Last week, Nevada regulators handed Tesla permits for up to 5,000 robotaxis in the Las Vegas area, with Waymo and Uber each cleared for another 1,000. That is roughly 7,000 permitted autonomous vehicles for a single US metro area, in a single announcement.

Meanwhile, in Punggol, Singapore, Southeast Asia’s most advanced public robotaxi trial, Grab and WeRide are running 11 vehicles along two fixed routes, free of charge, with commercial fares still pending.

Also Read: Grab makes strategic bet on WeRide to drive autonomous mobility in SEA

The contrast is stark enough to look like a failure of nerve. It isn’t. But it is a warning that Southeast Asia’s autonomous vehicle strategy needs to become a lot more deliberate before the gap becomes a gulf.

The scale gap is real, and it’s not just about money

Start with what Las Vegas actually signals. Nevada’s willingness to license fleets in the thousands, rather than tens, marks a shift from “pilot” to “infrastructure.” Tesla, Waymo and Uber are now treating a single city as a live commercial market, not a proof of concept. The US is betting that regulatory boldness, not just capital, is the scarce resource in the robotaxi race.

Southeast Asia has capital. Grab is Southeast Asia’s largest ride-hailing and delivery operator, and it has spent the past two years building exactly the kind of partnerships this moment calls for: an investment in Chinese autonomous driving firm WeRide and a separate tie-up with Michigan-based May Mobility aimed at adapting self-driving systems to the region’s roads. What the region has not had, until now, is a Nevada-style regulator willing to license fleets at four-digit scale.

That caution is not irrational. It is the product of genuinely harder conditions.

Why Southeast Asia moved slower and why that’s defensible

Singapore’s own roadmap targets only 100 to 150 self-driving vehicles by the end of 2026, a rounding error next to Las Vegas’s new permits. But Singapore’s roads, like most of the region’s, mix motorcycles, informal transport, unpredictable pedestrian crossings and left-hand traffic patterns that US autonomy stacks were never trained on. May Mobility’s own framing of the challenge is instructive: its CEO has said the plan is to bring the company’s autonomy system to the region as early as regulators allow, without committing to a specific market first. That is an admission that the technology, not just the paperwork, still needs local adaptation.

Also Read: Can autonomous delivery vehicles handle the chaos of real roads?

The caution is also informed by recent failures elsewhere. Robotaxi passengers have been left stranded for hours when a fleet’s software or connectivity failed, and a self-driving vehicle in China reportedly ended up in a construction pit. A regional operator scaling to thousands of vehicles before the technology has proven itself on SEA’s specific road conditions would be inviting exactly that kind of incident, at a much larger, more damaging scale.

So the 11-vehicle fleet in Punggol isn’t timidity. It’s a deliberate, government-coordinated test run, with Grab’s driver-partners retrained as safety and remote operators rather than displaced outright. That is a meaningfully different model from Nevada’s regulatory greenlight-and-scale approach, and arguably a more exportable one, for markets that cannot afford Las Vegas-style mistakes.

The leapfrog Southeast Asia can still make

Here is where the region has a genuine opening, rather than just an excuse. Grab is not simply importing American or Chinese autonomy technology; it is feeding its own mapping and routing data into May Mobility’s system specifically so the technology learns Southeast Asian traffic before it scales.

That is the leapfrog move: skip the “American roads first” assumption entirely, and build an autonomy stack whose first real-world competence is in the traffic conditions most of the world’s fast-growing cities actually have, not the wide, well-marked boulevards of Las Vegas.

If Southeast Asia gets this right, the region doesn’t just catch up to Nevada’s numbers eventually. It ends up holding the more commercially valuable asset: autonomous driving systems proven on the chaotic, mixed-mode traffic that characterises most of Asia, Africa and Latin America, rather than systems calibrated for wide American arterial roads. Nevada is optimising for scale in a forgiving environment. Singapore, if it moves deliberately, is optimising for robustness in an unforgiving one and robustness travels further.

What has to happen next

Three things need to move faster than they currently are.

First, regulators across the region, not just Singapore’s Steering Committee on Autonomous Vehicles, need clearer, published pathways from pilot to commercial fare, so operators can plan capital deployment instead of guessing at timelines.

Second, insurance and liability frameworks for mixed autonomous-human traffic need to exist before fleets scale past a few dozen vehicles, not after an incident forces the issue.

Third, the labour transition Grab has started — retraining driver-partners as safety and remote operators — needs to become an explicit regional policy commitment, not a single company’s goodwill gesture, given how many SEA livelihoods depend on ride-hailing and delivery work.

Also Read: Autonomy vs anarchy: How do we secure the future of autonomous transportation?

None of this means Southeast Asia should try to match Las Vegas vehicle-for-vehicle. It shouldn’t, and it can’t — not yet, and possibly not for years. But the region does need to stop treating its caution as a plan in itself. Caution bought Singapore a working 11-vehicle trial with real ridership data and a retrained workforce. It has not yet bought the region a credible answer to the question Nevada just asked out loud: what happens when robotaxis stop being a pilot and start being a market?

Southeast Asia has the ingredients — the superapp distribution, the local road data, the capital, the regulatory relationships — to answer that question on its own terms rather than importing someone else’s answer wholesale. What it doesn’t have yet is a timeline. Until it does, Las Vegas gets to write the scale story, and the region only gets to write the caveat.

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For much of the past decade, agritech in emerging markets carried a familiar venture capital promise: take a messy, offline industry, add software, and watch scale follow. A farmer advisory app here, a weather tool there, a digital marketplace somewhere else. The thesis was neat, asset-light and easy to pitch.

It also underestimated the reality of agriculture in markets where roads are patchy, cold chains are thin, trust is local, and farmers often need cash, transport and buyers long before they need another dashboard.

Also Read: Agritech’s next business model may not charge the farmer

That gap is now reshaping the sector, reveals the “AgTech Investment in Emerging Markets 2025” report released by AgBase, Briter, and Mercy Corps. Since the post-2023 funding slowdown, investors have become less willing to underwrite thin-margin growth stories that rely on rapid user acquisition but lack control over the physical value chain.

In Southeast Asia, where millions of smallholders remain central to food supply but operate across fragmented markets, the lesson is becoming harder to ignore: upstream agritech is moving from single-point apps to bundled platforms.

The new winners are not just digitising agriculture. They are building the missing rails around it.

The limits of the single-use farm app

The early agritech boom borrowed heavily from Western software-as-a-service models. Startups built products for agronomic advice, market price discovery, weather alerts, crop monitoring and farmer marketplaces.

In theory, these tools helped smallholders make better decisions. In practice, many ran into the same wall: farmers’ margins are too thin, incomes too seasonal, and pain points too physical for standalone software subscriptions to work at scale.

A farmer dealing with spoiled produce, no transport to market, rising fertiliser prices or a lack of working capital is unlikely to keep paying for an information-only product. Even when the product is useful, willingness to pay is limited. The economics become worse when a startup must spend heavily on field onboarding, farmer education and trust-building, only to earn a small subscription fee from a customer who may engage only during planting or harvest cycles.

This is the classic customer acquisition cost versus margin trap. High acquisition costs cannot be recovered from low-value, single-service relationships. The result has been a “pilot economy” across many emerging markets: promising tools tested with donors, development agencies or corporates, but unable to convert pilots into durable commercial models.

Southeast Asia has seen its own version of this. Digital farmer tools have often shown encouraging usage in controlled programmes, only to struggle once subsidies end. Indonesia’s post-boom correction in agritech was particularly telling. Models that expanded fast on the assumption that software-led scale would solve operational weakness found that food systems do not behave like consumer internet markets.

Why the bundle is becoming the business model

The emerging answer is not to abandon technology, but to place it inside a broader operating system. Modern agritech platforms increasingly bundle physical market access, input supply, financing, insurance, logistics, traceability and buyer relationships. This “phygital” model — part digital, part physical — is less elegant than pure software, but better matched to the market.

Also Read: Why Indonesia’s agritech winners will be phygital, not purely digital

The logic is straightforward. If a platform spends money to acquire and serve a farmer, it needs multiple ways to earn from that relationship. Selling quality seeds or fertiliser creates recurring engagement. Arranging transport and aggregation secures crop volume. Providing credit or pay-as-you-go equipment financing deepens loyalty. Connecting processors and buyers to verified supply opens downstream monetisation.

This shifts the platform from being a vendor to becoming infrastructure. It also changes who pays. Rather than charging farmers directly for every service, stronger models capture value from processors, exporters, retailers and food companies that need reliable sourcing, traceability and resilience. In a region where food manufacturers and agribusinesses face climate risk, volatile supply and tightening sustainability requirements, that downstream demand matters.

The bundle can also reduce churn. A farmer using one app for advice may leave easily. A farmer who buys inputs, receives seasonal credit, sells produce through the same network, and builds a repayment history inside the platform is far more likely to stay, provided the service delivers real income gains.

From coordination layer to infrastructure substitute

In mature markets, agritech platforms can often act as coordination layers. They plug into existing logistics providers, financial systems, farm data sets, insurance products and storage infrastructure. Their job is to optimise.

In much of Southeast Asia, the job is more basic: create what is missing.

That may mean building aggregation hubs, managing field agent networks, arranging transport, financing cold storage, verifying land or farmer identities, and collecting transaction data from scratch. These are not side activities. They are the operating foundation.

This is where the “winner-does-all” dynamic begins to emerge. The first platforms that can build dense networks of farmers, buyers, credit data and physical touchpoints gain advantages that are difficult to copy. Each transaction improves knowledge of farmer behaviour. Each buyer relationship strengthens demand visibility. Each repayment cycle improves credit scoring. Each aggregation node increases control over quality and volume.

The catch is that this model is capital-intensive and operationally unforgiving. It requires execution discipline closer to logistics, finance and supply chain management than to conventional software. It also means that “asset-light” is no longer always a virtue. In markets with weak infrastructure, refusing to touch assets can mean refusing to solve the real problem.

Fintech works best when it is hidden inside the stack

Agricultural finance remains one of the biggest opportunities in the sector, but standalone lending is rarely enough. Farmers need liquidity at specific moments: to buy inputs, rent machinery, pay labour or bridge the period before harvest income arrives. Lenders, meanwhile, struggle with limited credit histories, weather risk and repayment uncertainty.

Also Read: Agritech does not empower women farmers, until the system is fixed

Embedded fintech offers a more practical route. When credit is tied to inputs, equipment, insurance or guaranteed offtake, it becomes part of a controlled transaction loop. The platform can assess risk through purchase history, crop cycles, delivery records and buyer contracts. Repayment can be linked to harvest sales, reducing leakage.

This is why finance should be seen as the grease in the system, not the product itself. Pay-as-you-go models can help farmers access irrigation pumps, machinery or other productivity-enhancing assets. Working capital can increase transaction volume. Insurance can protect both farmer and lender. But the financial product works best when it sits inside a broader commercial relationship.

For Southeast Asian markets exposed to floods, droughts and price swings, that integration is becoming more important. Climate volatility makes lending riskier, but it also increases the value of platforms that can combine data, advisory, insurance and assured market access.

Capital has to match the terrain

The shift towards bundled agritech also demands a different funding playbook. Short-horizon venture capital can push companies towards rapid expansion before their operating systems are ready. That approach may suit software products with low marginal costs, but it can damage infrastructure-heavy models that need time to prove unit economics market by market.

A more realistic capital stack is layered. Development finance institutions and donors can help fund high-risk foundational infrastructure or provide first-loss capital. Corporate investors can bring offtake agreements, technical support and supply chain integration. Commercial equity is better suited once a platform has proven its economics and can scale without burning cash for every new district or province.

This matters in Southeast Asia because infrastructure gaps vary widely. A model that works in Vietnam’s coffee supply chains may not translate directly to Indonesia’s island geography or the Philippines’s fragmented logistics. Thailand’s more developed agribusiness networks present different opportunities from Cambodia or Laos. The capital and operating model must fit the local bottleneck.

The likely exit paths may also differ from the venture script. Some platforms may not head towards public markets. Strategic acquisition by agribusinesses, food processors, commodity traders, fintech groups or climate-focused supply chain companies may be more plausible.

The next phase of agritech

The death of the upstream single-point app does not mean digital agriculture has failed. It means the sector is becoming more honest about what digitisation requires.

In fragmented food systems, software alone rarely changes outcomes. It must be tied to trust, logistics, finance, buyers and physical presence. The companies that endure will be those willing to do the unglamorous work of building networks, collecting reliable data, managing field operations and solving several farmer problems at once.

Also Read: From Lagos to Jakarta: Why SEA agritech needs Africa’s “boots on the ground” playbook

For Southeast Asia, the stakes go beyond startup returns. Food security, rural incomes and climate resilience all depend on better-functioning agricultural markets. The next generation of agritech leaders will not win by owning the slickest app. They will win by owning, or at least orchestrating, the bundle that makes the whole system work.

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I observe that the digital asset sector’s total valuation has expanded to US$2.66T, up 0.98 per cent over the last 24 hours. This upward trajectory reflects a distinct shift in financial mechanics, in which regulated allocation dictates price action more than retail speculation. My analysis reveals an ecosystem that is heavily influenced by macroeconomic forces and traditional investment vehicles rather than by isolated technological breakthroughs.

The broader crypto landscape currently shares a 59 per cent correlation with the S&P 500 and a 67 per cent correlation with gold. These statistical relationships highlight how traditional financial narratives now dominate digital asset pricing models. Investors clearly treat these tokens as alternative stores of value and macro-sensitive instruments. This convergence is a permanent maturation of the asset class. The alignment with traditional equities and precious metals proves that large capital allocators view digital assets through the same risk-management lenses they apply to legacy markets.

Regulated exchange-traded funds continue to absorb massive amounts of underlying assets, driving the current bullish momentum. United States spot Bitcoin exchange-traded funds accumulated 4,038 Bitcoin tokens, representing US$316.54M in fresh capital, on August 26. Ethereum investment products simultaneously attracted 75,150 Ether tokens, totalling US$184.32M. This aggressive accumulation provides a robust foundation for price appreciation.

Fidelity clients have acted as net buyers for nine consecutive days, underscoring a persistent and deliberate allocation strategy by traditional finance giants. I view this consistent daily buying pressure as the primary engine sustaining the current rally. Retail traders often chase momentum, but institutional desks execute systematic accumulation strategies that anchor the price floor.

The continuous injection of massive amounts of daily capital through regulated channels completely alters supply dynamics. Participants must closely monitor the daily flow data because sustained inflows are absolutely necessary to maintain this upward trajectory. Wall Street desks now control the marginal pricing of these assets because their sheer volume overwhelms organic retail demand.

Also Read: Bitcoin touched US$81,000: Was that a rally or a forced repricing?

Bitcoin registered a modest 0.63 per cent increase to US$78,852.61, slightly underperforming the broader sector’s 1.1 per cent gain. This divergence stems directly from the macro-driven nature of the current rally. The leading cryptocurrency currently exhibits a strong 71 per cent correlation with gold over this specific period. Analysts attribute this synchronised movement to renewed focus on United States Treasury buybacks in long-dated bonds and ongoing currency debasement trades.

This price action is clear evidence that the premier digital asset currently functions primarily as a macro instrument. Traders react to shifts in global liquidity and currency expectations rather than internal ecosystem developments. The lack of a distinct coin-specific catalyst further supports this macro thesis. The modest price increase aligns perfectly with residual positioning flows rather than the start of a brand-new explosive trend. Observers must monitor changes in the 10-year Treasury yield and the DXY index, as these traditional metrics directly influence the direction of this trade.

Trading volume for the leading cryptocurrency fell by 36.9 per cent, indicating a lack of aggressive new buying from speculative participants. Positive regulatory developments also amplify the current uptrend and encourage broader participation. Social media platforms are buzzing with anticipation about the upcoming Senate vote on the CLARITY Act, which lawmakers have scheduled for September 15. This legislation promises to provide permanent regulatory clarity for the entire digital asset sector.

I believe the ecosystem aggressively prices in this reduced regulatory risk, which encourages traditional institutions to allocate capital without fear of sudden enforcement actions. This optimism is evident in the current Fear and Greed Index reading of 81, indicating extreme greed among participants.

While high sentiment readings validate the bullish trend, they also suggest the environment may be overextended in the short term. Traders often buy the rumour and sell the news, so this extreme greed warrants careful risk management. Participants should track the progress of the CLARITY Act and watch for any sudden shifts in sentiment metrics, as these elements will dictate near-term volatility.

Also Read: Bitcoin and Ethereum just flushed US$1.44B in shorts and the real test begins now

Technical indicators paint a clear picture of the immediate hurdles and support zones for both the total landscape and individual tokens. The overall digital asset direction in the coming week hinges entirely on the US$2.54T support level, which represents the 23.6 per cent Fibonacci retracement. If institutional inflows continue, the total capitalisation could easily test the recent high near US$2.66T again. A break below US$2.54T would signal a distinct shift in momentum and trigger a deeper pullback toward US$2.47T.

The market is currently in a holding pattern, testing whether recent gains can hold without an immediate catalyst. Maintaining structural integrity requires continuous capital injection to fend off profit-taking. I maintain that the structural integrity of this rally depends entirely on these daily capital injections. Without consistent buying, the ecosystem will likely succumb to profit-taking and revert to lower support zones. Algorithmic trading models place heavy weight on these specific Fibonacci levels when executing large block trades.

Bitcoin faces its own specific technical battleground as it consolidates between the Fibonacci support zone of US$78,290 to US$78,490 and resistance near US$79,340. The 61.8 per cent retracement level at US$78,290 provides a crucial floor for the leading cryptocurrency. The seven-day Relative Strength Index currently sits at 57.08, suggesting neutral momentum and leaving room for movement in either direction. A daily close above US$79,340 would signal a definitive breakout, while a break below US$78,290 would indicate a deeper pullback toward US$77,640.

Market participants eagerly await the next United States spot Bitcoin exchange-traded fund flow data, due on August 27, to gauge whether institutional demand can reignite bullish momentum. A seven-day streak of positive inflows sets a high bar for the upcoming reports. I firmly believe that disciplined observation of these specific data points will separate successful traders from those who suffer unnecessary losses during sudden corrections.

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Singapore’s artificial intelligence boom is beginning to show up in an unexpected place: the back office.

Rippling, the US$16.8-billion workforce management platform, is expanding its Singapore operations and moving into a new office at OCBC Centre East, as it nearly triples its local office-based workforce from August.

The US-headquartered company said the move reflects rising demand from Singapore businesses that are hiring across borders earlier in their growth journey, particularly as competition for engineering, data, product and AI talent tightens at home.

Also Read: The transformation ecology crisis: How AI is exposing the hidden fragility of high-performing teams

The expansion is not just about office space. It points to a broader shift in how startups and growth-stage companies in Southeast Asia are building teams. The old model — hire locally first, expand region by region, then stitch together payroll and HR systems as needed — is becoming harder to sustain. For many companies, the talent they need may be in India, Vietnam, the US, Europe or elsewhere in Asia Pacific, while their headquarters remain in Singapore.

That creates a practical problem. Hiring globally may help companies move faster, but it also adds layers of compliance, payroll, benefits, device management, security access and employee data across multiple jurisdictions. Rippling’s bet is that more companies will want those functions managed from one system rather than spread across disconnected tools.

Singapore’s growth story becomes a talent problem

The timing of Rippling’s expansion is closely tied to Singapore’s current economic cycle. The country has become one of Asia Pacific’s most important technology hubs, supported by AI investment, advanced manufacturing, semiconductor demand and its role as a regional headquarters base for multinational companies.

According to figures cited by Rippling, Singapore’s economy grew 5.7 per cent year on year in the second quarter of 2026. Manufacturing expanded 12.2 per cent, driven largely by AI-related demand for semiconductors and semiconductor manufacturing equipment.

That growth has sharpened an already tight labour market. Singapore had 73,300 job vacancies in March, equivalent to 146 vacancies for every 100 unemployed people, while unemployment stood at just 2 per cent in May. For startups and tech companies, the pressure is particularly acute in specialised roles such as AI engineering, data science, product management and cybersecurity.

This matters for Southeast Asia because Singapore often acts as a launchpad for regional companies with global ambitions. Founders may incorporate, raise capital and hire senior leadership in Singapore, but their commercial, technical and support teams can quickly spread across several markets. The more distributed the team becomes, the harder it is to maintain a consistent employee experience and operational control.

“Singapore’s AI boom is not only a technology story; it’s a talent story,” said Fiona Fergus, HR Business Partner, APAC at Rippling. “The country is producing global businesses and attracting significant investment, but that growth is intensifying competition for specialist skills that are already in short supply.”

The operational drag of global hiring

Rippling brings HR, payroll, IT and finance functions into one platform, giving companies a single source of workforce data. In practice, that means a business can onboard employees, manage payroll, assign devices, control software access and monitor workforce spending from the same system.

Also Read: AI won’t replace leaders, but it will expose weak leadership

This is where the company sees an opening in Singapore. As more startups expand into the US, Europe and Asia Pacific, they often accumulate a patchwork of local payroll providers, employer-of-record services, HR databases, IT systems and finance workflows. Each tool may solve one problem, but together they can make it harder for management teams to see who works where, what they cost, what systems they can access and whether the company is compliant.

Fergus said Singapore-headquartered companies are now building international teams earlier than before. “They want the flexibility to hire the best people wherever they are, while keeping workforce data, systems and operations connected,” she said.

The company is also positioning itself around AI governance, a newer concern for employers as staff begin using generative AI tools across daily workflows. Rippling’s AI Governance solution is designed to help companies control access to AI tools, track usage and spending, and manage AI agents in real time. For Singapore companies operating in regulated or security-conscious sectors, that oversight could become more important as AI moves from experimentation to everyday operations.

A Singapore startup case study

One local example is k-ID, a Singapore startup founded in 2023 that provides safety and compliance infrastructure for digital platforms serving children and teenagers. The company began with eight people and has since grown to more than 60 full-time employee and employer-of-record hires across 12 countries in Asia-Pacific, North America and Europe.

k-ID has used Rippling since 2024. For co-founder and Chief Safety and People Officer Jeff Wu, the issue was not simply managing headcount today, but avoiding a rebuild later.

“As we started hiring internationally, we needed infrastructure that could scale with us,” Wu said. “We wanted an HR system we could still be running at 100, 200 or even 500 people, without having to rebuild everything.”

He added that global hiring quickly exposes companies to different employment, payroll and benefits requirements. “When someone joins k‑ID, we want them to have the same employee experience no matter where they are in the world,” he said.

That consistency is becoming a bigger priority for venture-backed startups in the region. Distributed hiring gives young companies access to deeper talent pools, but it can also create uneven employee experiences if onboarding, benefits, equipment, security and HR support vary widely by country.

A crowded global workforce software market

Rippling is not alone in chasing this opportunity. The global workforce management market includes large incumbents such as Workday, ADP, SAP SuccessFactors and Oracle, which serve many enterprise customers. It also overlaps with newer global hiring and payroll companies such as Deel, Remote and Oyster, which have grown quickly by helping companies employ people across borders. For smaller businesses, platforms such as Gusto, HiBob and BambooHR compete around payroll, HR information systems and employee management.

Rippling’s pitch is that it combines HR, IT and finance in one data layer, but in Southeast Asia it will still need to win trust in a market where companies often mix global software with local payroll and compliance providers.

Its Singapore expansion suggests the company sees the region not merely as a sales outpost, but as a base for serving increasingly global Asian companies. Bringing previously remote employees together in a larger office could help Rippling work more closely with customers and partners across Asia-Pacific.

Also Read: The hidden problem inside AI teams isn’t skills — it’s the human environment

For Singapore’s startup ecosystem, the move also reflects a deeper reality: the next stage of growth will be less about whether companies can hire abroad, and more about whether they can manage those teams without slowing themselves down.

As AI investment accelerates and talent shortages persist, the companies that scale best may not be the ones with the largest offices, but those with the operational systems to make a borderless workforce feel coherent.

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Singapore’s fintech market entered 2026 with a familiar contradiction: its strategic appeal remains intact, but capital has become much harder to win.

Fintech companies in the city-state raised just over US$499 million across 53 deals in the first half of 2026, according to KPMG’s Pulse of Fintech H1 2026 report. That is a sharp fall from roughly US$1.45 billion across 97 deals in the same period last year and marks Singapore’s weakest first-half fintech investment performance in close to a decade.

Also Read: Southeast Asia solved distribution: Now fintech has to scale on the balance sheet

The headline number, however, masks a more uneven market. Funding was almost frozen in the first quarter, with about US$88 million raised across 26 deals. Activity then rebounded in the second quarter to around US$411 million across 27 deals, but the recovery was heavily dependent on one transaction: a US$320 million round for a cross-border payments platform in June.

That single deal accounted for close to two-thirds of all fintech investment into Singapore during the half. In other words, Singapore did not see a broad-based funding revival. It saw a market where investors were willing to write large cheques, but only for a small number of companies they considered mature enough, defensible enough, and central enough to the region’s financial infrastructure.

“The headline number tells only part of the story,” said Anton Ruddenklau, Partner and Head of Financial Services at KPMG in Singapore. “What we are seeing in Singapore mirrors the global market, where investors are being far more selective, consolidating capital behind a small number of scaled, high-conviction platforms rather than funding behaviour we saw in prior years.”

A funding market that rewards proof, not promise

The shift is stark when viewed against Singapore’s recent fintech cycle. In H1 2022, the country recorded US$3.54 billion in fintech investment across 234 deals, driven by abundant venture capital, pandemic-era digitisation, and investor enthusiasm for everything from digital banks to crypto infrastructure.

By H1 2026, deal volume had fallen to 53, less than a quarter of the level seen four years earlier. The value of investment was also below H1 2019, when Singapore fintechs raised US$610 million across 85 deals.

This does not mean Singapore has lost its fintech relevance. Rather, the market has moved from expansion to filtration. Investors are no longer rewarding growth stories by default. They are asking whether a company has revenue quality, regulatory resilience, enterprise demand, and a credible path to profitability.

That matters for Southeast Asia because Singapore remains the region’s main fintech capital formation hub. Many startups that serve Indonesia, Vietnam, the Philippines, Thailand, and Malaysia still use Singapore as a fundraising, regulatory, or headquarters base. A slower Singapore funding market therefore affects not only local startups, but also regional fintech companies that rely on the city-state to access institutional capital.

Payments still anchor Singapore’s fintech story

Payments remained one of Singapore’s most important fintech verticals in H1 2026, even though the numbers were unusually concentrated. The sector drew US$332 million across three deals, with the US$320 million June transaction accounting for nearly all of that value.

The continued interest in payments is not surprising. Southeast Asia is still a fragmented market when it comes to moving money. Businesses operating across the region often deal with multiple currencies, uneven banking rails, complex compliance rules, and slow settlement timelines. Cross-border payment platforms that can reduce friction in this environment sit close to real commercial demand.

For investors, the most attractive payment companies are no longer those promising consumer wallet adoption at any cost. The focus has shifted to infrastructure: platforms that help businesses move money, manage foreign exchange, comply with regulations, and plug into banking systems.

Also Read: What stands in the way of fintech growth in Asia?

This reflects a broader pattern across the region. As digital commerce, travel, remittances and B2B trade expand across borders, payment infrastructure becomes less of a standalone product and more of a core operating layer for companies. Singapore’s role as a regional treasury and financial services hub makes it a natural base for such platforms.

Crypto activity survives, but at earlier stages

Digital assets and cryptocurrency accounted for the largest share of deal activity in Singapore, with 27 deals in H1 2026. Yet the disclosed value was far smaller, at US$95.5 million, suggesting that most cheques were modest.

KPMG’s data shows that much of this activity was concentrated at seed and early stages, with 15 of the 27 digital asset and crypto deals falling into that category. The companies funded ranged from exchange and brokerage platforms to cross-chain tools and other digital asset infrastructure plays.

This is an important distinction. The crypto market that attracted speculative capital in 2021 and 2022 has largely disappeared. What remains in Singapore is more institutional and infrastructure-led. Startups are being built around regulated digital asset services, crypto payments, tokenisation, and tools that connect blockchain networks.

Singapore’s regulatory stance has helped shape this market. The Monetary Authority of Singapore has taken a tougher line on retail crypto speculation while continuing to support institutional use cases such as tokenised assets, stablecoin frameworks, and wholesale settlement experiments. That has made the city-state less hospitable to hype, but more credible for companies trying to build regulated financial infrastructure.

For Southeast Asian founders, this could be a double-edged sword. Singapore offers trust, talent, and regulatory clarity, but it also raises the bar. Early-stage crypto startups can still raise capital, but they need to show they are solving real infrastructure problems rather than chasing token-driven growth.

AI becomes part of the fintech stack

Artificial intelligence and machine learning featured in 18 of Singapore’s 53 fintech deals and accounted for US$365.9 million in disclosed value. Because deals are often tagged to more than one vertical, this overlaps with categories such as payments, crypto, and insurance.

The more interesting story is where AI is being applied. Later-stage deals clustered around software that embeds AI into existing financial workflows, including cross-border payments, investment research, insurance claims, credit-risk modelling, and document processing.

That says something about how fintech investors now view AI. They are not simply backing companies because they use the technology. They are looking for businesses where AI improves margins, automates manual processes, or strengthens an existing product.

At the seed and early stage, KPMG noted interest in agentic software and infrastructure. Agentic AI refers to systems that can carry out tasks with a degree of autonomy, rather than simply responding to prompts. In finance, that could eventually reshape how transactions are executed, how compliance checks are run, and how investment or credit decisions are supported.

The opportunity is significant, but so are the risks. Financial services is a heavily regulated industry where errors can have serious consequences. In Southeast Asia, where regulatory regimes differ widely from one market to another, AI fintechs will need to prove not only technical performance, but also explainability, governance, and compliance.

Singapore follows a global concentration trend

Singapore’s slowdown came as global fintech investment moved in the opposite direction by value. Worldwide fintech investment across venture capital, private equity, and M&A rose from US$72.2 billion in H2 2025 to US$103.1 billion in H1 2026, putting the sector on track for its strongest annual performance in four years.

But here too, deal volume weakened. Global fintech deal count fell from 2,500 in H2 2025 to 2,100 in H1 2026. The Americas dominated activity, attracting US$86.9 billion across 1,120 deals, with the US alone accounting for US$80.8 billion across 933 deals. By contrast, fintech investment in Asia-Pacific remained muted, declining from US$7.1 billion across 426 deals in H2 2025 to US$4.6 billion across 350 deals in H1 2026.

Also Read: Southeast Asia’s fintech apps don’t have a literacy problem, they have a fear problem​

The message is clear: fintech capital has not disappeared, but it has become more selective. Large transactions, especially in payments and AI-enabled fintech, are pulling up global totals, while smaller startups face a more difficult fundraising environment.

For Singapore, this may not be entirely negative. A leaner market can force stronger business discipline and reduce capital flowing into weak models. But it also means fewer young companies will get the chance to experiment, particularly in sectors where regulatory approval, infrastructure development, and regional expansion require patience.

The city-state’s fintech ecosystem is still built on durable advantages: a trusted regulator, deep links to regional markets, strong financial institutions, and a concentration of venture and corporate capital. What has changed is the cost of convincing investors.

In 2026, being based in Singapore is no longer enough. Fintech startups must show they can solve real cross-border problems, operate within tighter compliance expectations, and build businesses that survive beyond the next funding cycle.

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For much of the last decade, agritech startups in emerging markets were sold on a seductive idea: millions of smallholder farmers, armed with smartphones, would pay for software that helped them farm better. Investors liked the story because it sounded scalable. Build once, distribute widely, grow user numbers fast.

The problem was that the model rarely matched life on the ground.

Across emerging markets, including Southeast Asia, smallholder farmers may need better information, but they are often juggling more urgent constraints: access to affordable inputs, reliable buyers, working capital, weather shocks and unstable prices. A standalone app asking them to pay for advice was rarely competing with another app. It was competing with fertiliser, labour, transport, school fees and debt repayments.

Also Read: Why Indonesia’s agritech winners will be phygital, not purely digital

That mismatch has become harder to ignore since the global funding correction that began in 2022, according to the “AgTech Investment in Emerging Markets 2025” report prepared by AgBase, Briter, and Mercy Corps. As venture capital became scarcer, agritech companies could no longer rely on user registrations or app downloads as proof of progress. Investors started asking a more basic question: who is actually paying, and why?

The answer increasingly points downstream.

Rather than charging farmers directly, a new generation of agritech models is shifting monetisation towards buyers, processors, retailers, exporters and agribusiness corporates. These companies have stronger balance sheets and clearer incentives to pay for tools that improve traceability, climate resilience, supply visibility and compliance. In other words, the farmer remains central to the system, but no longer has to carry the full cost of digitisation.

The limits of farmer-paid software

The old “agri-SaaS” model borrowed too heavily from Western enterprise software. It assumed that smallholders would behave like corporate clients: subscribe, log in regularly, use dashboards and renew. But agriculture in emerging markets is not a neatly digitised office environment. It is fragmented, seasonal, trust-based and physically demanding.

There are an estimated 500 million smallholder farmers across emerging markets. Many operate on thin margins and face risks they cannot control, from droughts and floods to volatile commodity prices. In such a setting, software that addresses only one part of the value chain struggles to become indispensable.

For agritech platforms, the lesson has been blunt. Digital tools need to be bundled with tangible services: input supply, credit, insurance, market access, logistics or guaranteed offtake. Without solving these practical pain points, even useful apps can fail to generate recurring usage, let alone subscription revenue.

This is especially true in Southeast Asia, where agricultural supply chains can be highly localised. A rice farmer in Vietnam, a chilli grower in Indonesia and a durian producer in Malaysia may all benefit from better data, but their routes to market, financing options and buyer relationships differ sharply. A single digital product rarely fits all.

From venture bets to system bets

The funding environment has accelerated this shift. During the pre-2022 liquidity boom, many agritech startups were rewarded for reach. Growth decks highlighted registered farmers, hectares covered or villages reached. Those metrics were not meaningless, but they often obscured weak retention, low willingness to pay and expensive field operations.

Also Read: Agritech does not empower women farmers, until the system is fixed

By 2025, the bar has moved. Investors are looking for active usage, stronger unit economics and clearer paths to profitability. They are also more aware that agritech in emerging markets often requires mixed forms of capital. Concessional funding, donor money, commercial equity and corporate partnerships may all be needed to build infrastructure around farmers before a business becomes scalable.

This is a more disciplined phase for the sector. It also means founders must understand what some analysts call the “investable frontier”: the point at which a market’s infrastructure, regulation, logistics and buyer maturity make certain business models viable.

In a more developed agricultural export market, a startup may be able to build a relatively asset-light coordination layer on top of existing logistics and buyer networks. In a less mature market, the same company may need to build warehouses, aggregation centres, transport routes or agent networks before its software has any commercial value.

That difference matters. It explains why copying a model from one region to another often fails. Southeast Asia’s agritech opportunity is not the same as Africa’s, India’s or Latin America’s. Even within the region, Thailand’s export-oriented agriculture, Indonesia’s archipelagic logistics and the Philippines’ fragmented farming base require different operating models.

Why corporates are becoming the payer

Downstream monetisation works because it follows the money. Large agribusinesses, food manufacturers and retailers face growing pressure to know where their products come from, how they are produced and whether supply can withstand climate disruption.

Traceability is no longer a nice-to-have. Export markets are tightening rules on deforestation, labour standards, carbon reporting and food safety. Buyers need better farm-level data to comply with those standards. They also need visibility to protect their own margins when floods, droughts or disease threaten supply.

That creates an opening for agritech startups. Instead of selling generic advice to farmers, they can sell verified data and operational tools to corporates: supply chain transparency, water-efficiency monitoring, carbon measurement, sustainability reporting and quality assurance.

In Southeast Asia, this is particularly relevant for commodities tied to global supply chains, including palm oil, coffee, cocoa, rice, seafood, fruit and rubber. Export-oriented buyers need evidence that production meets increasingly strict standards. Startups that can gather, verify and translate farm-level information into compliance-ready data may find more reliable revenue from buyers than from farmers.

The commercial logic is simple. A farmer may not pay for a traceability dashboard. A multinational buyer facing regulatory risk, reputational damage or supply disruption might.

The return of physical operations

The shift downstream does not mean agritech can become purely digital. If anything, it reinforces the need for “phygital” models: digital systems supported by physical operations and human relationships.

Also Read: From Lagos to Jakarta: Why SEA agritech needs Africa’s “boots on the ground” playbook

Agriculture still depends on trust. Farmers need to know who is buying, when payment will arrive, whether inputs are genuine and whether advice is credible. Buyers need confidence that produce quality, volumes and sustainability claims are real. That cannot be solved by code alone.

The most durable models often combine software with field agents, collection points, logistics partners, financing channels or buyer aggregation facilities. In Southeast Asia, startups may be able to use infrastructure already built by cooperatives, distributors, government agencies or large corporates. That allows for more asset-light coordination than in markets where startups must build the “hard rails” themselves.

Digital public infrastructure can also help. Land registries, digital identity systems, e-wallets and government farm databases can reduce the cost of farmer verification, credit scoring and payments. But access to these rails varies widely across the region, which again makes local market design critical.

Impact as unit economics

The new agritech discipline also changes how impact is understood. It is no longer a separate slide at the end of a pitch deck. In smallholder markets, impact often determines whether the business works at all.

If a platform does not improve farmer income, reduce risk or open access to better markets, farmers churn. If a financing product does not bundle insurance, agronomic support or guaranteed offtake, repayment risk rises. The source material suggests that farmer income gains of 20 per cent to 30 per cent may be needed to materially lower churn and build long-term loyalty. Agri-finance models that combine insurance or guaranteed offtake can maintain repayment rates above 95 per cent.

These figures point to a bigger truth: farmer prosperity and startup sustainability are linked. Extractive models fail because they weaken the very supply base they depend on. Stronger models make farmers more productive and less risky, which in turn makes the platform more valuable to lenders, insurers and buyers.

The climate transition as business model

Climate change is likely to make downstream monetisation even more important. Food companies need to secure supply in a world of rising heat, water stress and extreme weather. Governments and regulators are demanding more transparent reporting. Investors are pushing companies to show credible sustainability progress.

Agritech startups that can help corporates measure emissions, manage water use, verify regenerative practices or protect yields will be better positioned than those selling narrow farm-management apps. Biological inputs, satellite monitoring, soil data, carbon accounting and AI-based advisory tools may all have a role, but only if they connect to a paying customer with a real commercial problem.

Also Read: The future of farming in the Asia Pacific is here to empower farmers

The era of vanity metrics is ending. Agritech’s next phase will be judged less by how many farmers download an app and more by whether the company can build a working system around them.

For Southeast Asia, that may be good news. The region’s agricultural sector is fragmented, but it is also deeply connected to global food, commodity and export markets. Startups that can bridge smallholder production with corporate demand for transparency, resilience and sustainability may finally find a path to durable revenue.

The lesson is not that farmers do not matter. It is that charging them directly for software was often the wrong place to start. The future of agritech profitability may depend on helping farmers create more value, while asking those who capture larger margins downstream to pay for the tools that make the system work.

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For years, digital wealth platforms in Southeast Asia have focused on helping users do one thing better: invest. They lowered account minimums, simplified portfolios, and made cash management and ETFs available through an app. StashAway now wants to move into a less glamorous but arguably more consequential part of the wealth journey: what happens to that money when its owner dies.

The Singapore-headquartered digital investment platform has acquired MakeGoodwill, a local digital wills platform that lets Singapore residents create a will online in about an hour. The terms of the deal were not disclosed. MakeGoodwill will continue to operate as a standalone brand.

Also Read: Digital wealth platforms hit scale in SEA as foreign investing apps outgrow local rivals

The acquisition marks StashAway’s first formal move beyond wealth accumulation into legacy planning. Since its launch in 2017, the company has built its business around cash management, managed portfolios, do-it-yourself ETF investing and alternative investments, including private markets. It now operates in Singapore, Malaysia, Hong Kong, the UAE and Thailand, and says it manages billions of dollars in assets.

The move comes as consumer fintechs face a more mature market. Robo-advisory and digital investing are no longer as novel as they were five years ago and platforms are looking for ways to deepen relationships with clients beyond portfolio performance. Estate planning, while less headline-grabbing than private credit or AI-driven investing, is one of the clearest adjacent needs.

“Our clients spend years building wealth for a better future, often with their families in mind. Yet many never plan how to protect that wealth and pass it on,” said Michele Ferrario, co-founder and CEO of StashAway. “Bringing MakeGoodwill into StashAway means we can support clients through some of their most important financial decisions, from investing to planning their legacy.”

The will gap

The numbers explain why StashAway is interested. According to a YouGov study cited by the company, only 22 per cent of Singaporeans have a legally drafted will. StashAway’s own survey of 125 clients, conducted in March 2026, found a similar gap among people already building wealth: three in four had no will. Among those who did, more than 40 per cent said their will was out of date.

The survey is small and limited to StashAway clients, but the findings reflect a broader behavioural problem. People know estate planning matters, but they delay it because it feels uncomfortable, complicated or expensive. More than eight in 10 respondents cited barriers such as procrastination, lack of time or uncertainty over what a will should include. At the same time, nine in 10 said they would create a will within three months if the process were simpler.

That gap between intention and action is exactly where digital platforms tend to position themselves. MakeGoodwill uses guided questions in plain language to help users generate a will based on a template developed by Singapore lawyers. Users then need to print and sign the document in the presence of two independent witnesses for it to be legally valid.

The platform has helped create more than 1,100 wills since launch. It is not a law firm and does not provide legal advice, a distinction that matters in estate planning. Its documents are designed to comply with Singapore’s Wills Act 1838, Probate and Administration Act 1934 and relevant case law, but people with complex family structures, cross-border assets, business holdings or disputes may still need legal counsel.

Lowering the cost of basic planning

MakeGoodwill charges S$179 (~US$132) to create a will. The company says traditional law firms typically charge between SGD500 and SGD1,500 for similar services. The platform includes client support at no extra cost, with questions answered within 24 hours on working days.

Each will comes with one year of unlimited edits, secure lifetime access to completed documents, and a 30-day money-back guarantee. After the first year, users can pay SGD35 annually to keep editing their will as their family, assets or circumstances change. Couples can add a second will for SGD89.50.

Also Read: ‘Resistance to digital wealth management has almost disappeared in SEA’: Bambu CEO Ned Phillips

That ability to update documents may prove important. A will is not a one-off administrative chore. It can become outdated after marriage, divorce, the birth of children, the purchase of property, changes in beneficiaries or changes in financial assets. The rise of digital investing has also made estates more fragmented, with people holding cash accounts, ETFs, crypto, private market exposure and overseas investments across multiple platforms.

“The best products cut through complexity and make things simple enough to act on,” said Priya Surya, founder of Goodwill, now MakeGoodwill. “We started Goodwill so anyone could create a legally valid estate plan in minutes instead of putting it off for years.”

For StashAway, the acquisition adds a practical layer to its brand promise. Wealth platforms often talk about long-term goals, retirement and family security. A will brings that conversation into sharper focus because it asks clients to specify who receives their assets, rather than leaving the matter to intestacy rules.

A Southeast Asian context

Singapore is a logical starting point for this kind of product. It has high household wealth, rising digital finance adoption and a relatively clear legal framework for wills. It also has a large population of globally mobile professionals who may own assets across jurisdictions, though MakeGoodwill’s current product is designed around Singapore law.

Across Southeast Asia, the legacy-planning gap is likely even wider. In many markets, families still depend on informal arrangements, verbal wishes or assumptions about inheritance. That can create disputes, delays and financial stress when someone dies. The issue becomes more complicated as middle-class households accumulate more financial assets, property and insurance, often across multiple providers.

Digital wills will not solve every estate-planning problem. Inheritance law, religious law, tax considerations and cross-border assets can be complex. Muslim inheritance, for example, may require different planning considerations in markets such as Malaysia and Indonesia. But for straightforward cases, a low-cost digital tool could help more people take a first step rather than avoid the topic entirely.

Rivals and the broader wealth race

StashAway’s closest regional rivals include Endowus and Syfe in Singapore’s digital wealth market, as well as other investment platforms and private banking alternatives competing for affluent retail and mass affluent users. Endowus has leaned heavily into access to funds, CPF and SRS investing, and advisory-led wealth management, while Syfe has built products around managed portfolios, brokerage and cash solutions. Banks such as DBS, OCBC and UOB also compete through increasingly digital wealth offerings, with the advantage of existing customer relationships.

The MakeGoodwill deal gives StashAway a different angle: instead of only adding more investment products, it is extending into financial administration around death, family and asset transfer.

The acquisition also reflects a wider shift in fintech. As customer acquisition becomes more expensive, platforms are trying to increase lifetime value by serving more use cases. For digital wealth players, that may mean retirement income, insurance, tax planning, estate planning or private markets. The winners will not necessarily be those with the longest product menu, but those that can make adjacent services simple without overstepping into areas that require regulated advice.

Also Read: Wealthtech, insurtech, SaaS fintech are the new hot verticals in Indonesia: AC Ventures report

StashAway’s challenge will be to integrate legacy planning without making it feel like another upsell inside an investment app. Wills are sensitive. They involve family relationships, mortality and trust. A clumsy user experience could undermine the very simplicity the acquisition is meant to deliver.

Still, the logic is clear. If digital wealth platforms have persuaded users to build portfolios online, the next phase is helping them organise what those portfolios are for. In a region where more people are investing but far fewer have planned how their assets should be passed on, StashAway’s acquisition of MakeGoodwill is a sign that wealthtech is moving from accumulation to continuity.

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For years, Southeast Asia’s battery ambitions have been framed around potential. Indonesia has nickel. Malaysia has semiconductor and advanced materials expertise. Singapore has research depth and capital networks. Thailand and Vietnam have growing electric vehicle supply chains. The Philippines is trying to build a stronger EV ecosystem of its own.

At the 4th ASEAN Battery Technology Conference in Malaysia this week, the discussion shifted towards a more difficult question: can these separate strengths be turned into an integrated regional industry?

Also Read: Southeast Asia’s EV startups draw US$622M as clean mobility shifts from pitch to pilot

Held from 19 to 21 August at the Mövenpick Hotel & Convention Centre KLIA in Sepang, ABTC 2026 brings together policymakers, manufacturers, researchers, investors and industry groups from across the region. Hosted by NanoMalaysia Berhad, the conference is themed “Industrialising Battery Technologies: Strengthening ASEAN’s Battery Value Chain for Global Competitiveness”.

That wording matters. The region is no longer talking only about research collaboration or EV adoption targets. It is now confronting the industrial layer behind the energy transition: battery materials, cell development, safety testing, certification, manufacturing scale-up, recycling and market deployment.

Opening the conference, Malaysia’s Minister of Science, Technology and Innovation, YB Datuk Chang Lih Kang, said ASEAN must move “from discussion to industrialisation”.

“ASEAN’s strength lies in our ability to complement one another through research, manufacturing, standards development, investment, and market integration. By working together, we can build a resilient regional value chain that benefits all our economies,” he said.

The challenge is that battery manufacturing is capital-intensive, technically demanding and highly sensitive to scale. China dominates much of the global battery supply chain, from processing to cell production. South Korea and Japan remain major players in advanced battery technologies, while the US and Europe are using industrial policy to localise parts of the chain. ASEAN’s opportunity is real, but it will depend on whether the region can coordinate rather than duplicate efforts across ten fragmented markets.

Malaysia positions itself as a battery industrialisation hub

Malaysia’s role as host reflects its own attempt to move battery research closer to commercial production.

Through initiatives such as the NanoMalaysia Energy Storage Technology Initiative and the Hydrogen–EV–Battery Centre, the country has been building capabilities in research, prototyping, testing, validation and pilot-scale manufacturing. More recent developments, including the establishment of GigaFactory Malaysia Sdn Bhd and Malaysia’s graphene-enhanced lithium-ion battery technology, point to an effort to convert laboratory work into industrial capability.

For Southeast Asia, this matters because the battery economy will not be built by raw materials alone. While Indonesia’s nickel reserves have attracted global attention, the broader value chain includes cathode materials, cell design, battery management systems, pack assembly, safety certification, second-life applications and recycling. Countries that can occupy several points along this chain will have a better chance of retaining value locally.

Prof. (Adj.) Dr Rezal Khairi Ahmad, CEO of NMB Group, said the region already has technical capabilities, but needs clearer pathways to scale.

“Malaysia has been building the infrastructure to move technologies from research into pilot and industrial application, but no single market can build the battery economy alone,” he said. “ABTC gives us the opportunity to connect capabilities across ASEAN, develop stronger cross-border pathways and collectively build an industry that can compete globally.”

Also Read: Grab invests in EBOOST as Vietnam’s EV charging race shifts into higher gear

That is the central tension facing the region. ASEAN has the ingredients for a battery ecosystem, but ingredients do not automatically become an industry. Investors will look for predictable demand, common standards, skilled talent, bankable offtake agreements and manufacturing discipline. Governments, meanwhile, need to align EV policies, grid storage plans and industrial incentives without turning the sector into a subsidy race.

Malaysia-Indonesia pouch cell points to regional complementarity
One of the most concrete announcements on the opening day was the launch of a Malaysia-Indonesia NMC-graphene lithium-ion pouch cell, developed through collaboration between NanoMalaysia Berhad and Indonesia’s National Battery Research Institute.

NMC refers to lithium-ion battery chemistry using nickel, manganese and cobalt in the cathode. It is widely used in EVs and energy storage because it can offer relatively high energy density, though it also raises questions around cost, raw material sourcing and safety management. Graphene, a highly conductive carbon-based material, is being explored globally to improve battery performance, durability and charging characteristics.

The pouch cell builds on a memorandum of understanding signed by NMB and NBRI during ABTC 2025. That agreement covered technology transfer, joint research and innovation, testing and standardisation, education and industrial training.

In practical terms, the initiative combines Indonesia’s work in NMC active material production with Malaysia’s battery formulation, graphene technology and cell development capabilities. It is a small but useful example of how the region could divide labour: one country need not own the entire stack if cross-border collaboration allows materials, research, testing and eventual commercialisation to connect more efficiently.

For Indonesia, such collaborations could help move its battery strategy beyond mineral extraction. For Malaysia, they offer a route to plug its materials science, electronics and manufacturing experience into a regional supply chain. For ASEAN as a whole, these projects test whether regional cooperation can survive the commercial realities of intellectual property, ownership, standards and market access.

Partnerships signal interest, but execution will decide impact

ABTC 2026 also saw several partnership announcements across battery storage, manufacturing, AI-enabled operations and commercialisation.

GigaFactory Malaysia and Milan Utama signed a supply agreement for prototyping compact battery energy storage systems. Infien Energy and Ampace announced a strategic collaboration to explore opportunities in battery technologies. Green Tenaga and Go Rental Singapore entered a partnership focused on sustainable energy solutions, while Neoron Energy Network, Aryva Energy, Nano Commerce and GigaFactory Malaysia formed a collaboration to develop and commercialise battery and energy storage solutions.

GigaFactory Malaysia also announced separate initiatives with Axium Industries and Montavista Energy Technologies Corporation. The Axium partnership is aimed at using AI and digital tools to improve battery manufacturing, operational efficiency and supply chain management. The Montavista collaboration focuses on high-energy-density battery innovation, recycling, manufacturing capabilities, equipment facilitation and market development.

Such agreements are common at industry conferences, and not all will translate into factories, revenue or exportable products. Still, they indicate where the region’s battery conversation is heading. Energy storage is becoming as important as EVs, particularly as Southeast Asian countries add more solar and renewable power to their grids. Battery energy storage systems can help manage intermittency, stabilise grids and support decentralised energy models for factories, commercial buildings and remote communities.

Safety and certification will also become more important as batteries move from pilot projects into homes, vehicles, factories and grid infrastructure. The conference’s opening sessions included discussions on battery safety, manufacturing scale-up, circularity and emerging technologies, with speakers from Argonne National Laboratory, the University of Chicago, SEDA, MARii, Pertamina, A*STAR and the Electric Vehicle Association of the Philippines.

From conference circuit to industrial policy

ABTC has evolved quickly since its first edition in Bali in 2023. Subsequent editions were held in Singapore and Phuket, with the 2026 event in Malaysia and the 2027 edition set to be hosted by the Electric Vehicle Association of the Philippines. Along the way, the platform has supported regional industry coordination, including an ASEAN battery associations memorandum in 2023 and the ASEAN Battery Safety Network in 2025.

The handover to the Philippines is symbolic, but the bigger test lies outside the conference hall. Southeast Asia’s battery ambitions will depend on whether countries can coordinate standards, train engineers and technicians, attract long-term capital, support recycling and create enough domestic demand to justify manufacturing investment.

The global battery race is moving fast. ASEAN does not need to replicate China’s scale to be relevant, but it does need to be clear about where it can compete. That may be in selected materials, specialised manufacturing, pack assembly, battery management systems, energy storage deployment, testing and certification, or recycling.

Also Read: Inside Thailand’s EV and battery push: Balancing growth with sustainability

The shift from dialogue to industrialisation is therefore less a slogan than a deadline. If Southeast Asia wants to capture more value from the EV and energy storage boom, the next phase will be measured not by memoranda signed, but by plants built, products certified and batteries deployed in real markets.

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Spending the last several months in Southeast Asia allowed me to expand my comprehension of the global market dynamics in times of uncertainty. And bridging global expansion with vibrant hubs, AI exponential adoption and market opportunities closely, I noticed that every market report eventually produces numbers that get quoted everywhere and questioned nowhere.

So, as I always dig deeper than the surface level, I am bringing to you some insights of my experience across SEA markets and the link with Google’s newly released Gemini Report: Southeast Asia 2026.

Two different kinds of “#1”

My first reaction when learning that Singapore is leading the highest AI adoption per capita globally was similar to an unamused emoji; since it is obvious that a market with high internet infrastructure and a ~6M population will get to the top of per capita ranks. I even ran a comparison with top markets of my dominance to see whether that would be applicable. And the results tell us a lot of interesting outputs.

In terms of AI Adoption rate per capita, the UAE ranks #1, which is a very similar market to Singapore when it comes to Internet infrastructure and penetration. A similar vision to embed AI into everyday life and successfully doing so. 

The difference though, is what made Singapore’s stats interesting to me. The UAE has government adoption as the primary source of adopting AI. The position is largely the product of national strategy: sustained government investment in compute infrastructure, sovereign model development, and top-down digital policy. 

In Singapore, the government mandate is also strong, though it is the population that is the driving force behind adoption: a daily behaviour that, on average, shows that Singaporeans prompt Gemini nearly 10 times per day, becoming #1 in the SEA region on daily engagement. 

In this regard, that is an impressive metric to show how the market is embedding AI as part of everyone’s lives. 

Also Read: Where AI money is made, and where SEA founders should actually compete

And comparing metrics on a superficial level misleads decision making because neither figure is wrong — they’re measuring two different growth models, and the distinction is the useful part.

 That’s the distinction I look for in any market I work in: is growth being built by policy, or is it being built by user habit? 

The two require completely different partnership and go-to-market approaches, and combining them is one of the common mistakes companies do in comparing markets to expand. 

SEA region resists a single narrative

The stats reinforce something I’ve long believed about economic blocs specifically: A region with fragmented reality full of cultural and market nuances that influence behavior, consumption and opportunities. Similar to the Middle East, Africa and LATAM. 

How interesting to see that AI adoption takes shape according to market dynamics. Knowing that in the Philippines women account for two-thirds of all micro, small, and medium enterprises, and that they heavily drive neighbourhood economies through home-based ventures, AI tools that help them scale while keeping a lean structure are key for their multi-faceted entrepreneurial journey. Hence, Philippines is the only country in the region where female users are the majority. 

Also Read: How AI helps sales teams stop losing context between calls and follow-ups

In Indonesia, 82 per cent of prompts come from mobile, a pattern that is above SEA’s market average. It reflects the emerging reality of individuals transiting places, having challenging infrastructure and being creative in several ways to make their living. 

Talking about creative ways, a standout pattern comes from Malaysia, where I have been fortunate to spend most of my time in the past months. Collectively, the SEA region accounts for over 5 billion images generated in the past 12 months, and Malaysia leads the rank as 1 in 5 users ask Gemini to generate images. To me, it makes a lot of sense – Malaysia has shown to me how vibrant, colourful and full of life, the country is.

These stats are simply different expressions of how each market is engaging with the same technology, shaped by local digital habits, language, and economic structure. That’s precisely the kind of nuance that gets lost when companies treat “Southeast Asia” as a single go-to-market target rather than a set of markets with their own logic.

Why this matters for your international expansion journey

I find this kind of comparative reading useful well beyond AI adoption. It’s the same discipline I apply when comparing opportunities across emerging markets and global hubs: look past the ranking, understand what’s actually driving the number, and never assume one market’s growth story explains another’s.

For companies planning their expansion and go-to-market strategies — whether from Asia, the Gulf, Europe, or the Americas — that distinction between policy-driven and habit-driven growth is often the difference between a market-entry plan that works and one that just looks good in a slide deck.

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Southeast Asia is piloting AI faster than almost anywhere else in the world. But how do you turn that pilot-phase momentum into real, enterprise-wide value? It forces a hard look at your data, your architecture, and the new operational risks.

Southeast Asia isn’t catching up on artificial intelligence; in many respects, it’s actually setting the pace. A study by McKinsey and the Singapore Economic Development Board revealed that 8 percent of companies in the region have fully scaled AI initiatives – edging out the 6 percent global average. Frontrunners like Singapore (56 percent) and Indonesia (51 percent) are already reporting meaningful progress toward region-wide implementation.

Yet, retail occupies a starkly split position within this landscape. More than half (56 percent) of consumer goods and retail enterprises across ASEAN remain locked in continuous piloting and experimentation. They are caught in a web of fragmented data environments, divergent cross-border regulations, and a persistent scarcity of AI-ready talent.

However, this scale and implementation hurdle isn’t unique to Asia. Global research shows that nearly three-quarters of retail AI initiatives fail to reach production, while close to half of all broader enterprise AI proofs-of-concept are scrapped before scaling.

What is unique to Southeast Asia is the shape of the opportunity: a young, mobile-first population accustomed to super-apps, paired with retail infrastructure that rarely carries the weight of rigid, legacy systems such as mainframes found in Western markets.

Having spent years designing the data and AI architecture for large-scale retail deployments globally, I’ve learned that the pilot-to-production gap is rarely a math problem. It’s a systems problem. What thrives in a controlled lab environment seldom survives contact with the chaotic realities of a multi-market retail operation.

Where AI pilots break first

A pilot succeeds precisely because it’s small, it generally focuses on one market, one dataset and one motivated team. None of those conditions hold once a retailer tries to roll the same model out across Vietnam, Indonesia, the Philippines, and Thailand at once.

Data is usually the first casualty

Imagine this: A brilliant demand-forecasting model perfected on clean, structured data in Singapore immediately sputters when confronted with Indonesia’s point-of-sale formats, Vietnam’s informal retail networks, or varying definitions of what constitutes a “completed transaction.” Across industries, roughly 85 percent of AI project failures trace back to poor data quality rather than the frontier model itself. In Southeast Asia – where modern trade, traditional trade (like warungs and sari-sari stores), and social commerce intersect, this data friction is particularly acute than in more homogenous markets.

The second casualty is strategic clarity and a clear definition of success

Retail AI projects that get scrapped often never had one to begin with. A staggering 73 per cent of failed initiatives lacked quantified success criteria from the start. Vague mandates such as “Improve customer personalisation” isn’t a target. A target like “reduce category-specific stockouts by 4.5 per cent across Tier-2 regional hubs” gives the engineering team an actual goal to track and build towards. More importantly, this means – this has the business stakeholder buy-in.

Also Read: Where AI money is made, and where SEA founders should actually compete

Designing for fragmentation, not against it

Let’s face it! Southeast Asia’s retail landscape is largely fragmented – by national borders, regulations, payment rails, language and new consumer habits. Rather than treating this diversity as a temporary friction to be ironed out later, retailers that are scaling AI successfully design their tech stacks around it from day one.

This is part of why multi-cloud and hybrid approaches have become the default in enterprise AI. Most large enterprises globally now run AI workloads across more than one cloud provider, largely to avoid the single point of failure (and the single point of pricing leverage) that comes with full dependency on one vendor. A recent CIO survey found more than a third of enterprises are now running five or more AI models in production, and a separate research found that close to three in four enterprises expect severe business disruption if a single AI vendor’s service were interrupted.

For an ASEAN retailer running real-time inventory and pricing decisions across several ASEAN markets at once, often with different data residency rules in each, that dependency is an existential continuity risk. Designing for portability – using cloud-agnostic data pipelines, open-standard interfaces, and flexible workload deployment – requires a higher upfront effort and investment. However, it guarantees that when data sovereignty rules change in Jakarta or a newer model emerges in Singapore, the business can adapt without rebuilding its core infrastructure from scratch.

Governance at the speed of autonomous scale

When your AI is running a small pilot, governance is easy, because the blast radius is tiny. But at a regional scale, an autonomous AI system might be dynamically setting prices, generating localised promotional content, or auto-issuing purchase orders across hundreds of storefronts simultaneously. Suddenly, you need a new kind of operating manual to ensure it doesn’t go off the rails.

Southeast Asia’s regulatory landscape is moving quickly but unevenly. Singapore and Vietnam have established some of the region’s first comprehensive, risk-based AI frameworks, while other markets are still catching up. Globally, the picture is similar – one 2026 survey of data leaders found that three out of four organisations admit their AI governance hasn’t kept pace with how quickly the technology has been adopted.

The retailers navigating this landscape successfully treat governance as a core operating system rather than a legal checkpoint at the end of a sprint. They assign clear operational ownership for every production model and mandate strict sign-offs before an algorithm interacts with a new country’s customer base.

More importantly, as AI systems move from passive recommendations to direct action – such as re-routing real-time warehouse inventory or approving supplier payouts – the central question changes. It is no longer just “Is this output accurate?” but “Was this the right commercial decision for the brand?”

Also Read: Where AI money is made, and where SEA founders should actually compete

What the region’s first movers are doing differently

None of this is an argument against piloting. It remains the cheapest way to test a hypothesis. What separates the retailers actually scaling AI across Southeast Asia’s fragmented markets is that they treat the pilot as one input into a production decision, not a stand-in for one.

In practice, these organisations share key operational habits: 

• Executive mandate over tactical pilots: C-suite commitment in high-performing ASEAN enterprises is nearly double that of their peers. Clear evidence that scaling AI requires senior leadership to move beyond approving budgets and take direct ownership of operational change management.
• Prioritising the data foundation: They clean and standardise regional data feeds before attempting to scale complex machine learning models. Data architecture is AI architecture.
• Reinventing workflows, not just layering AI on top: The region’s frontrunners are twice as likely to fundamentally redesign entire business processes, from procurement and supply chain routing to store operations, around AI capabilities. They reject the temptation to layer algorithms on top of unchanged, decades-old operating models.
• Architecting for portability: They design systems that comply with local data-residency laws and vendor-neutral pipelines from day one.
• Governance as an operational enabler: High performers are more than twice as likely to embed formal AI governance into their daily operations.
• Empowering local teams: They give field managers and local operators direct agency in redesigning their workflows around AI tools, ensuring systems are actually adopted rather than bypassed.

Southeast Asian retailers possess a rare structural advantage; they are largely unencumbered by decades of rigid legacy IT infrastructure, and they serve a consumer base that adopts digital innovations effortlessly.

Whether that advantage translates into long-term market dominance won’t depend on how many pilots a company launches this quarter; it will depend on whether the underlying architecture can withstand the weight of real scale.

The thoughts shared below and opinions expressed are the author’s own and do not necessarily reflect the views, positions, or opinions of his employer or any organisation he is affiliated with.

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