For many large companies in Southeast Asia, the challenge with artificial intelligence (AI) is no longer access. The models are available, the cloud infrastructure is ready, and boards have approved AI experimentation.

The harder problem is turning that experimentation into systems that work inside heavily regulated businesses without breaking compliance, confusing staff or creating new operational risks.

That is the gap Singapore-headquartered OneByZero, or OBZ, is trying to fill. The company has raised US$20 million in Series A funding led by Jungle Ventures, marking its first external fundraise after three years of operating with enterprise customers across the region.

Also Read: Singapore’s AI dividend will depend on what happens after the pilot phase

OBZ describes itself as a “frontier AI deployment company”, a phrase that reflects a broader shift in the AI market. Rather than selling a standalone software tool, the company places engineering teams inside large organisations to identify where AI can create value, build the technology into existing workflows, and keep improving it after deployment.

Its focus is on regulated and operationally complex sectors such as financial services, telecommunications and retail. These are industries where AI pilots are common, but production deployments tend to move slowly because systems are old, data is fragmented, and mistakes can carry reputational or regulatory consequences.

“Every enterprise can now get access to powerful AI. The value comes when it runs inside the systems that run the business, under the company’s own rules, and gets better every week,” said Niket Vaidya, CEO and co-founder of OneByZero. “That is the work we do every day, and this funding lets us do more of it, in more markets, and more industries.”

The deployment problem

OBZ’s fundraise lands at a time when enterprises across Asia Pacific are under pressure to prove that AI spending can produce measurable returns. Since generative AI tools went mainstream, companies have run pilots in customer service, internal knowledge management, software development, fraud monitoring, marketing and document processing. But many of these efforts remain stuck at the proof-of-concept stage.

The reasons are familiar to enterprise technology teams. AI systems need access to business data, but that data often sits across multiple legacy systems. Customer-facing use cases require strict guardrails. Regulated industries need audit trails. Staff need to know when AI can act on its own and when a human must intervene.

OneByZero says its approach is built around these realities. Its forward-deployed engineers work alongside customer teams to identify high-value use cases, build and deploy systems, then stay involved to run and improve them. It also operates local teams in each market, which it says helps customers deal with language, regulatory and systems differences.

The company claims its deployments have helped enterprises automate more than 90 per cent of some customer-facing interactions, generate measurable cost savings, and accelerate complex data modernisation projects by 50 per cent. It did not disclose customer names or revenue figures, but said it has more than doubled revenue annually over the past three years.

Also Read: Language was never the problem: Inside SEA’s real AI adoption gap

For Southeast Asia, this kind of work is likely to become more important. The region’s largest banks, telcos and retailers often operate across several markets, each with its own rules, languages and consumer behaviours. An AI system that works in Singapore may need significant adjustment before it can be used in Indonesia, Thailand, Vietnam or the Philippines. That makes deployment expertise, not just model access, a meaningful differentiator.

NEO and the rise of AI coworkers

At the centre of OBZ’s offering is NEO, its AI deployment platform. The company describes NEO as the control layer behind enterprise AI workforces, combining reusable components with governance features such as records of every agent action.

In simple terms, NEO is meant to help companies define what AI agents are allowed to do, where human approval is required, and how those actions are tracked. OneByZero calls these agents “AI Coworkers” — governed AI systems with defined roles and controls. The idea is that AI handles high-volume, repetitive work, while humans retain judgement and accountability.

“We have built NEO so companies can define what AI is allowed to do, where human judgement is required and how every system is governed,” said Vibhore Kumar, PhD, CTO and co-founder of OneByZero. “That foundation lets them introduce more capable AI without losing control.”

The governance point is crucial. As AI agents become more capable, enterprises are moving beyond chatbots and copilots into systems that can take actions: updating records, generating responses, flagging transactions, routing cases or initiating workflow steps. In sectors such as banking, telecoms and healthcare, companies will need clear limits on what those agents can do.

This is also where smaller or open-weight language models may play a role. OBZ said part of the new funding will go into helping enterprises build their own AI on open-weight and small language models. For regulated companies, smaller models can sometimes be easier to customise, control and run in specific environments than general-purpose large models. They may also cut costs for repetitive tasks where a frontier model is not required.

Expansion across Asia Pacific and Japan

OBZ currently operates in nine markets: Australia, India, Indonesia, Malaysia, the Philippines, Singapore, Thailand, the US and Vietnam. It plans to use the Series A funding to grow its forward-deployed engineering teams and deepen customer relationships in these markets.

It also plans to enter Japan, one of Asia’s largest enterprise technology markets. Japan is attractive because of its large corporate base, advanced manufacturing and financial sectors, and urgent need for productivity tools as the country grapples with labour shortages and an ageing population. But it is also a difficult market to crack, requiring local relationships, language capability and long enterprise sales cycles.

Also Read: fileAI expands in Japan with new backing from SMBC and Singtel Innov8

Beyond financial services and telecommunications, OBZ wants to expand into conglomerates, healthcare and the public sector. These sectors share many traits with its current customers: complex operations, large volumes of data, and a need for careful governance.

Jungle Ventures’s investment reflects growing investor interest in companies that can turn AI adoption into practical enterprise outcomes rather than simply building model wrappers. “OneByZero stood out because it is already doing what much of the enterprise AI market is still talking about,” said Yash Sankrityayan, Managing Partner at Jungle Ventures. “The team has spent three years deploying AI inside large, complex organisations and delivering measurable results.”

A crowded but evolving field

OBZ is not alone in chasing the enterprise AI deployment opportunity. Globally, it competes for attention and budgets with companies such as Palantir, C3.ai and DataRobot, and with large consulting firms including Accenture, Deloitte, IBM and Capgemini, all of which help enterprises operationalise AI. In Asia, systems integrators, cloud partners and boutique AI consultancies are also moving into the same space.

Its differentiation will depend on whether it can prove that its forward-deployed model and NEO platform deliver repeatable results across markets and industries. That is not easy. Service-heavy AI deployment businesses can be difficult to scale, while platform businesses need standardisation. OBZ is trying to sit between the two: using hands-on engineering to solve messy enterprise problems, then turning what it learns into reusable templates and governance tools.

Also Read: Why Southeast Asian enterprises need AI governance before scaling generative AI

That middle ground could be valuable in Southeast Asia, where companies often need local execution as much as software. But it also means OBZ will have to keep hiring strong technical teams in multiple markets while maintaining quality and consistency.

The broader market direction is clear. Enterprises are moving from asking what AI can do to asking where it can be trusted to act. OBZ’s bet is that the next wave of AI adoption will be won not by the companies with the flashiest models, but by those that can make AI work inside the unglamorous systems that actually run large businesses.

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Singapore’s electric vehicle (EV) market is no longer waiting for a breakthrough moment. In 2026, the shift is already visible on the road, in dealerships, and across public car parks where chargers have become a more common part of the urban landscape. But the next stage of growth may be harder than the first.

EV sales in Singapore are forecast to rise 34.3 per cent in 2026 to 34,940 units, according to BMI Country Risk and Industry Research, a Fitch Group unit. That would lift EVs to 54.6 per cent of total vehicle sales this year, underlining how quickly electric mobility has moved from early adopter territory into the mainstream.

Also Read: VinFast’s ride-hailing arm Green SM takes on Jakarta’s ojek economy with e-scooters

The wider fleet is also changing. BMI expects Singapore’s EV fleet to reach 92,705 units in 2026, or 10.7 per cent of the country’s total vehicle fleet. By 2035, the research house expects EVs to account for 44 per cent of all vehicles in Singapore, with EV sales making up 85 per cent of total vehicle sales.

Those numbers point to a market that is accelerating fast. Yet they also highlight a more complicated reality: Singapore’s EV transition is becoming increasingly dependent on policy design, charging availability, fleet electrification and the economics of ownership in a country that does not want too many cars in the first place.

A fast-growing market, but not a typical one

Singapore’s EV adoption has gathered pace rapidly in 2026. As of June, EVs accounted for 70 per cent of new vehicle registrations. In the first half of the year, EV adoption reached a record 62.4 per cent of new car registrations, up 110 per cent year on year.

The first quarter marked an important turning point. EVs made up 57.6 per cent of new car registrations, or 7,679 vehicles, the first time electric cars outsold internal combustion engine and hybrid vehicles combined, according to BMI. In June alone, EVs accounted for 4,791 new vehicle registrations.

This makes Singapore one of Southeast Asia’s most advanced EV markets by adoption share, even if its absolute vehicle volumes remain small compared with larger neighbours such as Indonesia, Thailand or Malaysia. The city-state’s high-income consumer base, compact geography and strong regulatory capacity make it well suited to EV rollout. Range anxiety is less severe than in large countries, while dense housing and public car parks allow charging infrastructure to be planned with more central coordination.

But Singapore is also unlike most car markets. Vehicle ownership is deliberately constrained through the Certificate of Entitlement system, high registration costs and a long-standing “car-lite” strategy that prioritises public transport. That means EV adoption can grow quickly as a share of new sales, even while the total number of private cars remains tightly managed.

BMI expects passenger EV sales growth to moderate over the longer term, with an average annual growth rate of 5.3 per cent between 2026 and 2035. The constraint is not only consumer demand. It is the structure of Singapore’s transport policy.

Incentives are doing heavy lifting

Government incentives remain one of the most important drivers of adoption. Singapore’s EV Early Adoption Incentive, which runs until December 2026, provides new electric cars and taxis with a 45 per cent rebate on the Additional Registration Fee, capped at US$5,864 in 2026.

The Enhanced Vehicular Emissions Scheme also supports demand, offering rebates of up to about US$17,592 for qualifying cars in 2026 and around US$15,637 in 2027. These incentives matter because Singapore is one of the world’s most expensive places to own a car. Even a cheaper EV can carry a high upfront cost once taxes, fees and the Certificate of Entitlement are included.

Also Read: Thailand’s mobility future will be decided by data, not just vehicles

At the same time, policy is becoming more exacting. From 2026, the Vehicular Emissions Scheme band thresholds were recalibrated to align with stricter real-world measurements under the Worldwide Harmonised Light Vehicles Test Procedure. BMI said this will affect the rebates and surcharges applied to new vehicle registrations.

The recalibration is important because Singapore is not simply trying to replace petrol cars with electric cars. It is trying to reduce transport emissions while maintaining tight control over road usage. In that context, incentives must encourage cleaner vehicles without undermining the broader push towards public transport.

This is where the country’s EV story differs from other Southeast Asian markets. Thailand and Indonesia are using EV policy partly to build manufacturing supply chains. Singapore’s focus is demand-side adoption, infrastructure readiness and emissions reduction within a dense urban transport system.

Chinese brands change the price equation

Another major force behind Singapore’s EV momentum is the arrival of more affordable models, particularly from Chinese manufacturers. BYD has become the standout example.

According to BMI, BYD accounted for 25 per cent of Singapore’s passenger vehicle market in the first half of 2026, compared with 12.5 per cent for Toyota. In the first quarter, BYD represented 24.3 per cent of new vehicle registrations with 3,239 units, making it the market leader.

This reflects a wider regional pattern. Chinese EV makers have been expanding aggressively across Southeast Asia, bringing lower-cost models, battery expertise and faster product cycles. In markets where EVs were once associated mainly with premium brands, Chinese manufacturers have helped shift the conversation towards affordability and practicality.

For Singapore buyers, the impact is amplified by the cost of ownership. Any reduction in the vehicle’s base price can make a meaningful difference once rebates and registration costs are applied. But it also increases competitive pressure on Japanese, Korean and European automakers that have long been familiar names in Singapore.

Charging network becomes the next test

As EVs move into the mainstream, charging infrastructure becomes more than a convenience issue. It becomes a confidence issue.

Singapore had around 30,500 EV charging points as of March 2026, nearly double the roughly 15,300 recorded in November 2024. The government aims to install 60,000 charging points by 2030 under the Singapore Green Plan 2030, including 40,000 in public car parks and 20,000 at private properties such as residential developments and offices.

That target matters because many Singaporeans live in high-rise public or private housing and do not have access to private garages. Unlike landed home owners in other markets, they depend heavily on shared charging infrastructure in car parks, workplaces and commercial areas.

Also Read: Tesla establishes Vietnam subsidiary as EV rivalry with VinFast looms

The charging market is also getting more competitive. BMI said there were 36 EV charging operators in Singapore as of July 2026, although it expects consolidation as companies compete in a crowded field. In June, SP Mobility completed its acquisition of ChargEco, integrating more than 1,000 public charging points and becoming the operator of Singapore’s largest EV charging network.

Regulation is also evolving. In March 2026, Singapore raised its national EV charging standard from Technical Reference 25 to SS 722. The new standard includes requirements for smart-grid integration, electrical safety, battery-swapping protocols and updated direct-current fast-charging specifications.

Fleets may drive the next wave

Commercial vehicles could become an important part of the next growth phase. BMI forecasts commercial EV sales to rise 18.5 per cent in 2026 to 2,652 units, after growing 63.4 per cent in 2025. From 2026 to 2035, commercial EV sales are expected to grow at an average annual rate of 8.4 per cent.

The drivers are clear: pressure on businesses to decarbonise supply chains, government and municipal fleet electrification, and better charging infrastructure. Incentives also help. The Commercial Vehicles Emissions Scheme, which runs until March 2027, provides incentives of up to about US$15,637 for the least-polluting commercial vehicles and penalties of up to around US$11,728 for the most polluting.

For heavy vehicles, the Heavy Vehicle Zero Emissions Scheme supports businesses registering new zero-tailpipe-emission heavy goods vehicles and buses. The incentive was reduced to about US$11,728 from September 2026, except for vehicles with a maximum laden weight above 7,000kg, after strong take-up and a narrowing cost gap with internal combustion models.

BMI expects Singapore’s electric heavy commercial vehicle segment to remain small at about 212 units in 2026, but forecasts it to reach 1,131 units by 2035. Bus fleet electrification should also provide medium-term support.

Still, not all consumer sentiment is moving in one direction. A 2026 study cited by BMI found that 32 per cent of respondents planned to buy an internal combustion engine vehicle over the next two years, up from 26 per cent in 2024. Concerns over charging availability and hidden costs were among the reasons.

Also Read: Waymo’s Singapore entry raises the stakes for autonomous mobility in Asia

That is the paradox of Singapore’s EV transition. Adoption is rising quickly, but future growth will not come from a simple expansion of private car ownership. Public transport remains central: MRT, light rail and bus networks recorded an average of 7.2 million daily rides in 2023, and the government wants at least 80 per cent of households to be within a 10-minute walk of a train station by 2030.

Singapore’s EV market is therefore entering a more mature phase. The easy story is that electric cars are winning. The harder story is what comes next: keeping incentives calibrated, making charging reliable, electrifying fleets, and ensuring EV adoption supports, rather than competes with, the country’s broader car-lite future.

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For most artificial intelligence companies, Singapore is either a regional sales base or a policy-friendly testbed. For Zero Gravity, better known as 0G, the city-state is now becoming something more central: its global headquarters.

The AI infrastructure company said it will invest about US$15.4 million in Singapore over the next five years, using the country as a base to grow its operations, research partnerships and developer ecosystem.

The announcement was made at 0G Dev Day Singapore 2026 at the National Gallery Singapore, where close to 3,000 participants registered, including developers, researchers, businesses, investors and members of the wider technology community.

Also Read: SEA’s venture capital shifts from mega-rounds to AI and SaaS

The move places 0G in a country that has been working to position itself as a trusted AI hub for Southeast Asia and beyond. Singapore’s National AI Strategy 2.0 has put emphasis on talent, compute access, governance and practical adoption, while the city’s regulators have tried to balance innovation with safety. For companies building AI infrastructure, that mix is attractive: Singapore offers proximity to regional markets, deep pools of capital and a government keen to shape global AI standards.

Senior Minister of State for Digital Development and Information and Health Tan Kiat How, who delivered the keynote at the event, framed Singapore as a place where AI products can be deployed, adapted and scaled. That message fits neatly with 0G’s own pitch: build in Singapore, then export globally.

Michael Heinrich, CEO and co-founder of 0G, said the company’s commitment is “not simply about opening an office” but about “research, talent, innovation and long-term investment”. He added: “We see Singapore not as a final destination, but really as a launchpad for the rest of the world.”

A headquarters play, not just an office opening

Of the planned US$15.4 million investment, around US$7.7 million will go towards establishing Singapore as 0G’s global headquarters, building operations, growing the team and developing its ecosystem.

The company has already committed about US$3.9 million to a four-year research collaboration with Nanyang Technological University (NTU), focused on decentralised AI and blockchain-based infrastructure. It plans to commit another US$3.1 million to research collaborations with other universities and academic partners. A further US$770,000 will support AI and badminton research with NTU and YB Badminton Academy.

0G’s first physical office globally is also in Singapore, at Stamford Place. The location is symbolically convenient: the building formerly housed Singapore’s National Heritage Board, a detail Heinrich has used to position the company as one building future infrastructure from a site linked to the country’s past.

Also Read: Singapore’s Psalion raises US$50M fund for Web3’s next practical phase

At a practical level, the decision reflects a broader pattern in Southeast Asia’s tech ecosystem. Singapore continues to attract regional headquarters for startups, fintech firms, AI companies and crypto-related infrastructure players, even when their markets, users and developer communities are spread across Indonesia, Vietnam, the Philippines, India and beyond. Its strengths lie less in domestic market size and more in regulation, talent mobility, institutional partnerships and investor access.

Taking decentralised AI from lab to court

The more unusual part of 0G’s announcement is not the headquarters plan, but where some of its research is going next: badminton.

At Dev Day, Zero Gravity Labs and NTU formalised the next phase of their existing US$3.9 million research collaboration, expanding work in decentralised AI towards real-world applications. Sports will be an initial focus, with badminton as the starting point.

The partnership, established in 2025, has been working on decentralised AI training, model alignment and verifiable AI systems. Researchers from 0G and NTU have had three collaborative research papers accepted at NeurIPS and one at ICML, two of the most closely watched machine learning conferences globally.

Badminton is not a random choice. In Southeast Asia, the sport has deep cultural and competitive significance, particularly in Indonesia, Malaysia, Thailand and Singapore. Singapore’s Loh Kean Yew, a former world champion, has also helped raise the sport’s profile locally, while his Asian Games silver added further momentum.

For AI researchers, badminton offers dense and fast-moving data. A single rally can involve rapid changes in body position, shuttle trajectory, footwork, shot selection, fatigue and tactical decision-making. Much of that is hard to capture in one clean dataset.

Working with NTU and YB Badminton Academy, 0G plans to explore a badminton foundation model that combines data from players, movement, video, training and competition. Foundation models are AI systems trained on broad datasets and then adapted for specific tasks. In this case, possible uses include helping coaches spot movement patterns that are difficult to see in real time, identifying training loads that may increase injury risk, and supporting young players with more personalised feedback.

“Badminton brings together frontier AI research, real-world data and a very human outcome: helping people perform better and stay healthier over time,” Heinrich said.

Also Read: Malaysia’s sovereign AI bet: Local context becomes the next startup moat

0G Singapore also signed a three-year memorandum of understanding with YB Events and Sports for Project New Frontiers: Bringing Badminton to New Horizons. Under the partnership, 0G Singapore will commit about US$204,000 annually for three years to support youth badminton development, international competition and the exploration of AI and emerging technologies in sport.

The trust layer question

Beyond sport, 0G is pitching itself as part of the infrastructure stack needed for safer AI adoption. The company describes its mission as building the “trust layer for AI”, with decentralised infrastructure designed to make AI more private, verifiable, sovereign and open.

At Dev Day, it showcased 0G Private Computer, a product aimed at bringing privacy and verification to sensitive AI workloads. Heinrich said the system is designed so that sensitive workloads can remain private, including from 0G itself. The broader idea is to give organisations more confidence over how data is handled and how AI workloads are processed, especially when proprietary information is involved.

The company also introduced BestCEO, a ready-to-use AI solution aimed at making advanced AI capabilities accessible to businesses, including small and medium-sized enterprises, without requiring them to build AI infrastructure or applications from scratch.

This is a relevant angle for Southeast Asia, where SMEs make up the backbone of most economies but often lack the technical teams or budgets to adopt AI meaningfully. The region’s AI opportunity is not only about large enterprises deploying copilots, but also about whether smaller companies can use the technology without handing over sensitive data or depending entirely on foreign platforms.

Rivals in a crowded AI infrastructure race

0G is entering a crowded and fast-shifting market. In decentralised AI and compute, it sits alongside global projects such as Bittensor, Gensyn, Akash Network, Render Network and Aethir, all of which are trying to rethink how AI models, compute resources and data networks are coordinated. It also competes indirectly with hyperscale cloud providers such as Amazon Web Services, Microsoft Azure and Google Cloud, which remain the default infrastructure providers for most AI companies. The key question for 0G is whether developers and enterprises will see decentralisation and verifiability as must-have infrastructure, rather than a technically elegant alternative to existing cloud systems.

Community as a test of accessibility

0G is also trying to position AI access as a community issue, not just an enterprise problem. At its first community AI workshop in Singapore, 70 residents, including many seniors, learned about AI and built websites and applications on 0G over two days. One senior participant built a website to help people understand which health screenings they should consider at different ages, including reminders for women about mammograms.

Also Read: Crypto is dead? Apparently not, says Y Combinator – Blockchain is still worth building

That example is small, but it points to the broader challenge around AI adoption in the region. For AI to move beyond boardrooms and developer conferences, it must become useful to ordinary users, schools, coaches, seniors and small businesses.

As 0G plants its headquarters in Singapore, the company is making a familiar but ambitious bet: that the city-state can serve as a neutral, trusted base for technologies meant to travel far beyond its borders. The harder test will be whether its infrastructure can move as smoothly from research papers to badminton courts, SMEs and real-world AI systems.

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Southeast Asia has become one of the world’s most competitive regions for investment.

Global companies are diversifying supply chains beyond China. Governments are offering tax incentives, industrial land and digital-economy programmes. New capital is flowing into manufacturing, data centres, semiconductors and technology companies.

Yet investors evaluating the region are looking beyond growth rates and startup potential.

They are also evaluating governments.

Will tax rules remain stable? Can foreign investors retain control of their companies? Will data be allowed to move across borders? Will incentives survive the next budget? Could a new regulation make an existing business model unviable?

These questions shape investment decisions more than many founders realise.

Capital is attracted by growth. It stays where the rules remain understandable.

Policy uncertainty has a price

Businesses do not always need low taxes or light regulation. They need rules they can plan around.

A company can model a 20 per cent corporate tax rate. It can adapt to foreign ownership restrictions. It can comply with strict data-protection laws.

What is much harder to manage is constant change.

If a licence normally takes nine months, a company can include that delay in its plans. If approval might take three months, two years or never arrive, the risk becomes harder to calculate.

The result is often predictable. Investors delay decisions, reduce the size of projects or choose another market.

Regulatory uncertainty effectively becomes an additional cost. Investors demand higher returns to compensate for it. They commit less capital and plan over shorter periods.

Startups are especially exposed.

Large corporations can hire legal teams, advisers and compliance specialists. Early-stage companies cannot. A sudden change in employment law, payment regulation, data policy or foreign ownership can consume months of management time and scarce cash.

For founders, uncertainty can be more damaging than strict regulation.

Stability does not mean no change

Governments must update policy.

Artificial intelligence, digital finance, platform work and cybersecurity all require new rules. A government that refuses to adapt can become as unattractive as one that changes direction too often.

The real difference is between structured reform and improvisation.

Credible governments explain why a rule is changing. They consult companies, coordinate between agencies and provide transition periods. Businesses may dislike the new rules, but they understand what is expected.

Less predictable systems announce policies abruptly, issue incomplete guidance or allow different agencies to interpret the same rule in different ways.

Investors can adapt to change. They struggle with confusion.

Also Read: Asian investors aren’t choosing between crypto and TradFi anymore

Vietnam: Consistency of direction

Vietnam is not Southeast Asia’s easiest market.

Businesses still report licensing delays, infrastructure constraints and differences between national and provincial implementation.

But Vietnam has maintained a clear economic direction for decades.

Successive governments have supported export-oriented manufacturing, trade integration and foreign investment. The details have evolved, but the broader strategy has remained recognisable.

That consistency has helped Vietnam build deep manufacturing supply chains.

Electronics companies attract component suppliers. Suppliers create demand for logistics, industrial software and professional services. Workers gain technical experience. Some later become founders or investors.

Vietnam is now trying to move into semiconductors, advanced electronics and higher-value manufacturing.

This shift will be difficult. Skills, energy supply and infrastructure remain constraints. But investors can see that the new strategy builds on the country’s existing industrial base.

Vietnam’s advantage is not perfect regulation. It is confidence in the long-term direction.

Malaysia: The challenge of implementation

Malaysia has strong infrastructure, experienced industrial clusters and an established role in electronics and semiconductors.

It also has a history of launching ambitious plans that can become harder to follow across political transitions and overlapping government agencies.

The country is now trying to build more durable industrial institutions.

The New Industrial Master Plan 2030 focuses on advanced manufacturing, semiconductors, technology and decarbonisation. The Johor-Singapore Special Economic Zone is another major test.

The zone aims to combine Singapore’s capital and connectivity with Johor’s lower costs, available land and workforce.

The economic logic is strong.

The challenge is execution.

Companies will judge the project by whether customs, immigration, licensing and investment approvals actually become simpler. They will also ask whether commitments survive changes in ministers and government priorities.

Malaysia does not lack strategies. Its competitive advantage will depend on turning those strategies into systems that businesses can trust.

Also Read: Reverse home bias: Why Southeast Asia’s digital investors may be diversifying in the wrong direction

Singapore: Credibility as infrastructure

Singapore offers the region’s clearest example of regulatory predictability.

Its rules are not always light. Financial services, employment, data protection and corporate governance are closely regulated.

Its advantage lies in the process.

Changes are usually announced clearly, accompanied by guidance and introduced through institutions with defined responsibilities.

This gives investors confidence that official decisions, contracts and regulations will retain their meaning.

Singapore’s model also has limits.

It is expensive. Land is scarce. Labour costs are high. The domestic market is small.

As a result, many companies place headquarters, intellectual property and financing functions in Singapore while locating manufacturing or operations elsewhere in Southeast Asia.

This shows the value of regulatory credibility. Even when physical activity is distributed across the region, ownership and strategic control often remain in the jurisdiction investors trust most.

Stability alone is not enough

Policy stability can also preserve bad systems.

A predictable but inefficient licensing process is still inefficient. Stable protectionism can still discourage investment. A long-standing subsidy may support weak companies rather than productive ones.

Consistency therefore needs to be combined with competence.

Governments must be able to update policies, enforce them fairly and coordinate across agencies.

Growth can also compensate for instability.

Investors may accept regulatory risk in markets with exceptional consumer growth, strategic resources or strong supply-chain advantages.

Also Read: India’s IPO boom is rewriting the exit playbook for global investors

But this often influences the type of capital that arrives.

Short-term investors may tolerate uncertainty. Factories, infrastructure projects and research centres cannot move easily once established. They require greater confidence in the future.

Policy predictability matters most when a country wants long-term capital that trains workers, develops suppliers and becomes embedded in the local economy.

What this means for startup ecosystems

Startup policy is often built around visible programmes.

Governments announce accelerators, matching funds, conferences, tax incentives and startup visas. These initiatives can help, but they do not create an ecosystem on their own.

Founders also need reliable company law, sensible tax treatment of employee shares, predictable visa rules, workable bankruptcy procedures and clear data regulations.

When these systems are uncertain, founders adapt.

They incorporate holding companies abroad. They keep intellectual property in Singapore. They hire through foreign entities. They raise capital in another jurisdiction.

The startup may continue operating locally, but ownership, financing and strategic control move elsewhere.

Countries then risk retaining low-value activity while losing the parts of the company that create the most wealth.

Credibility may be the cheapest incentive

Southeast Asian governments are competing with tax holidays, grants, industrial zones and infrastructure spending.

But incentives lose value when investors do not trust the policy framework around them.

A 10-year tax concession is less attractive if its interpretation may change after three years. A startup visa is less useful if approvals are inconsistent. A digital strategy means little if companies cannot determine which agency controls implementation.

Governments do not need to promise that rules will never change.

They need to show that change will be explained, coordinated and introduced through a process companies can understand.

That commitment requires administrative discipline more than public spending.

As Southeast Asia competes for factories, data centres, venture capital and technology companies, growth will remain the first attraction.

Predictability will increasingly decide where investors stay.

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