On July 25, Defense Secretary Gilberto Teodoro Jr. ordered the Armed Forces of the Philippines to widen its Direct Commission Program (DICOM), fast-tracking cyber, AI, and engineering talent into commissioned officer roles. Defence spokesman Arsenio Andolong was blunt about the logic: some of the country’s best hackers are unemployed, and the state would rather channel that talent than lose it to cybercrime.

Most coverage stopped there — a recruitment story. That’s exactly why the real opportunity is still sitting open. Recruiting a few hundred officers doesn’t build or run a modern military’s cyber backbone. It’s a talent signal sitting atop an integration, training, and sustainment gap that no single Philippine agency can close alone — and one that almost no SEA integrator has priced into their pipeline yet.

The size of what’s actually up for grabs

DICOM sits within a much larger machine: the AFP’s Comprehensive Archipelagic Defence Concept and its Horizon 3 modernisation phase, which, for 2026, carries a defence budget of roughly ₱430 billion (US$7.08 billion), with tens of billions earmarked specifically for cyber and command-and-control systems.

Set against that budget is a workforce gap DICT itself has been flagging for years: roughly one cybersecurity professional for every 2,000–3,000 citizens, against a mature-economy benchmark near 1-in-200. Other estimates put unmet demand at around 180,000 professionals just to cover 10 per cent of critical institutions.

Put those two numbers side by side, and the gap is the opportunity: a ₱430-billion (US$7.08 billion) modernisation program with nowhere near the domestic technical bench to execute it, and almost no regional integrators actively positioned to fill that bench. This isn’t a crowded RFP market yet — it’s closer to whitespace.

Where DICT and CICC actually fit — and why most pitches miss half the buyer

Here’s the mistake most outside vendors make: they treat the AFP as the only buyer. It isn’t. The Philippines built a division of labor after the Cybercrime Prevention Act (RA 10175) and the law creating DICT (RA 10844): law enforcement (NBI, PNP-ACG), intelligence (NICA), national defence (DND/AFP, NSC), and — sitting in the middle — network protection, split across DICT and its attached agency, the Cybercrime Investigation and Coordinating Center (CICC).

• DICT is the policy author. It drafts the National Cybersecurity Plan and runs the NCERT and National Security Operations Centre, monitoring government networks and coordinating incident response. Pending legislation would require incidents touching critical infrastructure be reported to DICT/CICC — a compliance layer above any AFP-adjacent system.
• CICC is the coordination secretariat — and, by its own sector’s account, thinly staffed on the technical side. An agency chairing the National Cybercrime Inter-Agency Committee with almost no in-house bench is a market of its own.
• The overlap is a friction point competitors haven’t noticed. DICT’s own leadership has floated redirecting reformed hackers into civilian training — language nearly identical to DND’s pitch. Two agencies are quietly courting the same narrow talent pool, uncoordinated.

Also Read: Human-centric skills in the age of AI: How to never lose touch with humanity in the workplace

Vendors who only build a relationship with DND miss half the approval chain. That’s precisely why “zero competition” isn’t hyperbole — most firms aren’t even mapping the right buyers.

Eight concrete plays for SEA integrators — before this stops being whitespace

• Systems integration and interoperability layers — stitching legacy AFP comms, newly acquired foreign platforms, and DICT’s NCERT/NSOC feeds into one auditable architecture, instead of another siloed point solution.
• Managed detection and response for under-resourced agencies — CICC’s thin technical bench is a direct opening for outsourced SOC-as-a-service and incident-response retainers tied to existing reporting requirements.
• Workforce-scale training and certification pipelines — bootcamps and university partnerships, in the spirit of the UP–DICT microcredentials model, producing hundreds of vetted operators a year — not the handful DICOM can commission.
• Sovereign, auditable software builds — co-developed or locally-built detection, logging, and command-support tools that satisfy data-sovereignty and JV-ownership rules foreign closed-source vendors can’t.
• Multi-year sustainment contracts — maintenance and local technical support built in from day one, addressing the exact failure mode analysts cite in past hardware procurement.
• Compliance and reporting tooling — dashboards that help agencies meet the pending DICT/CICC critical-infrastructure incident-reporting mandate, a near-guaranteed procurement line once the legislation passes.
• AI-readiness and data-governance consulting — auditing data pipelines and setting decision-vs-flag guardrails before any model goes live, positioning integrators as foundation-builders, not platform-sellers.
• Regional threat-intelligence sharing infrastructure — tools that let the AFP participate in allied information-sharing (e.g., under the US–Philippines defence guidelines) without breaching data-localisation rules — a genuinely unmet niche.

Firms that check off two or three of these — not just pitch a single flagship platform — are the ones positioned to actually survive procurement cycles that move slower than the news.

Why the whitespace exists — and won’t stay open forever

The AFP’s own modernisation is still assembling itself in phases — Horizon 1 gave frigates and jets, Horizon 2 gave rocket systems and submarines — and analysts call the process piecemeal, project-by-project rather than unified. Few local firms have end-to-end integration experience at this scale. Commentators still point to the Jose Rizal-class frigate program as a cautionary tale of systems bought without maintenance planning — a risk cyber platforms carry just as heavily. That gap is real, but temporary: the government’s own legislative pipeline is working to close it.

The barriers that are keeping the field this empty

Ownership ceilings

Under RA 12024, foreign firms need a Filipino JV partner holding at least 60 per cent. RA 11647 lets the President block foreign investment in “strategic” cyber industries outright — exactly why most foreign players haven’t bothered.

Hardware-first procurement law

RA 10349 and RA 10055 were built around buying hardware, not software expertise. Pending bills would add a dedicated innovation office and capacity fund, but expect processes calibrated for frigates, not SaaS — for now.

Budget volatility

Of ₱90 billion (US$1.48 billion) proposed for 2026, only ₱40 billion (US$659 million) was firmly programmed; the rest depends on new revenue. In 2024, the Senate had to restore a ₱10-billion (US$165 million) cut to cyber-related projects. Structure contracts to survive a legislature that treats this funding as negotiable.

“Ghost project” scrutiny

The AFP has uncovered ghost projects within its own modernisation spending — treat that scrutiny as a filter favouring credible operators over opportunists.

Data localisation tension

Industry groups warn broad localisation mandates can isolate defenders from threat-sharing. Systems must satisfy sovereignty rules without severing allied intelligence-sharing under US-Philippines defence guidelines.

These barriers explain why the market stays thin. They’re not permission slips for foreign platform vendors — they’re a moat that favours integrators with a real local partnership and patience.

Also Read: The anti-hustle manifesto: Why being strategic beats being the best

Is anyone actually opposing this?

No official has publicly opposed the DICOM expansion itself. The friction is structural, not ideological:

• Congress has already cut cyber-related modernisation line items under budget pressure.
• Analysts have asked whether the AFP can compete on pay, warning the role could become a career “killer” for professionals used to private-sector terms.
• Internal audits surfacing ghost projects suggest caution about how loosely new cyber money should flow.
• DICT and DND are running parallel, uncoordinated outreach to the same small hacker population.

None of this is opposition — it’s a signal that execution, not intent, is the real battleground, and where a patient, credible integrator wins.

Where AI fits — and why sequencing matters

AI is an obvious accelerant for a talent-constrained cyber effort: threat detection, log analysis, anomaly detection, decision support. That’s a legitimate line item.

But this is a matter of national security, not just good practice: Filipino institutions need their own foundations — trained analysts, governed data pipelines, clear rules on what AI may decide versus flag, and homegrown audit capacity — before layering AI on top.

A system deployed without that foundation doesn’t just underperform; it can distort judgment and create dependency on foreign black boxes the country can’t independently verify in a crisis. Integrators leading with “buy our AI platform first” are pitching the wrong stage. Those who build talent, data discipline, and audit capacity first — in coordination with DICT’s NCERT/NSOC infrastructure and CICC’s coordination role, not around them — win the long-term contract.

The bottom line

This is a ₱430-billion (US$7.08 billion) modernisation program with a documented skills gap, two agencies quietly competing for the same talent pool, and a legal framework still built for buying hardware rather than software. That combination is precisely why competition is thin: most integrators saw a recruitment headline and moved on, without mapping DICT, CICC, the ownership rules, or the actual services gap underneath. The integrators who understand the full buyer chain, respect the procurement realities, and build local capacity before selling AI shortcuts have a genuine multi-year opportunity — and right now, remarkably little company.

This article synthesises public statements from the Department of National Defense, the AFP, DICT, CICC, the Philippine News Agency, and independent defence-policy analysis. It is a market and policy overview for technology integrators, not legal or investment advice.

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Every few decades, the global economy gets rewritten. We are living through one of those moments now. Tariff walls are going up between the world’s two largest economies. Supply chains that took thirty years to build are being unwound in real time. Capital that once flowed freely across borders is increasingly asking permission first. The language of “globalisation” has quietly given way to the language of “friend-shoring,” “de-risking”, and “strategic autonomy.”

For a region like Southeast Asia, comprising 11 countries, a population of over 680 million and GDP north of US$3.8 trillion, this fracturing is not an abstract geopolitical story. It is the operating environment where we build companies every day. 

And having spent the past decade running a hospitality business across Singapore, Indonesia, the Philippines, Vietnam and beyond through a global pandemic that nearly ended our business; a Thailand exit that felt catastrophic at the time; and now an expansion push into India and Australia, I have a fairly unsentimental view of where this region actually stands.

The world is splitting into blocs, SEA doesn’t have to pick one

The most consequential shift in the global economy right now is not a single tariff or a single election. It is the slow reorganisation of trade and capital into competing blocs — a US-aligned bloc, a China-centred bloc, and a shrinking pool of countries still trying to trade with everyone.

Southeast Asia’s structural advantage is that it has never had to choose, and largely still doesn’t. ASEAN’s intra-regional trade share sits at roughly a fifth of total trade, which sounds modest until you realise it means four-fifths of the region’s commerce still flows outward: to China, the US, the EU, Japan, India, the Gulf. That diversification, which used to look like a weakness (no single dominant trade relationship, no scale), now looks like the region’s best insurance policy against a world where picking the wrong side can be economically ruinous.

Foreign direct investment into the region has held up remarkably well precisely because of this hedge value. Manufacturers pursuing a “China+1” strategy have poured capital into Vietnam and Indonesia. Data centre and semiconductor investment has flowed into Malaysia and Singapore. 

None of this happened because Southeast Asia offered the cheapest labour or the biggest market. It happened because the region offered optionality at a time when optionality has become the scarcest resource in global business.

Also Read: Founders’ playbook: What it really takes to scale beyond Series A

What running hotels in emerging markets actually teaches you

I want to be honest about something: resilience is not a strategy slide. It is what’s left after you’ve made expensive mistakes and survived them.

Building RedDoorz across multiple Southeast Asian markets has reinforced one lesson above all others: resilience is not something you plan for on a strategy slide. It is built by continuously adapting to changing market conditions, regulatory environments, consumer behaviour and economic cycles.

The temptation during years of abundant capital was to believe that success in one market could simply be replicated elsewhere. Experience has taught us otherwise. Every market has its own dynamics, customer expectations and operating realities. Sustainable growth comes from understanding those nuances rather than assuming a single playbook fits all.

That lesson matters even more today. As the global economy becomes increasingly fragmented, businesses that remain flexible, disciplined and locally relevant will be far better positioned than those pursuing expansion based purely on scale.

Indonesia as the proof of concept

If there is one market that validates the thesis that domestic demand, not global trade flows, will carry Southeast Asia through this period of fragmentation, it is Indonesia. With a population of 280 million and a rapidly expanding middle class, Indonesia’s growth story has never depended on being the world’s factory floor or its financial hub. It depends on Indonesians spending money in Indonesia—on travel, retail, and services.

That is precisely the demand RedDoorz has built its business around, and it is why Indonesia continues to anchor our macroeconomic backdrop even as global trade gets noisier. Our customers are value-seeking domestic travellers, and our supply partners are independent hotel owners looking to formalise and grow. Both sides of that equation are local, self-reinforcing, and largely indifferent to what happens between Washington and Beijing. In a fracturing world, businesses anchored in domestic consumption, not cross-border trade, have the most durable ground to stand on.

Also Read: The 3Cs+1 framework: Navigating geopolitical fragmentation as a founder

Building optionality into the business

The same philosophy should shape how founders across the region think about their own next chapter. Rather than committing to a single geography or expansion path, the stronger position is building a flexible, multi-brand or multi-format platform that can pursue opportunities across Asia-Pacific as markets evolve.

Different markets require different propositions, customer segments and operating models. Our objective is not simply to grow a single brand, but to create an ecosystem of hospitality brands and capabilities that can adapt to local market conditions while leveraging shared technology, commercial expertise and operational scale. In an increasingly fragmented world, strategic flexibility is far more valuable than rigid expansion plans.

The same thinking also underpins our decision to pursue a listing on the Singapore Exchange. Singapore remains one of Asia’s most trusted financial centres, offering strong governance, regulatory certainty and access to long-term institutional capital. As geopolitical and economic uncertainty continues to reshape investment flows, we believe businesses will increasingly be valued not only for growth, but for resilience, credibility and the ability to execute across multiple markets.

The task ahead

The world is fragmenting into competing spheres of influence. Southeast Asia doesn’t need to choose one. Its greatest strength lies in remaining the region where ideas, capital, talent and trade continue to converge. In a world defined by uncertainty, optionality is the only real currency left—and Southeast Asia is uniquely positioned to create it. 

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

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

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A few years ago, when a company said it wanted a “Southeast Asia strategy”, the request usually sounded reassuringly straightforward. The business would establish a regional base in Singapore, identify a few priority markets, adapt its messaging slightly and begin expanding. The technology stack was often global, the strategy was usually designed at headquarters and Southeast Asia appeared on the slide as one neat, manageable region.

Then the actual conversations began. A message that worked in Singapore needed to be rethought for Malaysia. A customer assumption did not hold in Indonesia. A platform selected globally raised questions about data storage or regulatory compliance locally. A hiring plan that looked efficient on paper struggled against very different talent markets, salary expectations and working cultures.

This is the part of Southeast Asia that outsiders often underestimate. The region is connected, but it is not uniform. For a long time, that complexity was balanced by another advantage. Southeast Asia could remain economically connected to both the US-led and China-led worlds. Companies could access American technology, Chinese manufacturing, regional capital, global trade routes and a growing consumer base without every commercial decision being interpreted as a political choice.

That middle ground now feels less comfortable. Decisions about cloud providers, semiconductor supply chains, artificial intelligence systems, investors, data centres and technology partners increasingly carry geopolitical weight.

What once looked like a procurement decision can now affect market access, regulatory exposure and long-term strategic alignment. Yet I do not believe Southeast Asia’s future depends on preserving neutrality at all costs. Its real advantage was never neutrality. It was translation.

The region is too important to be treated as a corridor

Southeast Asia is often described as a bridge between larger economies. It is an understandable description, but it is becoming an insufficient one. ASEAN had a population of more than 684 million in 2024. Trade in goods reached approximately US$3.84 trillion, while trade in services stood at nearly US$1.29 trillion. These are not the numbers of a region whose main function is simply to connect other powers.

Investment tells a similar story. Foreign direct investment into ASEAN reached about US$231 billion in 2024. UNCTAD reported that the region remained the leading FDI recipient among developing regions, even as global investment weakened. Southeast Asia’s digital economy was projected to exceed US$300 billion in gross merchandise value in 2025, up from roughly US$40 billion a decade earlier. These figures matter because they change the question.

The question is no longer whether Southeast Asia can remain useful to both the US and China. The more important question is whether the region can turn its economic weight into capabilities, institutions and companies that are valuable in their own right. Being a convenient middle ground is helpful when the world is open and predictable. It is more fragile when larger powers begin asking partners, suppliers and markets to demonstrate where they stand.

Also Read: The localisation gap: Why multilingual AI isn’t enough for APAC markets

Translation is not the same as neutrality

In my own work across media, technology and regional communications, I often see the difference between a company that operates in Southeast Asia and one that actually understands it. The first brings a global strategy into the region. The second knows what must be translated. That translation might involve language, but it goes much further. It means understanding why trust is built differently across markets. It means recognising that regulation does not move at the same speed everywhere. It means knowing that a technology story framed around efficiency in one country may need to be framed around employment, accessibility or national capability in another. It also means accepting that “Southeast Asian consumers” are not one consumer group.

The region’s diversity is often described as a challenge. It is certainly not easy. But in a more fragmented global economy, the ability to operate across different political systems, commercial cultures and levels of development is itself a strategic capability. Companies that learn how to succeed here are forced to become better listeners. They must localise without losing scale, standardise without becoming rigid and build regional systems that leave room for local judgement. This is not passive neutrality. It is active adaptation.

The old regional playbook is already changing

Many organisations are not formally choosing between the US and China. They are doing something more practical. They are diversifying suppliers. They are reviewing where their data is stored. They are building separate technology or operational arrangements for different markets. They are asking more questions about vendor ownership, regulatory exposure and supply-chain resilience. They are also discovering that the cheapest or largest option is not always the safest long-term decision.

For years, regional strategy was often shaped by a relatively simple logic: select the biggest market, use the most established technology provider and consolidate operations wherever costs were lowest. The criteria are becoming more complicated.

Businesses now need to consider whether a system can satisfy multiple data regimes, whether a partner creates exposure to future export controls and whether a regional hub can continue serving every intended market if political conditions change. This creates additional cost and complexity. It can slow decisions that once appeared routine. But it may also produce better architecture.

A company that cannot depend on one supplier becomes more serious about interoperability. A business that must account for different regulatory environments becomes less careless about data governance. A regional team that can no longer copy and paste a global strategy is forced to build stronger local knowledge. Fragmentation is a burden, but it can also expose weaknesses that were previously hidden by convenience.

Also Read: The funnel was never neutral: What Asia’s markets reveal about Western marketing theory

Southeast Asia cannot localise its way out of every problem

There is, however, a limit to tactical adaptation. Local data centres, multiple vendors and market-specific campaigns may help companies manage immediate risks. They do not automatically give Southeast Asia a stronger position in the global economy.

The region still relies heavily on technologies, platforms and capital developed elsewhere. Many Southeast Asian markets remain better at adopting and implementing technology than creating the underlying systems that shape it. That is why the next source of regional advantage cannot simply be the ability to welcome everyone.

Southeast Asia must invest more seriously in its own research, talent, digital infrastructure and intellectual property. Regional companies need greater confidence to build for Southeast Asian realities first, rather than treating local markets as testing grounds for ideas developed elsewhere. There must also be more meaningful integration within the region itself.

It is difficult to speak about ASEAN as an independent economic force when businesses still face major differences in regulation, payments, talent mobility and digital standards from one country to another. The region does not need to become identical. Its diversity is part of its value. But stronger coordination would allow companies to scale within Southeast Asia before relying on distant markets for growth, capital or validation.

From connector to decision-maker

Southeast Asia will probably continue working with both the US and China. It should. The region’s relationships are too deep, its economies too interconnected and its development needs too varied for a simplistic choice between blocs. But staying connected to both sides is not the same as having a strategy. The narrowing middle ground is a threat when Southeast Asia is treated only as a market, manufacturing base or diplomatic buffer. It becomes an opportunity when the region uses this moment to build more of what it currently imports, strengthen ties within ASEAN and become more selective about the partnerships it accepts.

Perhaps Southeast Asia’s greatest advantage is that it has never had the luxury of believing in one universal playbook. Businesses here already know how to work across contradictions. They understand that what succeeds in one market may fail in the next. They know that relationships, regulations and consumer expectations cannot always be reduced to a regional spreadsheet. That knowledge is becoming more valuable as the rest of the world becomes less predictable. Southeast Asia may have less room to sit comfortably in the middle. But comfort was never the real advantage.

The real advantage is knowing how to operate when there is no single centre, no universal model and no easy answer.

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Investors often say they back exceptional founders and ambitious ideas. In practice, they also invest in the environment surrounding those companies.

When Airwallex, founded in Melbourne, made Singapore its global headquarters, the decision was about more than location. The city offered access to regional customers, a familiar regulatory environment and a deep pool of financial and technical talent.

The company later established San Francisco as a second global headquarters as it expanded in the United States, recruited engineers and strengthened its links to American investors.

The pattern is instructive. Airwallex positioned different parts of its organisation close to the resources they needed.

Venture capital may be invested in an individual company, but the company is rarely assessed in isolation. Investors also consider whether the surrounding ecosystem can provide employees, customers, advisers, follow-on funding and eventual buyers.

The startup is being assessed as part of a system.

Capital is more concentrated than ideas

Entrepreneurial ability is widely distributed. Venture funding is not.

Most global venture capital continues to flow towards a small number of established technology centres. Artificial intelligence has intensified this concentration, with enormous rounds going to companies that already sit close to major investors, research institutions, computing infrastructure and specialist talent.

This does not mean that the strongest ideas are produced in only a few cities.

It means investors are judging the probability that an idea can become a large, financeable and eventually liquid business.

A venture investment is usually described as a bet on a company. In reality, it is a chain of bets.

The founders must build the product, recruit the right people and persuade customers to adopt it. The company must survive mistakes, management departures and difficult funding conditions. It must then expand into larger markets, raise more capital and eventually produce an acquisition, public listing or another form of liquidity.

A strong ecosystem lowers the perceived risk at almost every stage.

Also Read: Southeast Asia in the 2026-2030 world order: Trade, chips, AI, and capital

Ecosystems make mistakes more survivable

Startups rarely develop according to plan.

Products change. Customer acquisition proves more expensive than expected. A senior employee leaves. Regulation intervenes. A prospective lead investor withdraws before a financing round closes.

In an established startup hub, the company may have several routes out of difficulty.

An investor may help recruit a replacement executive. Existing angels may provide bridge financing. A specialist lawyer may restructure the deal. A corporate partner may become a strategic investor or acquirer.

In a weaker ecosystem, the same setback can become terminal.

The difference is not that startups in mature ecosystems avoid mistakes. Their mistakes are more likely to be survivable.

This is one reason an investor may prefer a moderately promising company inside a functioning network over an apparently exceptional company operating alone.

The first has access to institutions, talent and relationships. The second may depend almost entirely on the continued performance and personal connections of its founders.

These advantages rarely appear in a pitch deck. Investors still price them.

Success leaves infrastructure behind

Startup ecosystems grow through repetition.

A company raises capital and hires employees. Some of those employees later launch businesses of their own. Founders who sell companies become angel investors. Early backers use successful returns to raise larger funds. Lawyers, recruiters and advisers develop specialist expertise through repeated transactions.

Each successful company leaves behind knowledge, capital and relationships.

This is why mature ecosystems are difficult to replicate. Governments can build innovation centres, launch public funds and subsidise accelerators. They cannot quickly reproduce decades of interaction among universities, technology companies, investors, professional advisers and experienced founders.

Silicon Valley remains the clearest example. Its advantage extends far beyond the amount of money managed by local venture firms. It comes from the constant movement of people and knowledge between established companies, startups and investment funds.

Singapore has developed a similar role within Southeast Asia, although on a smaller scale. Funds are managed there. Regional headquarters are established there. International deals are structured there. Investors are familiar with its legal and regulatory environment.

Capital attracts more capital because it leaves infrastructure behind.

Southeast Asia is not one startup market

Southeast Asia is often presented as a single growth opportunity. Its startup economy remains highly fragmented.

The region has a large population, growing digital markets and substantial technical talent. But differences in language, regulation, purchasing power and corporate behaviour make regional expansion difficult.

Singapore occupies a distinctive position.

Its domestic market is smaller than those of Indonesia, Vietnam, Thailand or the Philippines. Yet it provides many of the legal, financial and professional institutions through which investors fund companies operating across the region.

Also Read: AI is Vietnam’s new capital magnet

Vietnam offers a different proposition. Its appeal is linked to the scale and growth of its domestic economy, technical talent and the possibility that companies can build meaningful scale at home before expanding abroad.

Thailand has strong infrastructure, large corporations, sophisticated consumers and a substantial financial system. Yet its venture market remains limited relative to the size of its economy.

This reveals an important distinction.

A country can have abundant capital without providing much venture capital.

Banks generally assess borrowers through repayment capacity, established cash flows, credit history and collateral. Venture investors finance companies whose value depends largely on uncertain future growth.

A developed banking system does not automatically create a strong startup-financing system.

Investors think about exits early

Founders tend to focus on securing the next round. Venture investors must consider what happens several rounds later.

A fund’s returns depend on selling its stake through an acquisition, public listing or secondary transaction.

A market may produce many promising startups, but investors will remain cautious if it produces few credible exits.

The absence of liquidity weakens the entire ecosystem.

Fund managers struggle to demonstrate returns. Successful founders cannot easily recycle wealth into new companies. Employees receive limited benefit from equity compensation. International funds become reluctant to finance larger rounds.

The ecosystem may create businesses without completing the financial cycle required to sustain them.

This is why exits matter as much as startup formation.

A good product does not guarantee market access

The experience of DocDoc, a Singapore-based healthcare technology company, illustrates the problem.

Grace Park and her husband, Cole Sirucek, developed the business after their infant daughter was diagnosed with a rare liver condition. The experience exposed how difficult it was for patients to compare specialists and treatment options.

DocDoc built a platform designed to help patients identify appropriate care.

The problem was real. The product alone was not enough.

Commercialising it required relationships with insurers, hospitals and established healthcare institutions. In a regulated sector, those partnerships can determine whether a technically strong product reaches customers at all.

The same is true elsewhere.

A fintech company needs access to banks, regulators and payment networks. A biotechnology company needs laboratories, hospitals and specialist advisers. A climate technology business may depend on utilities, industrial partners and public procurement.

Investors evaluate these dependencies because a company lacking regulatory access or distribution partners may require more capital, take longer to expand and face fewer exit opportunities.

The idea may travel easily. The infrastructure required to scale it does not.

Also Read: Rewriting the rules: Southeast Asia as climate capital proving ground

Geography still shapes trust

Cloud computing and remote work have expanded the range of places from which companies can be built. They have not eliminated the importance of professional networks.

Venture capital depends heavily on information and trust.

Investors cannot assess every startup from first principles. They rely on referrals from founders, lawyers, accelerators, angels and other funds.

A referral does not guarantee funding, but it can determine which company receives serious consideration.

In a mature ecosystem, founders are more likely to be one introduction away from an investor, executive, customer or adviser who can solve an immediate problem.

Outside these centres, finding the right person and establishing credibility can take much longer.

The delays accumulate.

A competitor in a stronger ecosystem may raise capital faster, recruit earlier and reach customers before a company outside the network secures its first serious investor meeting.

Venture capital is an amplifier

Venture capital seldom creates an ecosystem from nothing.

More often, it accelerates places where talent, customers, capital and entrepreneurial experience have already begun to accumulate.

This explains why comparable startups can receive very different valuations and funding offers. The difference may say less about the quality of their ideas than about the strength of the machinery surrounding them.

Good ideas are widely distributed.

The systems capable of financing them, scaling them and returning capital to investors are much harder to build.

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

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

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

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The conversation around AI voice has changed dramatically over the past year.

Not long ago, businesses wanted to know whether AI could hold a natural conversation. Today, that question has largely been answered. Modern voice agents can qualify leads, schedule appointments, resolve customer enquiries, and handle a growing range of routine interactions with remarkable fluency.

At Agora, we’ve noticed a corresponding shift in customer conversations. Businesses are no longer asking whether voice AI works. Instead, they want to know how well it performs when deployed across different markets, languages, and customer segments.

Industry data points in the same direction. Gartner found that 85 per cent of customer service leaders plan to explore or pilot customer-facing conversational AI in 2025, with 44 per cent specifically evaluating voice AI as part of their customer experience strategy.

As adoption accelerates, we’ve found that two assumptions frequently shape deployment decisions. Both deserve a closer look.

Misconception #one: Strong English performance means AI is ready for APAC

Many of today’s leading voice models achieve impressive performance in English. Demonstrations often showcase smooth, natural conversations that make the technology feel ready for immediate deployment.

Real customer conversations, however, are rarely that predictable.

Across Asia Pacific, people naturally switch between languages depending on the context of the conversation. A customer may discuss payment details in Bahasa Indonesia before mentioning a product feature in English. A caller in Singapore may move between English and Mandarin without thinking twice. Across Thailand, Vietnam, Malaysia, and the Philippines, regional accents, local vocabulary, and conversational habits add further variation.

These aren’t edge cases. They are everyday interactions.

For AI systems, however, these communication patterns introduce additional complexity. Speech recognition must accurately identify different languages, preserve context as conversations shift, and correctly interpret customer intent despite changes in pronunciation, vocabulary, or sentence structure.

This is one reason speech recognition continues to evolve. While recent advances have dramatically improved accuracy, real-world deployments still need to account for multilingual conversations, regional accents, background noise, and inconsistent network conditions that rarely appear in benchmark evaluations.

Performance in English, therefore, should be viewed as the starting point rather than proof that a voice agent is ready for every APAC market.

Also Read: You’re waiting for everyone to agree: The hourglass doesn’t care

Misconception #two: Supporting multiple languages is the same as localisation

Once businesses recognise the diversity of APAC, the next instinct is often to prioritise multilingual support.

Supporting more languages is certainly important. But localisation involves much more than expanding a language menu.

Customers who speak the same language do not necessarily communicate in the same way. Regional expressions, industry terminology, pronunciation, and code-switching all influence how conversations unfold. A system that performs well in one market may require further adaptation before delivering the same experience in another.

Research from Microsoft reinforces this point. The company found that multilingual users naturally switch between languages during conversations and respond more positively to conversational AI that adapts to those shifts instead of remaining rigidly monolingual.

Customer expectations reinforce the need for localisation. According to CSA Research, 76 per cent of consumers prefer buying products with information in their own language, while 88 per cent of Indonesian consumers prefer content presented in Bahasa Indonesia. Although the study focused on digital content, the same principle applies to voice interactions. Customers expect communication to feel natural, not translated.

Ultimately, customers don’t evaluate AI based on the number of languages it supports. They evaluate whether the conversation feels effortless. If they have to repeat themselves, avoid certain phrases, or adjust the way they naturally speak, the interaction becomes less effective regardless of how sophisticated the underlying model may be.

What businesses are prioritising now

One of the most noticeable changes we’ve seen is how conversations with enterprise customers have evolved.

A year ago, many discussions centred on whether voice AI could realistically replace traditional IVR systems or automate routine enquiries. Today, those questions have become far more operational.

Businesses want to understand how quickly voice agents can be adapted for new markets, how they perform across multilingual contact centres, how they integrate with existing customer workflows, and how consistently they serve customers who communicate differently from one another.

That shift reflects the broader maturity of the market. Organisations are moving beyond experimentation and focusing on deployment quality. Success is no longer measured by whether a voice agent can complete a demonstration. It is measured by whether it can deliver a consistently positive customer experience across thousands of real conversations.

Also Read: What AI safety researchers actually worry about

The next competitive advantage won’t be better voices, it will be better understanding

As foundation models continue to improve, the gap in conversational quality between voice AI platforms is likely to narrow. Natural-sounding speech will increasingly become an expected capability rather than a differentiator.

The next competitive advantage will come from understanding customers more effectively.

For businesses operating across Asia Pacific, that means recognising that localisation is not simply another feature to enable before launch. It is becoming a core deployment strategy that determines whether AI creates friction or removes it.

The organisations that succeed with voice AI will not necessarily be those that automate the greatest number of calls. They will be those that build voice experiences around the realities of how their customers communicate, market by market, language by language, and conversation by conversation.

As AI phone calls become a standard part of customer engagement, understanding people may prove just as important as understanding speech.

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

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

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There’s a number that should reframe every stablecoin policy debate in the region, and it isn’t flattering. As of early 2026, the global stablecoin market is worth north of US$300 billion, and about 99.76 per cent of it is backed by the US dollar. Non-dollar coins, every euro, yen, ringgit and Singapore dollar experiment combined, split the remaining quarter of one per cent.

For two years, the region’s answer to that has been the same: write a better rulebook. Singapore built an open, multi-currency licensing regime under the Monetary Authority of Singapore and drew in issuers like StraitsX, Paxos and Circle. Malaysia is running the region’s most-watched ringgit stablecoin pilot, bank-anchored and Shariah-inclusive.

These are thoughtful pieces of policy, and the instinct behind them is right: digital money is becoming a question of sovereignty, and sovereignty is worth defending.

But a rulebook and a market are different things, and we keep confusing the two. That 99.76 per cent isn’t a gap in anyone’s licensing regime, but a verdict of sorts. Users, exchanges and treasurers have already chosen, and they chose the dollar, for its liquidity, its ubiquity across every wallet and venue, and the plain fact that it’s what everyone else is already holding.

You don’t legislate your way out of a network effect, and you can’t simply license a default into existence.

It’s worth looking at who set that default, because it wasn’t an accident. When the United States passed the GENIUS Act in July 2025, it did something the region should study closely. The law requires payment stablecoins to be fully backed one-to-one by dollar assets, which sounds like consumer protection and works like statecraft.

Every compliant token routes fresh demand into US Treasuries and widens foreign access to dollars. Washington understood that this contest isn’t won in the rulebook, it’s won in the reach. Whoever owns the default token exports their currency with it. China clearly agrees; it’s now drafting a yuan-stablecoin roadmap of its own. The big players are treating this as a distribution war. We’re treating it as a compliance exercise.

That’s the mismatch. A licence authorises a product; it doesn’t give anyone a reason to hold it. The best-regulated ringgit stablecoin in the world still has to compete against a dollar token that’s already in every wallet, already trusted, already the path of least resistance. In fintech circles, you hear the market’s indifference described, very politely, as “user preference for usability,” which is just a nice way of saying nobody cares where a coin was issued. Sovereignty on paper isn’t sovereignty in wallets, and no amount of regulatory craft closes that gap on its own.

The fair objection is that retail adoption may be beside the point. Maybe local-currency stablecoins aren’t built for consumers at all, but for business, cross-border settlement, remittances, corridor flows where banking relationships and regulation matter more than what sits in a shopper’s phone.

Also Read: Japan shows how non-USD stablecoins complement USDC and USDT

It’s a reasonable argument, and it’s partly true. But it doesn’t rescue the licensing-first strategy; it just moves the same problem upstream. The dollar’s incumbency in settlement is exactly the thing a regional coin has to dislodge, and incumbents don’t fall to frameworks. Retail or wholesale, it’s a battle for the default, and defaults are won on reasons to switch, not rules to comply with.

Here’s where the region’s real advantage has been hiding in plain sight, and where I think a marketer reads this problem differently than a regulator does. Southeast Asia doesn’t lack rails or rulebooks.

What it has, that almost no one else does, is distribution it already owns, the wallets and QR systems hundreds of millions of people open every day without thinking, from QRIS to PromptPay to the super apps that have quietly become default infrastructure. That’s the asset.

A local-currency stablecoin embedded as the native rail inside systems people already trust isn’t asking anyone to make a patriotic choice; it’s making the local option the easy one. Add corridors where a regional coin is genuinely cheaper and faster than a dollar round-trip, and you start giving people, retail and treasury alike, a concrete reason to switch that a licence never could.

None of this means the frameworks were wasted. They’re the floor. But a floor isn’t a strategy, and we’ve been mistaking one for the other, polishing the rules for money that keeps flowing in someone else’s currency. The awkward part is that the licensing is the easy bit. The hard part, the part that actually decides sovereignty, is distribution and trust. And that’s the part nobody’s resourcing.

Also Read: Taiwan’s stablecoin moment: Why the NTD could outshine the dollar

So the question isn’t whether the region can regulate stablecoins well. It plainly can. The question is whether it intends to contest the default itself, to fight for the thing people reach for first, or keep drafting careful rules while the digital dollar wins by simply being everywhere it already is.

On the present course, we’re reacting to a standard the dollar set and the GENIUS Act is now actively defending. Being part of rewriting the rules means fighting a battle that a rulebook, on its own, was never going to win.

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

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

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For years, artificial intelligence in games has mostly meant enemies that chase, dodge or shoot with varying degrees of believability. Razer and the National University of Singapore now want to push that idea into more demanding territory: AI systems that understand context, adapt in real time and eventually behave less like scripted software and more like responsive companions inside digital worlds.

The gaming hardware and software company has partnered with NUS Computing to establish the Razer-NUS Joint AI Research Lab, a Singapore-based research initiative focused on AI for gaming across hardware, software and services. The lab will be hosted on the NUS campus and will bring academic research closer to Razer’s product and engineering teams.

Also Read: AI in gaming: How Southeast Asia became the testing ground for virtual companions

The collaboration comes as gaming companies globally are trying to work out what generative AI and adaptive models can usefully do beyond producing concept art, dialogue or non-playable character chatter. For Southeast Asia, where Singapore has been positioning itself as a regional hub for AI research, game development and digital talent, the lab is also a sign that gaming is being treated less as a niche entertainment category and more as a serious testbed for real-time AI systems.

Razer, which is dual-headquartered in Irvine, California and Singapore, already operates AI Centres of Excellence in Singapore and France. The company says its AI lab network now includes close to 100 AI researchers, data scientists and engineers. The new NUS partnership is designed to add a more research-heavy layer to that ecosystem.

Why gaming is a hard AI problem

At the centre of the partnership is a research area Razer and NUS are calling Gaming Artificial Narrow Intelligence, or GANI. In plain terms, this refers to AI models built specifically for interactive digital environments rather than broad, general-purpose systems.

That distinction matters. Games are not static documents or one-way media. A model deployed inside a game must respond instantly to a player’s movement, strategy, skill level and decisions. It must also work within the technical constraints of live gameplay, where lag or awkward behaviour can quickly ruin immersion.

Razer and NUS say GANI could eventually power AI teammates that adjust tactics to a player’s style, generate objectives and dialogue in real time, and change difficulty during live matches. If done well, such systems could make games feel less repetitive and more personal. If done poorly, they could create unfair, unpredictable or intrusive experiences.

“Gaming presents some of the most demanding environments for AI, requiring systems to respond in real time, adapt to changing contexts, and enhance the player experience,” said Li-Meng Lee, Chief Strategy Officer at Razer. He added that breakthroughs in this area could also be relevant to education, simulation and other real-time digital experiences.

That wider applicability is an important part of the story. AI that can operate smoothly in a fast-paced multiplayer game may also be useful in training simulations, virtual classrooms, industrial interfaces or digital assistants that need to react to changing human behaviour.

From lab work to products

The Razer-NUS Joint AI Research Lab will focus on three areas: core model innovation, real-time content systems and advanced personalisation. The two partners plan to test research in both simulated and live gameplay environments, with successful outcomes potentially integrated into Razer’s proprietary systems.

Also Read: AI and the rise of gaming entrepreneurs

NUS Computing will lead research and talent development, while Razer will provide industry use cases, engineering access and commercialisation pathways. Associate Professor Ooi Wei Tsang from NUS Computing’s Department of Computer Science will serve as Director of the joint lab.

“Universities play a crucial role in advancing scientific discovery and shaping the evolution of emerging disciplines,” said Ooi. He said the partnership gives GANI “a dynamic testing ground” by combining NUS’s AI research strengths with access to Razer’s live engineering environment.

For Razer, the lab also supports ongoing AI projects such as Razer AVA and Project Motoko. AVA is the company’s concept for a digital human companion that can offer personalised interactions through memory, personality, contextual awareness and adaptive behaviour. Project Motoko is a wearable AI headset intended to bring multimodal generative AI into an everyday form factor.

Both ideas remain ambitious. Digital companions have often struggled with trust, usefulness and emotional authenticity, while wearable AI devices have faced questions around privacy, battery life and whether consumers truly want another always-on device. The research lab could help Razer test these assumptions before they become mass-market products.

The Southeast Asian angle

Singapore has been steadily building its position as Southeast Asia’s AI nerve centre, backed by state funding, university research, enterprise adoption and multinational technology partnerships. NUS, in particular, has become a key node in this strategy, with its School of Computing working across AI, cybersecurity, data science and digital trust.

The Razer-NUS lab fits neatly into that broader national agenda. Unlike pure software AI startups, gaming sits at the intersection of chips, devices, cloud infrastructure, creative production and consumer behaviour. That makes it a useful sector for training technical talent and spinning out applied research.

Southeast Asia also has a large and young gaming population, even if much of the region’s game development activity remains fragmented. Mobile gaming dominates markets such as Indonesia, the Philippines, Vietnam and Thailand, while Singapore has served as a regional base for publishers, esports organisers and technology firms. If AI can reduce content production costs or help smaller studios build richer game worlds, the impact could extend beyond Razer’s own ecosystem.

Still, the commercial upside will depend on whether research can be translated into tools that developers actually use. Game studios are cautious about technology that adds complexity to production pipelines or creates unpredictable player experiences. AI features must improve gameplay, not simply signal that a company is keeping up with the latest trend.

A crowded field

Razer is not the only company trying to define the future of AI in gaming. NVIDIA has been pushing AI-powered game characters through its ACE technology, while Microsoft has explored AI tools across Xbox, cloud gaming and developer workflows. Sony, Tencent and NetEase all have deep gaming interests and the resources to experiment with AI at scale.

On the software side, Unity and Epic Games are building AI capabilities for developers, while startups such as Inworld AI focus on AI characters and interactive storytelling.

Razer’s traditional rivals in gaming hardware, including Logitech G, Corsair, SteelSeries and ASUS ROG, are also exploring ways to make peripherals and gaming systems more intelligent. The difference is that Razer is trying to connect hardware, software, services and AI research under one umbrella. Whether that becomes a defensible advantage will depend on execution rather than lab announcements.

The market backdrop is attractive. The global AI in gaming market is projected to grow from US$4.2 billion in 2025 to US$66.8 billion by 2035, representing a 32 per cent compound annual growth rate. A recent survey cited by Razer found that 79 per cent of gamers are receptive to at least one AI-enabled feature they believe would improve their experience.

Those numbers explain why companies are moving quickly. But gaming audiences can be unforgiving. Players tend to welcome AI when it makes games more immersive, responsive or fair. They reject it when it feels like a shortcut, a gimmick or a way to replace human creativity.

Also Read: Gaming as the next social network: How Gen Z and Gen Alpha are redefining digital belonging

For Razer and NUS, the opportunity is to show that AI in gaming can be more than automated content generation. If GANI can produce systems that understand players without overwhelming them, Singapore could become an important base for a new category of interactive AI research.

The harder task now is proving that intelligence built in the lab can survive contact with real players.

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In the second week of August 2009, four months into my first job as an R&D engineer at a pulp and paper plant in Riau, I told my supervisor I was leaving to join a bank. I was 23. I had spent four years studying chemical engineering, graduated at the top of my department, and worked my way into the bleaching process team at one of the country’s largest paper producers. I had also concluded that what I wanted to do for the next four decades was sit on the other side of how risk moves through systems, and that finance was where that work lived.

My supervisor told me, more politely than I deserved, that I was making a mistake.

I am now 15 years into a risk career that has run through three banks, an insurer, and eventually my own company. In every one of those seats, the skills I have leaned on hardest were not the ones I picked up in business school or in risk certification cycles. They were the ones I learned in a chemical engineering lab in North Sumatra.

This is not a coincidence. The principles that govern how chemical plants work happen to be the same principles that govern how financial systems work. The finance industry, by and large, has not noticed.

What I did not know I was learning

The chemical engineering curriculum I went through at Universitas Sumatera Utara was, on the surface, about reactors, separation processes, mass transfer, and process control. What it actually trained was a way of seeing systems.

The discipline forces you to think in terms of inputs, outputs, transformations, and constraints. Nothing inside a chemical process is allowed to be vague. If you do not know where a stream goes, you do not understand the plant. If you cannot predict how the system will behave when one variable changes, you cannot operate it safely. The mental habit this builds, the refusal to leave any part of a system unaccounted for, turns out to be the same habit you need to run a risk function inside a bank.

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

Three principles that transferred

Three things in particular have stayed with me, and have shaped every risk decision I have made since.

Mass balance. In a chemical process, every kilogram of material in must equal every kilogram out, less what is accumulated or transformed inside the system. There are no unexplained gaps. The reflex this builds, that an unbalanced ledger is a mis-measurement, not a mystery, is the same reflex that catches operational losses, fraud patterns, and capital gaps inside a bank. A risk officer who instinctively believes that what comes out of a system must equal what went in, less what was retained, asks the right questions almost without thinking.

Process control and feedback. In a well-designed chemical process, the system measures itself continuously and adjusts in real time. The temperature drifts above the setpoint, a valve closes. The pressure spikes, a relief opens. There is no quarterly review committee. The system corrects, or it ruptures. This way of thinking about feedback, small adjustments made continuously against a known boundary, is exactly what most financial risk frameworks still do not do. They review periodically. They escalate sporadically. They operate, in engineering terms, like a reactor with no instrumentation.

Failure mode and effects analysis. Before any chemical plant goes live, the engineering team systematically maps every way the process can fail, ranks the failure modes by likelihood and consequence, and designs the controls before the failure happens. The discipline of asking “what would have to be true for this to go badly?”, not as anxiety, but as method, is the single most useful habit I brought into risk management. Most of the loss events I have seen across two decades were predictable inside a competent failure analysis. Most of them did not have one.

Where the finance training falls short

Finance has its own analytical apparatus. Modigliani-Miller, Black-Scholes, value-at-risk, the architecture of modern asset pricing. These are powerful tools inside the assumptions they were built for. Outside those assumptions, they are quieter than their reputations suggest.

The gap I have noticed, across many years of working with both engineers who entered finance and finance professionals who stayed in finance, is this. The engineer asks first: what could break this system, and what would be true if it did? The finance professional asks first: what is the expected outcome, and what is the variance around it? Both questions matter. But in a crisis, and risk management is the discipline of crises, the engineer’s question is the one that saves the institution.

Also Read: How do you finance a first nuclear reactor for a data centre? The deal structure is finally coming together

What this means for anyone choosing a non-traditional path

I get asked, perhaps once a month, by an engineering student whether they should leave technical work for finance, strategy, or consulting. My answer has become consistent.

The pivot is not the question. The skills you have built in engineering are some of the most transferable skills any discipline produces. You can move into finance, and your engineering training will quietly do half the work of your new role. The question is whether you are leaving for the right reason, because the systems you want to understand are now financial systems, not chemical ones, or because you think the new field will be more glamorous than the one you trained in.

If it is the first reason, the move is sound. If it is the second, no field will deliver what you are hoping for.

I do not draw flowsheets on whiteboards. I do not solve heat transfer equations. But the way I think about risk, about systems, balances, feedbacks, failures, was shaped by four years at USU and four months in Riau before I ever opened a banking textbook. 15 years later, that training is still doing more of the work than anything I learned afterwards.

The most useful risk management education I have ever received was a chemical engineering degree. It just took me a decade to fully realise it.

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

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

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A great deal of bad strategy begins with a comforting number.

Market share is one of the most over-trusted measures in business because it looks like proof of strength while often revealing very little about actual control. It tells you how much of the market you currently touch. It does not tell you who sets the terms, who shapes behaviour, who captures the best economics, who sees demand first, who becomes hard to route around, or who gets stronger when everyone else grows.

That distinction matters more than most leadership teams admit.

A company can have impressive market share and still be structurally weak. It may be large but replaceable. It may serve many customers without controlling any decisive part of the system. It may be visible in the market but absent from the points where pricing power, dependency, switching cost, regulatory comfort, workflow design, or standards actually get determined. In that situation, share creates exposure more than power. The company has more revenue to defend, more cost to carry, and more surface area to lose.

Power comes from something else.

Power comes from control points.

By control points, I mean the parts of a market that others must pass through, design around, conform to, or receive permission from. These are the places where choice narrows, dependence increases, economics concentrate, and leverage becomes durable. Control points are not always the biggest part of the value chain. In many markets they are the smallest visible layer and the most important strategic position.

Market share measures presence, control points determine terms

This is the first distinction serious strategists need to make.

Market share answers the question, how much of the market do we currently serve? Control points answer a much more important question: under what conditions does the market operate, and how much influence do we have over those conditions?

That is a harder question because it forces leaders to examine where actual leverage sits. Does the company control distribution? Does it control customer identity? Does it control switching friction? Does it control access to demand? Does it control compliance interpretation? Does it control the data that trains the system, validates performance, or proves value? Does it control the workflow where alternatives become painful? Does it control the commercial mechanism through which everyone else gets paid?

These are very different positions from simply being widely used.

Also Read: AI-powered business automation: How SMEs are transforming operations in Southeast Asia

The real contest in markets is usually over choke points, not customers

We often describe competition as a fight for customers, but that is usually only the surface-level view. Underneath that visible contest is another one. Companies are competing to own the choke points that shape how customers are acquired, how products are integrated, how risk is managed, how spending is justified, and how alternatives are compared.

This is where strategic thinking gets more interesting.

A control point may sit in onboarding, where identity and trust are established. It may sit in the workflow, where staff do not want to relearn behaviour. It may sit in the reporting layer, where leadership sees value and performance. It may sit in compliance, where approval becomes easier for one route than another. It may sit in the commercial structure, where procurement can buy one thing cleanly but struggles to buy the alternative. It may sit in data custody, where the history required for tuning, insight, and continuity quietly accumulates in one place.

None of these is glamorous in the way market share is glamorous. But they are often far more consequential.

Control points are often hidden inside boring functions

One reason leaders miss control points is that they expect power to sit in obvious places. They look for power in brand visibility, revenue scale, installed base, or category leadership. They do not always notice that durable influence is often buried in functions that appear mundane.

Billing can be a control point. Identity can be a control point. Audit records can be a control point. Procurement approval paths can be a control point. Data lineage can be a control point. Technical certification can be a control point. Distribution rights can be a control point. Default settings can be a control point. Even complaint handling can become a control point if it determines who the institution trusts when something goes wrong.

These positions rarely get celebrated in market narratives because they are not as exciting as product innovation or growth curves. Yet they are often where strategic reality lives.

A company that owns a boring control point can quietly become impossible to displace. Everyone else may appear more dynamic, more loved, or more talked about. But when the market has to choose under pressure, the firm sitting inside the operational necessity tends to win.

Also Read: Why AI-empowered teams are getting smaller, and why that is harder than it sounds

The most valuable control point is often the one that feels legitimate

Not every choke point becomes durable power. Some create resistance, regulatory backlash, or market workarounds. The most defensible control points are usually the ones that feel justified by the system rather than artificially imposed on it.

This matters a great deal.

A control point lasts when participants accept that it serves a real function. It reduces uncertainty. It simplifies coordination. It lowers risk. It improves trust. It makes the system easier to govern. It creates a common language for decision-making. It becomes part of how the market keeps itself stable.

This is why legitimacy matters more than mere friction.

An artificial barrier can generate temporary leverage, but a legitimate control point generates embedded authority. Participants may not love it, but they recognise that the market works better with it than without it. Once that happens, the control point stops feeling like an advantage and starts feeling like infrastructure.

That is when strategy becomes hard to attack.

Strategy is not only about getting chosen, it is about becoming hard to route around

That is the deeper idea underneath this whole argument.

Many strategies are built around being selected again and again. That is fine in open competition, but it is exhausting and fragile if every decision resets the contest from the beginning. Truly strong strategic positions do something else. They reduce the frequency with which choice is genuinely reopened.

This does not always mean lock-in in the crude sense. It can mean being embedded in the reporting layer where value is measured. It can mean being the trusted source of operational truth. It can mean becoming the easiest path through governance. It can mean owning the transition cost. It can mean sitting where multiple parties coordinate. It can mean controlling the evidence required to compare alternatives fairly. It can mean becoming the familiar answer in moments of uncertainty.

These are all forms of route control.

Once a firm occupies that place, competitors may still exist, customers may still express dissatisfaction, and market share may still move at the edges. But the company remains difficult to route around because it has become part of the operating logic of the system itself.

That is much closer to power than popularity ever is.

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