasingly recognising that governance must start upstream, at the point where data is created, moved, transformed, and accessed.

In the report, 90 per cent of Singapore respondents said data streaming platforms can help address governance, risk, and compliance issues in agentic AI by enforcing data access and usage policies upstream. Another 91 per cent said these platforms can improve large language model (LLM) reliability by ensuring data is more complete and current, while 92 per cent said they make data more trustworthy, contextualised, and discoverable.

Shaun Clowes, Chief Product Officer at Confluent, framed the issue as a data problem rather than an AI spending problem. “Most organisations do not have an AI investment problem, they have a data problem. AI systems depend on fresh, accurate and contextual information, but too many are still being built on fragmented data, batch processes, and infrastructure that was not designed for continuous intelligence,” he said.

Investment follows the infrastructure layer

The report found that 86 per cent of Singapore leaders rank data streaming as an investment priority, close to AI and machine learning solutions at 85 per cent and data management and governance at 90 per cent.

That pattern matters because technology budgets are beginning to move from experimentation into implementation. Enterprises that spent 2023 and 2024 testing generative AI tools are now asking whether those tools can be embedded into core operations. In Singapore and the wider region, the answer will depend on whether companies can connect AI systems to live operational data without compromising security, compliance, or reliability.

Also Read: Can your AI actually read your data?

For Confluent, the commercial implication is clear: AI adoption creates demand for the infrastructure that moves and governs data in real time. For enterprises, the message is more sobering. Access to advanced models is becoming commoditised. The harder work lies in cleaning up data ownership, modernising legacy systems, and building governance into the flow of information.

Singapore may remain ahead of much of Southeast Asia in AI policy and enterprise readiness. But the report suggests that even in the region’s most mature digital economy, AI scale is now running into the same unglamorous constraint that has slowed many technology transformations before it: the plumbing.

The post Agentic AI ambitions in Singapore run into legacy systems and data quality gaps appeared first on e27.

Qapita is an ESOP platform for startups through to listed companies, helping founders unlock the Power of Ownership for their stakeholders. Qapita’s focus aligns with a growing global trend: as startups stay private for longer, the complexity of managing cap tables, liquidity events, and investor reporting has created a surge in demand for various ESOP management tools. Powering over 2,400 clients globally, Qapita offers cap table, ESOP advisory, liquidity programmes, as well as valuation and financial reporting services tailored to meet the needs of both shareholders and employees.

Managing an ESOP within a Singapore-incorporated private company comes with a structural limitation that direct share issuance and traditional trusts don’t fully solve. Singapore limits private companies (Pte Ltd) to 50 shareholders, presenting a unique challenge for founders to manage this statutory restriction.

For a firm in Singapore, allowing employees (ex-employees and advisors) to exercise their options early may lead to additional admin, including but not limited to potentially crossing this 50-shareholder private company threshold sooner than expected. With many founders considering incorporating an entity or a holding company in Singapore, this signals a need for alternatives in share delivery solutions across the Southeast Asia region.

To address this, Qapita has recently launched ESOP SPV, a first-of-its-kind share delivery solution built specifically for Singapore-incorporated entities. This could be particularly useful for founders who have yet to set up their ESOP plan and want to incorporate an SPV from the start to ensure a clean cap table before future team expansion and fundraises.

Also Read: From perk to power: Rethinking ESOPs in the modern talent economy

A Special Purpose Vehicle (SPV) acts as an alternative share delivery method that consolidates shareholder names in a single entity. When employees exercise, they become shareholders of the SPV instead of the company directly, encouraging tangible employee ownership in a flexible yet compliant manner.

Here’s how Qapita’s ESOP SPV works

A Singapore Private Company (Pte Ltd) is set up to hold shares. Employees hold shares in the SPV proportionate to their allocation. Only the SPV appears on the cap table. Here are some of the key features of Qapita’s new and improved product:

• Clean cap table from day one: A single SPV entry is cleaner for investors than a list of employee names. Employees stay consolidated in a single SPV entity, which simplifies due diligence, cap table documentation, and future fundraising rounds.
• Flexibility on employee share exercises: Employees can exercise more regularly without the company crossing the 50-shareholder limit. This lets them act when it’s most tax-efficient — rather than waiting for a liquidity event. As employees become shareholders of the SPV instead of the company directly, encouraging share exercises can allow them to feel a sense of ownership.
• Perfect middle ground between direct share issuance and trusts: ESOP trusts require a licensed trustee, ongoing fees, and greater regulatory overhead. For a startup, an SPV delivers the same structural benefit at a fraction of the cost.

To sum up, ESOP SPVs are best suited for early-to-growth-stage Singapore-incorporated startups with up to 50 ESOP participants. As the SPV allows employees to exercise their options and participate as shareholders through a structured vehicle, this reduces administrative hassle, maintains a clean, investor-ready cap table, and results in potential tax-saving opportunities for employees.

Ultimately, the right ESOP structure depends on your goals, your team size, and how you want employees to engage with their equity. Qapita can help you figure out what works, including implementation, structural, and taxation considerations for your employees.

Discover how an ESOP SPV compounds future benefits, giving employees real ownership while keeping your cap table investor-ready, at a fraction of the cost of a trust. Whether you’re setting up a new ESOP plan or already have an existing programme, Qapita’s advisory team can help you evaluate whether an SPV is the right structure for your startup and set it up end-to-end.

Learn more here: https://www.qapita.com/sg/companies/equity-compensation-advisory/spv

—

Want updates like this delivered directly? Join our WhatsApp channel and stay in the loop.

The e27 team produced this article in partnership with Qapita.

We can share your story at e27 too! Engage the Southeast Asian tech ecosystem by bringing your story to the world. You can reach out to us here to get started.

Featured Image Credit: Qapita

The post Qapita launches ESOP SPV for Singapore-incorporated entities appeared first on e27.

The venture capital world is awash with AI hype. Every fund claims to back the next frontier. Few can point to companies that have crossed from demo to dollars in under a year. Antler, the global early-stage VC with a growing Asia footprint, is making that claim and backing it with numbers.

Jussi Salovaara, co-founder and Managing Partner for Asia, sat down to defend the firm’s thesis on agentic AI, its “One Asia” platform spanning Korea, Japan, and Southeast Asia, and its controversial bet on China-outbound founders. He also confronts the hard questions: enterprise trust, deeptech timelines, talent wars with Samsung and Hyundai, and what happens to these startups if the AI spending bubble pops.

Also Read: Why Antler is going all-in on Japan’s earliest-stage founders

The answers are sharper and more candid than most VCs offer.

Edited excerpts:

You’re describing a shift from AI copilots to autonomous systems. But most enterprise buyers are still struggling to trust AI with basic decisions. Aren’t you getting ahead of reality?

The question assumes AI autonomy is binary. It isn’t. Think of your best manager training a new employee. With the right guidance, that employee can make basic decisions and handle well-defined responsibilities. AI is at a similar stage. Most modern models already have the logical reasoning needed for many business tasks. The real challenge is designing the right context, guardrails, and scope.

That’s exactly what we look for at Antler. We’re not backing companies claiming artificial general intelligence. We’re backing founders who identify a narrowly defined problem, codify domain expertise into AI systems, and enable reliable decisions within a carefully crafted scope.

The results speak for themselves. IndustrialMind.ai, founded by three ex-Tesla Gigafactory executives, built AI that replaces up to 80 per cent of repetitive engineering work. AppSecAI automatically writes, validates, and delivers security patches in 30 minutes at one-hundredth of the cost of manual processes. CONPA secured six-digit contracted revenue within three months of launch. These are commercial outcomes, not experiments.

What exactly counts as “meaningful commercial traction”? Is that a paying customer, a signed pilot, or something else?

Meaningful traction means contracted revenue, live ARR, or a very large qualified pipeline with documented ROI. We do not count free pilots or letters of intent.

To give specific examples: ChainShift secured six-figure contracted revenue within 10 months. i10x reached seven-digit annualised revenue in eight months. This pace is significantly faster than historical benchmarks for early-stage software, which often took 18 to 24 months to reach similar milestones.

Korea, Japan, and Southeast Asia have very different startup cultures and enterprise buyer behaviours. How does Antler actually operate as a unified “One Asia” platform in practice?

The starting points are genuinely different. Japan and Korea offer unmatched industrial depth, robotics expertise, and corporate R&D budgets. Southeast Asia offers a massive, mobile-first digital economy and an agile scale-up environment. Chinese founders bring frontier AI research talent and an execution intensity forged in the world’s most competitive technology market. These are not interchangeable, and we do not pretend they are.

What the Antler platform provides is a common outcome opportunity: building a global company. The friction appears in localisation, regulatory compliance, and enterprise sales cycles. We mitigate that with experienced, on-the-ground partners across our 27 global locations.

Global VCs like a16z, Sequoia, and Lightspeed are all doubling down on agentic AI. What does Antler genuinely offer an AI founder in Asia that they can’t get from a brand-name fund?

Several of those funds have backed companies we first invested in at inception; they operate at a different stage and serve a different need. What we bring beyond capital is a network of local partners with boots on the ground across 27 locations, embedded in the ecosystems where founders are expanding.

The most concrete expression of this is our Embark programme, a four-week immersion that bridges our strongest Asian portfolio companies into Silicon Valley, connecting them with US enterprise customers, investors, and operators. Twelve startups across Asia have gone through three Embark cohorts. Every single one has secured US traction. We build the infrastructure and systematic support to get founders to the stage where global funds are ready to write the next cheque.

In a press release, you mentioned backing “China-outbound entrepreneurship.” Given geopolitical tensions and scrutiny in Western markets, how do you assess those risks?

China has spent two decades producing some of the world’s most technically rigorous engineers and AI researchers. A growing number of those founders are choosing to build for global markets from day one. That combination of frontier technical training and genuine global ambition is rare, and it is concentrated in this cohort right now.

Also Read: Analysis: SEA’s June funding spike masks a narrow recovery in VC funding

The question we assess at the investment stage is simple: where is your customer, where is your data, and where is your team? If the answers point towards global ambition from inception, the geopolitical risk profile is fundamentally different from a company that started in China and is now trying to expand outward.

Several portfolio companies are in sectors with notoriously long commercialisation timelines. How does Antler’s inception-stage model align with deeptech?

Deeptech companies with long timelines are precisely where early conviction creates the most asymmetric returns. We help founders compress the timeline from lab to first enterprise deployment, then hand them off to the right capital partners to carry the journey forward.

At inception, we look for technical validation, strong IP protection, and the first commercial signal — a paid pilot, a joint development agreement, or a signed letter of intent. Korea’s conglomerates and Japan’s industrial corporates are among the most sophisticated early adopters of deeptech in Asia, and we work closely with those networks to connect our founders with the right enterprise partners.

What happens to these companies if the enterprise AI spending correction some analysts are warning about actually materialises?

A spending correction would actually accelerate the path for the companies we back. A correction is, by definition, a correction in spending on broad horizontal platforms, experimental tooling, and marginal productivity gains. When budgets tighten, enterprise buyers do not cut tools that are reducing their costs or generating their revenue.

Our founders create business value through genuine domain expertise, not generalist AI. Verixus Labs CEO Joel Kosmin holds an Oxford PhD in Molecular Genetics, has over a decade of research experience, and worked at AstraZeneca before building an AI-powered operating system for biomanufacturing. His platform delivers 61 per cent higher mammalian stem cell yields and 66 per cent fewer experiments compared to standard approaches. That is not a product that gets cut when AI budgets tighten. A correction would validate it.

AI talent in Asia is fiercely competed for by Samsung, Hyundai, and SoftBank-backed companies. How are early-stage founders competing for engineers without matching corporate salaries?

Early-stage founders compete on ownership, autonomy, and the chance to build category-defining technology from scratch. The best engineers are often frustrated by bureaucracy and slow deployment cycles inside large conglomerates.

Also Read: Antler invests US$5.6M across 14 AI startups with early commercial traction

The founders in our portfolio are the very talent those conglomerates want to hire. IndustrialMind.ai was founded by executives who led Tesla’s manufacturing AI transformation. Infron was founded by ex-Alibaba AI researchers who left one of the most well-resourced AI environments in the world. They didn’t leave because they couldn’t get corporate salaries. They left for equity, creative control, and the chance to define a category. That’s the story they tell every engineer they recruit, and it’s credible precisely because they made the same choice themselves.

The post Why Antler is backing Chinese founders building away from China appeared first on e27.

The post The first mover myth: Why being first rarely means winning appeared first on e27.

Singapore-based travel rewards startup HeyMax has launched HeyMax First, a membership product that gives users access to miles before they have earned them, in a bid to reshape how frequent travellers think about redemption.

The product allows members to draw down up to one million Max Miles upfront and use them for flight or hotel redemptions through partner loyalty programmes. Members then earn the miles back over time through spending on the HeyMax app. The company said first-year membership fees will be waived for users who sign up during the launch period.

Also Read: What travel tech can look like for the travel industry’s revival

HeyMax said members must pay a reclaimable access fee to unlock the upfront miles. That fee is returned as users earn back the miles through future spending. The company said there is no deadline, penalty, or minimum activity requirement for members to complete the earn-back process.

The proposition is straightforward: instead of spending for years to accumulate enough points for a premium redemption, users can take the trip first and rebuild their balance later. The harder question is whether enough users will change their behaviour, and whether the model can be sustained without becoming a liability-heavy rewards scheme.

Reversing the loyalty sequence

Traditional airline loyalty programmes rely on a simple sequence: spend, earn, redeem. That structure gives airlines, banks and merchants years to manage liability, expiry, breakage and devaluation. HeyMax First reverses the order by moving redemption to the front of the customer journey.

“For so many years, loyalty programmes have asked travellers to do the same thing: spend first, wait years, and hope your miles are still worth something when you finally have enough,” said Joe Lu, CEO and co-founder of HeyMax. “HeyMax First reverses that. We front you the miles, you take the trip you’ve been putting off, and you earn them back on your own schedule.”

The product targets a clear consumer frustration. Premium award flights often require large mileage balances, and casual travellers may struggle to accumulate enough points before programmes change redemption rates or impose new restrictions. In Southeast Asia, where cross-border travel is frequent but incomes and credit card penetration vary widely by market, the ability to access miles earlier could appeal to younger professionals and aspirational leisure travellers.

HeyMax says its miles transfer on a one-to-one basis to more than 20 airline and hotel loyalty programmes, giving users access to over 70 airlines across major global alliances. The company did not disclose the full commercial terms behind HeyMax First, including how it prices the access fee, manages redemption risk, or accounts for miles advanced to members.

A crowded rewards battlefield

HeyMax was founded in 2023 by four former Meta engineers. The company raised US$11 million in Series A funding in January 2026, led by Peak XV Partners, and has since expanded beyond Singapore into Hong Kong. It plans to enter Japan, Taiwan and Australia by the end of 2026.

The startup operates in a market that sits at the intersection of travel, fintech, commerce and loyalty. In Southeast Asia, rewards have become a customer acquisition tool for banks, e-wallets, superapps, airlines and cashback platforms. GrabRewards, ShopBack, Kris+, AirAsia MOVE and Cathay’s Asia Miles all compete in adjacent ways for consumer attention and transaction volume.

Also Read: HeyMax acquires Hong Kong’s krip to supercharge Asia loyalty rewards expansion

Globally, companies such as Bilt Rewards in the US have shown that non-traditional spending categories can be converted into travel rewards at scale. Points-search and redemption platforms such as Point.me and AwardWallet have also built businesses around the complexity of airline loyalty. HeyMax is taking a different route: it is not merely helping users optimise existing points, but advancing future rewards against expected spending.

That distinction is crucial. Loyalty programmes are balance-sheet businesses as much as marketing tools. Miles have real cost, and redemption-heavy users can be expensive if they do not generate sufficient follow-on activity. HeyMax First will likely depend on three things: a broad merchant network, repeat spending behaviour, and careful control of who receives upfront miles and how much.

The company says users can earn Max Miles from more than 800 merchants globally. That merchant base gives HeyMax a starting point, but the model’s durability will depend on whether members concentrate more of their everyday spending inside the app after taking an upfront redemption.

Why Southeast Asia is a relevant testbed

Southeast Asia is a logical market for this type of experiment. The region’s digital economy has grown rapidly, with Google, Temasek and Bain estimating gross merchandise value at US$263 billion in 2024. Online travel has also rebounded sharply since the pandemic, with consumers increasingly comfortable booking flights, hotels and experiences through digital platforms.

At the same time, the region remains fragmented. Loyalty behaviour differs across Singapore, Indonesia, Thailand, Vietnam, Malaysia and the Philippines. Payment methods vary, airline networks are uneven, and regulatory approaches to consumer credit, stored value and rewards liabilities are not uniform. A rewards product that looks simple to the user may require careful structuring behind the scenes.

Singapore gives HeyMax a useful launch market. It has high card penetration, heavy outbound travel demand, and consumers who are familiar with airline miles and bank reward points. But regional expansion will not be automatic. In larger Southeast Asian markets, the company would face stronger localisation demands, lower average spending power, and competition from entrenched wallets and superapps.

The product also arrives at a time when airlines and banks are becoming more protective of loyalty economics. Frequent flyer programmes have become valuable assets, and carriers routinely adjust redemption charts, fuel surcharges and partner availability. If HeyMax positions itself as a flexible layer across multiple programmes, it may benefit from consumer frustration with single-airline schemes. But it will also remain exposed to changes imposed by those same partners.

The test ahead

HeyMax First is an ambitious attempt to repackage loyalty around immediacy rather than delayed gratification. The company is betting that access to premium travel today will motivate users to route future spending through its platform tomorrow.

That may resonate with travellers who dislike the uncertainty of waiting years to redeem points. It may also appeal to consumers who see travel as a priority but do not have enough miles or credit card spend to reach business-class thresholds quickly.

Also Read: HeyMax hits US$6M revenue milestone, eyes Asia Pacific expansion

Still, the product will need to prove that its earn-later structure is not just attractive at launch, but economically repeatable. Waiving first-year membership fees should reduce friction, but the key metric will be post-redemption engagement: whether members continue spending after they have taken the trip.

For now, HeyMax has put a sharp twist on a familiar category. In a region where travel demand is rising, rewards are becoming more competitive, and consumers are increasingly willing to try fintech-led alternatives, the company has chosen a high-risk, high-attention way to stand out.

The post HeyMax First offers upfront miles, but the economics will face a real-world test appeared first on e27.

Every AI conversation seems to begin with the same question: what can AI do better than humans?

It is an understandable question since AI can now analyse information quickly, summarise long reports, generate first drafts, support customer service, and automate tasks that used to take hours. For many companies, the appeal is immediate. If a tool can help a team work faster, reduce repetitive work, and make better use of existing resources, it is difficult to ignore.

But I think there is another question we should be asking more often, especially in Southeast Asia: Who actually gets to benefit from this shift?

The current AI conversation often assumes that everyone starts from the same place. It assumes that workers have time to experiment with tools, businesses have budgets for training, and communities have equal access to digital infrastructure. In reality, the gap between those who are ready for AI and those who are not is still very visible.

This is where the discussion about human value becomes more interesting. The issue is not simply whether AI will replace certain tasks. It is whether we are building an AI economy where more people can meaningfully participate.

Human value is changing, but it is not disappearing

Much of the anxiety surrounding AI comes from the belief that machines are replacing human value. I understand where that concern comes from, but I do not think it tells the full story.

For a long time, many professional skills were built around access to information. People were valued for how quickly they could research, organise knowledge, analyse trends, or turn information into a useful output. Those skills still matter, but AI has changed the baseline. A first draft, a summary, or a basic analysis is no longer as difficult to produce as it once was. That does not mean human value has disappeared. It means the source of value is moving.

In an AI-enabled workplace, the people who stand out are often not the ones who can simply produce the most output. They are the ones who can ask better questions, understand context, make sound judgments, and connect technology to real human needs.

Also Read: The accordion effect: How AI follows the rhythm of expansion and compression

AI can generate a list of ideas, but it cannot always know which idea is right for a specific market, community, or moment. It can analyse patterns, but it does not carry the lived experience needed to understand why people behave the way they do. It can help optimise a process, but humans still need to decide what kind of outcome is worth optimising for.

This is why I do not see the future of work as a simple story of humans versus machines. It is more likely to become a story of who can use machines with enough judgment, empathy, and responsibility.

The real divide is access, not interest

In Southeast Asia, interest in AI is not the problem. Many people and businesses are curious about it. However, the harder question is whether they have the same opportunity to learn, test, and apply it.

The World Economic Forum’s Future of Jobs 2025 coverage on Southeast Asia notes that digital skills are becoming more important for companies across the region, but many employers still see significant gaps. Upskilling and reskilling are becoming priorities because the pace of change is already affecting what businesses need from their teams.

This matches what many of us are seeing on the ground. Larger companies can invest in AI tools, internal training, consultants, and structured experimentation. Smaller companies often have to make do with limited time, limited budget, and limited guidance.

For workers, the difference can be just as stark. Someone in a major city with strong internet access, an English-language education, and exposure to global tools may find it easier to learn AI. While a frontline worker, informal worker, or small business owner in a less connected area may not have the same starting point.

The risk is that AI becomes another layer of advantage for people and organisations that already have access to capital, infrastructure, and education.

Southeast Asia needs inclusive AI growth, not just faster AI adoption

The region’s digital economy is still growing quickly. The e-Conomy SEA 2025 report says Southeast Asia’s digital economy has grown from US$40 billion in GMV a decade ago to more than US$300 billion in 2025.

Indonesia is a useful example of why inclusion matters in this conversation. MDI Ventures’ recent white paper, Catalysing Digital Resilience and Sustainable Growth: Advancing Inclusive Innovation and AI-Driven Impact Across Indonesia’s Digital Economy, notes that the country has around 65 million MSMEs, contributing 60.5 per cent to GDP and absorbing 96.5 per cent of the national workforce. It also points out that Indonesia’s digital economy is projected to reach between US$180 billion and US$340 billion by 2030, while many small businesses still face challenges in financing access, digital infrastructure, cybersecurity, and AI readiness.

Also Read: Singapore, AI, and the rise of emotional outsourcing

That context matters because Indonesia’s digital economy cannot be considered truly strong if its smaller businesses are left behind. Growth may happen at the top, but resilience depends on whether the broader business ecosystem can participate.

This is where AI should be seen as more than a productivity tool. If applied well, it can support better credit scoring, improve access to digital financial services, strengthen cybersecurity, and help small businesses operate with more confidence. But these benefits will not spread automatically. They need infrastructure, trust, relevant products, and patient ecosystem-building.

The MDI white paper makes this point indirectly through its focus on impact capital, digital trust, AI, cybersecurity, and inclusive digital infrastructure. Its portfolio examples, including Amartha, Qoala, Privy, and CYFIRMA, show how technology can support access, protection, identity, and trust within the wider digital economy.

We should also think about how people learn

There is another part of this shift that deserves more attention. As companies automate more entry-level tasks, we may accidentally weaken the pathways that help people build experience.

Many junior roles are built on tasks that are not glamorous but are deeply educational. Writing meeting notes, preparing research, drafting reports, checking details, and supporting senior colleagues are often how people learn how an industry works. These tasks teach judgment slowly. They expose people to context, mistakes, client expectations, and decision-making.

If AI takes over too much of that early work without a replacement learning path, companies may solve one efficiency problem while creating a future talent problem.

This is why the talent conversation should not stop at whether people know how to use AI tools. The deeper question is how quickly people can keep learning as the nature of work changes. LinkedIn estimates that 70 per cent of the skills used in most jobs will change by 2030, while PwC’s 2025 Global AI Jobs Barometer found that workers with AI skills command a 56 per cent wage premium. This suggests that AI is not simply reducing the value of human talent. It is raising the value of people who can keep adapting.

For organisations, the risk is that workers who already have access to training, tools, and experimentation time will move further ahead, while those without that access fall behind. This does not mean companies should avoid automation. It means they need to be more intentional about learning.

If AI handles the first draft, junior employees still need to learn how to evaluate that draft. If AI summarises research, people still need to learn how to question the source, spot missing context, and decide what matters. If AI supports execution, teams still need to teach accountability, communication, and ethical judgment.

AI can speed up work, but it should not remove the process through which people become thoughtful professionals.

Great talent now looks different

This also changes what we should look for in talent. A few years ago, the strongest candidate might have been the person with the most polished technical skills or the most impressive credentials. Those things still have value, but they are no longer enough on their own.

Also Read: AI slop is a strategy problem, not a content problem

In an AI-enabled environment, I would pay closer attention to curiosity, adaptability, clarity of thinking, and the ability to work with ambiguity. I would also look for people who know how to use AI without outsourcing their judgment to it.

That last part matters. There is a difference between someone who uses AI to think better and someone who uses AI to avoid thinking. The first person becomes more capable. The second person becomes more dependent.

This is why AI literacy should not be treated as a narrow technical skill. It is becoming part of how people communicate, analyse, make decisions, and build trust. The strongest professionals will be those who can combine technological fluency with human understanding.

The future of AI should be measured by who gets included

Many businesses are asking how AI can help them do more with fewer people. That is a practical question, and it will not disappear.

But I hope more leaders also ask a broader question: how can AI help more people contribute?

That question leads to a different set of priorities. It pushes organisations to invest in training beyond senior teams. It encourages businesses to think about frontline workers, small merchants, regional entrepreneurs, and communities that may not be first in line for new technology.

Southeast Asia’s future growth will depend not only on how quickly AI is adopted, but on how widely its benefits are shared. If smaller businesses, young workers, and underserved communities are left behind, the digital economy may become more advanced without becoming more resilient. That would be a loss for everyone.

In the end, the most important human contribution in an AI-powered world may not be competing with machines. It may be making sure the future we build with them still works for more humans.

—

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of e27.

Join us on WhatsApp, Instagram, Facebook, X, and LinkedIn to stay connected.

The post Human value in the AI era is not what most people think appeared first on e27.