Singapore-based blockchain startup Startale Group has closed a US$63 million Series A funding round, led by a US$50 million injection from financial powerhouse SBI Group, with an additional US$13 million from Sony Innovation Fund.

The capital raise marks a significant leap for Startale’s ambitions to transform Asia’s on-chain capital markets and push the boundaries of blockchain adoption beyond niche use cases.

Also Read: Stablecoins are becoming ‘dollars as a service’ for emerging markets

At its core, Startale builds infrastructure and applications that bring traditional financial assets and services onto the blockchain, creating seamless tokenised securities trading, stablecoin payments, and consumer-facing blockchain solutions. The company is co-developing Strium, a Layer 1 blockchain platform tailored for institutional investors to trade tokenised securities and real-world assets (RWA) around the clock.

Meanwhile, Startale’s native stablecoins—JPYSC, pegged to the Japanese yen, and USDSC, tied to the US dollar—are central to providing smooth fiat-to-crypto gateways alongside innovative features such as onchain dividend and yield distribution.

The latest funding round solidifies Startale’s strategy to vertically integrate blockchain infrastructure, financial ecosystems, and consumer applications into a comprehensive stack. This is particularly critical in Asia, where the complexity of legacy systems and regulatory fragmentation have hindered blockchain’s broader adoption in finance.

SBI Group’s involvement is not new; it has been a strategic partner since 2025, working alongside Startale to co-create core products, including Strium and JPYSC. With over 80 million customers across securities, banking, and insurance, SBI’s confidence in Startale reflects the startup’s ability to deliver institutional-grade financial products on-chain at scale, promising a radical overhaul of how banking and securities operate in the digital era.

Yoshitaka Kitao, SBI Group’s Chairman and CEO, summarised the partnership’s potential succinctly: “By joining the SBI Group’s digital space ecosystem, I am confident we can accelerate the on-chain transformation of society and demonstrate a strong competitive advantage by driving a vertical integration strategy in the digital finance sector.”

Also Read: How stablecoins are quietly reinventing the global dollar system

The growing adoption of stablecoins in Japan provides fertile ground for Startale’s ambitions. Japan’s regulatory environment has evolved to accommodate stablecoins, with growing institutional interest and consumer adoption driven by the need for faster, cheaper, and more transparent cross-border payments and settlements. The trust bank-backed JPYSC stablecoin is Japan’s first of its kind, offering greater legal certainty and security than many other stablecoins. This regulatory clarity, combined with the burgeoning demand for digital financial products, is rapidly accelerating Japan’s stablecoin ecosystem.

Startale intends to expand the adoption of JPYSC and USDSC across retail, enterprise, and institutional users. Their utility extends beyond simple payment instruments, providing functionalities such as automatic distribution of on-chain dividends and yields, integrating traditional finance’s value propositions with blockchain’s efficiencies.

In parallel, Startale is scaling Strium as an institutional-grade settlement and exchange framework for Asia’s trading of tokenised securities and real-world assets (RWA). This platform promises to enable 24/7 trading and real-time settlements, significantly enhancing liquidity and transparency compared to traditional markets tethered to business hours and manual reconciliation processes.

On the consumer front, Startale’s SuperApp platform is designed to abstract blockchain complexity behind a sleek interface that combines asset management, social features, payments, and “mini apps.” This unified experience aims to onboard millions of users to on-chain finance and the broader blockchain economy, further accelerating mainstream adoption.

This Series A round is also a testament to the growing convergence between finance, entertainment, and blockchain technology in Asia. Startale is building on partnerships with Sony that explore novel ways to integrate entertainment content and blockchain applications, carving out new user experiences and monetisation models.

Also Read: How stablecoins are disrupting traditional financial systems

For Southeast Asia, a region ramping up blockchain adoption amid diverse regulatory frameworks and vibrant fintech ecosystems, the rise of companies like Startale signals a maturing market infrastructure. Providing scalable, compliant blockchain solutions that bridge traditional finance and on-chain systems will be crucial to driving regional digital economy growth.

By weaving together infrastructure, stablecoins, institutional offerings, and consumer applications, Startale is strategically positioning itself as a cornerstone in the emerging on-chain financial landscape. The Series A funding not only validates this approach but also injects the firepower needed to execute aggressive growth plans.

In short, Startale’s ability to deliver on-chain financial products at an institutional scale could redefine banking, securities, and financial services in Asia. The move towards tokenisation and stablecoin-driven ecosystems has the potential to drastically cut costs, speed up transactions, and open new avenues for investment and consumer engagement—ushering in a new era of digital finance.

Also Read: How SMEs are using stablecoins to beat currency swings

With the support of SBI Group and Sony, and Japan’s expanding stablecoin market, Startale is primed to lead Asia’s on-chain revolution.

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Supply chain cyberattacks are no longer a niche concern reserved for multinationals with sprawling vendor networks. They are becoming a routine business risk, and Southeast Asia is entering that reality while still short of security talent, uneven in basic cyber hygiene and heavily dependent on third-party technology providers.

That is the clearest takeaway from a new Kaspersky-commissioned survey of 1,714 enterprise IT and security decision-makers across 16 countries, including Singapore, Vietnam, India, Indonesia, and China.

Also Read: Digital Growth, fragile defences: Inside Philippines’s cybersecurity gap

The headline finding is stark: one in three organisations globally said they had been hit by a supply chain attack in the past year. Yet many still lack the people, internal discipline, and contractual leverage needed to deal with the problem.

Talent shortages and operational overload are compounding risk

Globally, 42 per cent of respondents said the shortage of qualified IT security workers was a major barrier to reducing supply chain and trusted relationship risks. The same share said organisations are struggling to prioritise among too many security tasks, leaving third-party risk management exposed.

That lands uncomfortably well in Southeast Asia, where businesses have spent the past decade digitising operations, moving workloads into the cloud, integrating payments and logistics systems, and stitching together regional expansion plans with software from dozens of external partners. Every API, contractor platform, cloud dashboard, and outsourced IT function expands the attack surface. And in many companies, especially those scaling quickly, vendor risk management has not kept up.

The Kaspersky data shows just how uneven the region has become. In APAC markets covered by the study, the share of organisations citing a lack of qualified IT security staff ranged from 34 per cent in Singapore to 57 per cent in Vietnam. Those figures suggest the issue is not limited to less mature digital economies. Even Singapore, Southeast Asia’s most developed technology and regulatory hub, is still wrestling with capacity constraints.

The difference is that in places such as Vietnam, the talent gap appears more acute, while in Singapore the problem is increasingly one of overload. Nearly half of respondents in Singapore, or 47 per cent, said they were juggling multiple cybersecurity priorities. In Vietnam, that figure stood at 48 per cent. India was even higher at 54 per cent.

That matters because supply chain security is rarely urgent until something breaks. Security teams tend to focus first on patching internal systems, responding to active incidents, dealing with audits and meeting compliance demands. The slower, messier work of assessing vendors, reviewing contractor access, updating third-party clauses and validating partners’ controls often gets pushed down the list. Attackers count on exactly that.

Weak governance and trust-based relationships create hidden vulnerabilities

This pattern has been visible in major breaches over the past few years. The SolarWinds compromise showed how malicious code inserted upstream can cascade across customer networks. The MOVEit attacks demonstrated how a single exploited third-party tool can expose multiple downstream victims.

Also Read: The founder’s blind spot: The security question you must answer before growth

Southeast Asian firms were not always named as primary targets in those cases, but the region’s businesses are deeply embedded in the same global software and services supply chains. They do not need to be the original target to suffer the fallout.

What makes the current moment especially risky for Southeast Asia is the region’s uneven cyber maturity. Large enterprises and regulated sectors such as banking and telecoms have generally improved their internal controls. But supply chain security depends on the weakest link across a broader ecosystem that includes software vendors, contractors, managed service providers, logistics partners, outsourced development teams and small suppliers.

The survey suggests many of those relationships are still governed too loosely. Across APAC markets, between 30 per cent and 61 per cent of respondents said their contracts did not include IT security obligations for contractors. Between 25 per cent and 38 per cent said non-IT staff did not fully understand supply chain and trusted relationship risks.

Those are not small operational gaps. They point to a deeper governance problem: cybersecurity remains too often confined to technical teams, while procurement, legal, finance and operations continue to sign or manage vendor relationships without strong, enforceable security baselines. In high-growth companies, especially across Southeast Asia’s startup and mid-market segments, that is a familiar weakness. Vendor onboarding is usually optimised for speed, cost and functionality — not for resilience.

Malaysia offers a useful illustration of the structural challenge. The country is trying to strengthen its cyber capability under the Malaysia Cyber Security Strategy 2025-2030, but the labour pipeline remains under pressure. The Ministry of Digital has projected that Malaysia will need 28,068 cybersecurity professionals by 2026, while earlier estimates placed the existing workforce at roughly 16,765. That gap helps explain why many organisations struggle to continuously monitor third-party exposures even when they know the risks are real.

Even basic cybersecurity practices remain inconsistent

The confidence problem is just as telling. Globally, 85 per cent of businesses said they need to improve protection against supply chain and trusted relationship risks. Only 15 per cent considered their current measures effective.

Also Read: Why AI security demands a different playbook in Asia

In APAC, confidence varied sharply. India, Indonesia and Singapore reported low confidence levels of 11 per cent, 14 per cent and 14 per cent respectively. Vietnam came in at 21 per cent, while China stood out at 34 per cent. That spread may reflect real differences in preparedness, but it may also reflect differences in perception. Either way, low confidence in Singapore and Indonesia is significant. These are markets with growing digital economies, dense vendor ecosystems and rising exposure to cloud and software dependencies.

One especially revealing finding concerns two-factor authentication. It was the most common protective measure identified in the survey, yet adoption remained patchy. Singapore stood out for the wrong reason, with an adoption rate of just 28 per cent. Other APAC markets reported rates above 35 per cent, but still below the global average.

For a region that often presents itself as digitally ambitious, weak uptake of such a basic safeguard is hard to ignore. Two-factor authentication is not a silver bullet, but low adoption suggests that even foundational controls are not being applied consistently across partner relationships. That is often where attackers find room to manoeuvre: not through sophisticated zero-day exploits alone, but through ordinary lapses in identity management, access control and vendor oversight.

Sergey Soldatov, Head of Security Operations Centre at Kaspersky, put the problem plainly: “When security teams are overstretched, understaffed and have to prioritise urgent tasks over long-term resilience priorities, organisations are left exposed to threats that can move silently through their provider ecosystem.”

A fast-growing digital economy built on fragile foundations

That assessment lines up with how many security incidents now unfold. Rather than battering down the front door, attackers compromise a supplier, abuse a trusted connection, hijack credentials or exploit neglected third-party software. The result is the same: businesses inherit risk from partners they depend on but do not fully control.

There is one encouraging signal in the survey, though it comes with a catch. Companies that had already experienced supply chain or trusted relationship attacks were more likely to adopt stronger security practices afterwards. Victims of supply chain incidents were more likely to request penetration test results from suppliers, while organisations hit by trusted relationship breaches more often checked for compliance with industry standards and their contractors’ own supply chain policies.

In other words, some firms are learning — but mostly after taking a hit.
That is a costly way to mature, particularly in Southeast Asia, where digital trust is becoming a competitive issue as much as a technical one. Financial services, healthcare, logistics, e-commerce and manufacturing all depend on interconnected systems and outsourced capabilities. A weak vendor risk posture no longer threatens only internal operations; it can disrupt customer experience, trigger regulatory scrutiny and damage expansion plans across borders.

For startups and growth-stage companies, the message is even sharper. Supply chain security is not just a big-enterprise compliance chore. The moment a company plugs into payment gateways, cloud infrastructure, SaaS tools, outsourced developers or regional fulfilment networks, it becomes part of someone else’s attack path.

Also Read: Cybersecurity has a prioritisation problem, and Hackuity wants to fix it

The survey itself should be read with the usual caution attached to vendor-sponsored research. But its core finding is difficult to dismiss. Southeast Asia’s supply chain cyber problem is not simply about technology gaps. It is about a region moving fast on digital transformation while still underinvested in cyber talent, inconsistent in basic controls and too willing to trust third parties without demanding proof.

That combination is exactly what attackers prefer: fast growth, fragmented oversight and plenty of invisible dependencies.

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Deep learning, a part of machine learning, simulates the processes of the human brain to solve complex tasks with neural networks. Though it drives everything from fraud detection to supply chain prediction, implementing deep learning in enterprise environments is a game altogether. 

Unlike research or laboratory settings, companies must deal with operational constraints, regulatory concerns, and the demand for ROI. That’s where the real challenge begins. 

Some of the challenges of deep learning are: 

• Data quality and quantity

Deep learning is fuelled by huge, high-quality data sets. Enterprise data, however, whether customer files and transaction logs or sensor data and email, is dirty, siloed, and in short supply. Thus, enterprise data rarely amounts to AI-ready. 

Labelling data at scale is also slow and expensive. When you throw in data privacy laws (like GDPR or HIPAA), it’s easy to see why getting the best training data is a significant obstacle. 

• Model interpretability and transparency

Once again, deep learning models are black boxes that provide the answers without explaining how they arrive at them. This is not ideal for regulated industries like healthcare, finance, or manufacturing. 

Executives and decision-makers will require authority and audit trails, compliance-ready output, and, as they will be cognisant of escalation in tech debt, standardisation, reliability, and usability. Explainable AI (XAI) is increasingly becoming popular, but the maturity of the XAI domain with deep learning models is slow. 

• Scalability and infrastructure needs

Deep learning models require higher-powered GPUs, more memory, and more compute time, along with ongoing deployment costs to stream. After deployment, maintaining low latency and responsiveness across enterprise-sized systems can be a costly engineering challenge. 

Also Read: How early-stage deep-tech startups can attract and retain the right talent

Companies must consider what their cloud/on-prem/hybrid platform will do for these requirements and, importantly, whether they expect real-time inference for mission-critical situations. 

• Legacy system integration

Most companies still have many legacy systems, such as ERP suites, mainframes, and software developed decades ago. There are no plug-and-play deep learning libraries for these old systems. 

It usually means significant customisation, middleware, or even re-architecting parts of the systems. Going from predictive insight to actions within legacy processes is time-consuming and expensive. 

• Cross-team collaboration and talent

Deploying deep learning isn’t hiring a data scientist. It’s a close interaction between domain experts, software engineers, data engineers, and DevOps teams. 

Misalignment between these stakeholders is a typical reason for failed projects or models that aren’t created. Deep learning projects require good communication loops and joint responsibility between departments. 

• Model drift and continual learning

The only constant in life is change. A model trained on data collected twelve months ago will be unable to locate anomalies or patterns that are present today. In commercial applications like e-commerce, fraud detection or prevention, and transport planning, even the slightest drift pattern in the data can dramatically affect the business. 

Businesses require systems that can track performance, recognise model drift, and launch retraining pipelines. Without lifecycle management, even the best models will fade quickly. 

Best practices to overcome these challenges 

To fully realise the benefits that deep learning can provide, companies need to have an approach based on technical maturity and target the industry.

Also Read: 3 ways AI and deep learning is now changing the education industry

Some of the critical best practices include: 

• Develop MLOps pipelines that deploy models, monitor, and retrain automatically – all are important to manage accuracy in fast-changing domains such as patient care or diagnostics.  
• In the design phase of any AI application, make data lineage and governance a priority for HIPAA compliance, auditability, and compliant use of AI, particularly for sensitive patient health records and medical images.  
• Include domain knowledge from clinicians and other medical experts in the model development process to increase the relevance and acceptance of AI models in healthcare. 
• Design scalable with hybrid capabilities using one pipeline for hospital/health systems networks, remote-monitoring systems/devices with AI hosted in the cloud. 
• Integrate explainability into the life cycle of an AI model, as stakeholders in the healthcare industry need to understand what the AI recommends and why. 

Conclusion 

Deep learning has the potential to be a great solution, but fulfilling that potential in the enterprise space requires much more than simply neural networks.

It requires clean data, interpretable models, scalable platforms, and a business strategy. Getting there isn’t easy, but the advantages of automating, customising, predicting, and uniquely differentiating your business are worth it. 

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As billions in investment pour into Southeast Asia’s data centre sector, US$6.3 billion to be specific, a rising tide of public scepticism over energy and land consumption has been raised at the Singapore-Johor-Riau (SIJORI) dialogue.

This, in turn, could create a critical public relations challenge – for digital infrastructure investors, operators and players, this could create a wider Public Relations problem on how they engage meaningfully with regulators.

Southeast Asia is aggressively building the engine rooms of the digital economy. With a staggering US$6.3 billion invested in the sector in 2024 alone, the race to power AI, cloud computing, and digital banking is undeniable. Hotspots like Johor in Malaysia are booming, absorbing demand from constrained neighbours, while Thailand and the Philippines are rolling out the red carpet for hyperscale operators. Malaysia, in particular, is taking a leading role. Its digital investments surged 125 per cent quarter on quarter in the second quarter of 2025, per the Malaysian Digital Economic Corporation.

But beneath the headline figures lies a potential disconnect. As government and industry leaders conceded at the recent SIJORI dialogue, immense strains on energy grids, water resources, and land availability – with a lack of viable solutions – could create friction, breaking momentum. This is also, in part, fuelling a perception gap where communities see only resource-intensive black boxes, not strategic assets. This disconnect is fast becoming a significant business risk, escalating into a looming public relations crisis for the industry.

According to industry analysts, this perception problem is largely self-inflicted. The historical model of development prioritised speed and discretion over public dialogue, creating a communications vacuum. This is a reactive situation that a specialised PR agency that works closely with media and other stakeholders are brought in to carefully manage, rather than a proactive strategy to build trust from the outset.

From technical problem to PR solution

The tough questions about sustainability are now driving policy. In Singapore, where data centres strain the power grid, the government’s post-moratorium criteria heavily favour green efficiency, a direct response to public and environmental pressure. For operators, navigating this complex landscape now requires more than just engineering excellence; it demands sophisticated communications, often leading them to seek specialist PR experts to help articulate their value proposition.

Also Read: From silicon to sustainability: Data centres in a warming world

Forward-thinking developers argue that the solution to these challenges is a new, holistic development model, built around sustainability. We talk to technology leaders – from hybrid cooling systems to quantum computing innovators; water treatment providers; renewable energy providers – all focused and committed towards sustainable, responsible growth.

This strategy transforms an infrastructure project into a positive PR story. New development models, for instance, are integrating vast green spaces, contributing to local community funds, and sharing network capacity to boost rural connectivity. In the process these infrastructure operators and partners are creating jobs, and becoming a visible community partner.

The next wave demands a new narrative

The need for a better public relations strategy is being amplified by the arrival of next-generation technology. The immense power and stability required by AI and quantum computing render the old development model obsolete.

This future is already here: For instance, BDx Data Centres recently announced the launch of Singapore’s first commercial use of quantum computing within its facilities, with the potential to drive further advancements in technology innovation and sustainability. This highlights the region’s technological ambition, but also underscores the urgent need for a public mandate to support such powerful infrastructure.

Ultimately, the entire region requires a more cohesive communications strategy. The scale and cross-border nature of the industry suggest a growing need for a strategic PR across Southeast Asia that can tailor a compelling narrative to the unique cultural and political nuances of each market.

Data centre operators, governments and developers must urgently reframe the conversation. They must proactively explain not just what data centres are, but what they do for society. If the industry continues to treat community engagement as an afterthought, it will find its path to growth blocked not by a lack of capital, but by a lack of trust. The race for Southeast Asia’s digital future will be won not just by building infrastructure, but by building understanding.

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Environmental, Social, and Governance (ESG) issues have moved from the periphery of corporate strategy to the centre of boardroom attention. Yet in Asia, many boards still treat ESG primarily as a reporting obligation or a compliance checkbox — not as a strategic lever for long-term resilience and value creation.

As independent and non-executive directors, we must recognise that boards need to advance their perspective. ESG has moved beyond being a mere obligation; it now represents a driver of competitive advantage, a safeguard against risk, and a foundation for stakeholder confidence. Boards that embed ESG into governance and strategy are positioned to surpass their peers in sustainable growth, reputation, and long-term resilience.

Why ESG is now a board-level imperative

Several forces are converging to make ESG a core board responsibility:

• Regulatory pressure: Governments across Asia are introducing ESG disclosure requirements, carbon reduction mandates, and reporting standards aligned with TCFD (Task Force on Climate-related Financial Disclosures).
• Investor expectations: Institutional investors increasingly link capital allocation to ESG performance. Firms with poor ESG records face higher cost of capital.
• Stakeholder scrutiny: Customers, employees, and communities are demanding ethical practices, sustainability, and transparency.
• Operational risk: Climate-related events, supply chain disruptions, and labour issues directly impact financial performance.

Boards can no longer delegate ESG oversight to management; it has become a fiduciary responsibility. Ignoring ESG is a governance failure.

The danger of treating ESG as “cosmetic compliance”

Too often, boards focus on what is easy to measure: carbon reporting, policy statements, and social initiatives. While necessary, these activities do not create meaningful value unless linked to strategy.

The pitfalls of cosmetic ESG include:

• Misalignment between ESG reporting and business priorities
• Tokenistic initiatives that fail to influence culture or operations
• Reputation risk if stakeholders perceive ESG as performative
• Missed opportunities to embed ESG into product innovation, market positioning, and long-term planning

Asian boards must recognise that ESG is not a moral add-on – it is a strategic lever that drives growth and reduces risk.

Also Read: ESG frameworks and standards: Cutting through the complexity for private markets

What board oversight of ESG should look like

Effective boards go beyond disclosure. They define the frameworks, KPIs, and accountability mechanisms for ESG. Key areas include:

Climate and environmental risk

• Scenario analysis for physical and transition risks
• Alignment with net-zero or national climate targets
• Oversight of resource efficiency, waste reduction, and energy management

Social and human capital

• Employee well-being, inclusion, and skills development
• Supplier ethics, labour rights, and community engagement
• Board oversight of culture, retention, and succession planning

Governance and accountability

• Integration of ESG KPIs into executive compensation
• Clear ownership for ESG outcomes across the organisation
• Transparent reporting to regulators, investors, and stakeholders

Boards should request ESG assurance reports, similar to financial audits, to validate progress and performance.

ESG as a strategic growth engine

Boards that treat ESG strategically can unlock multiple benefits:

• Financial performance: Companies with strong ESG metrics attract lower-cost capital, better credit ratings, and loyal investors.
• Innovation: Sustainability challenges inspire new products, services, and operational efficiencies.
• Resilience: ESG-oriented companies are better prepared for regulatory, reputational, and supply chain shocks.
• Stakeholder trust: Employees, customers, and communities increasingly reward responsible companies with loyalty and advocacy.

Asian boards must view ESG not as a compliance cost, but as an investment in long-term resilience and competitive advantage.

Also Read: The future of finance: ESG integration in tokenised funding

How boards can build ESG competence

To embed ESG into governance effectively, boards should:

• Conduct ESG capability assessments: Identify gaps in expertise, particularly around climate science, sustainable finance, and social impact.
• Upskill directors and management: Offer workshops, briefings, and scenario planning exercises.
• Integrate ESG into strategy sessions: ESG should be part of the discussion in every strategic review, not a standalone agenda item.
• Link ESG metrics to executive accountability: Align compensation with measurable ESG outcomes.
• Use ESG as a risk lens: Consider climate, social, and governance risks in capital allocation, M&A, and operational planning.

The future board: ESG-embedded and forward-looking

By 2030, the most successful boards in Asia will not be the ones that simply report ESG metrics. They will be the boards that:

• Anticipate regulatory and societal shifts
• Integrate ESG into strategy, risk, and culture
• Drive innovation while reducing negative environmental and social impacts
• Communicate openly with investors, employees, and communities

For aspiring independent directors, understanding ESG deeply is no longer optional. It is a core competency, a strategic differentiator, and a sign of governance maturity.

Boards that embrace ESG as strategic value creation, not just disclosure, will position their organisations for resilience, trust, and long-term success.

This article was first published on The Boardroom Edge.

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Companies like to call themselves global. But in many workplaces, language, nationality, and proximity to HQ still decide whose voice carries weight. If we want a more equitable digital economy, we need to stop confusing connected teams with fairly distributed power.

When people talk about equity in the digital economy, the conversation usually starts with access.

• Access to jobs.
• Access to capital.
• Access to technology.
• Access to opportunity.

Those things matter. But from my experience working across US, European, and Asian companies, I believe the bigger issue often starts earlier and closer to home.

It starts inside the workplace.

Before a company builds an inclusive product, it builds a culture. Before it expands opportunity in the market, it decides how influence works internally. And that internal system determines who gets heard, who gets trusted, who gets promoted, and who gets left behind.

That is why workplace culture is not a soft topic. It is operating infrastructure.

This matters even more now because work itself is being redesigned at scale. The World Economic Forum’s Future of Jobs Report 2025 draws on more than 1,000 employers representing over 14 million workers across 55 economies. This is not a niche HR issue. It is a global operating reality.

The corporate narrative today is that digital work has made companies flatter, faster, and more merit-based. Teams work across time zones. Meetings happen on Zoom. Workflows run through Slack, Teams, Notion, and shared documents. Translation tools continue to improve.

In theory, all of this should make work more equitable.

In practice, it often does not.

Many companies still run on an older logic: global footprint, centralised power

The people closest to headquarters usually carry an invisible advantage. Sometimes it comes from nationality. Sometimes from language. Sometimes, it comes from understanding the tone, humour, and unwritten rules of the people at the centre. Most of the time, it is a combination of all three.

This is rarely explicit. That is exactly why it survives.

It shows up in quieter ways. Whose ideas are seen as strategic. Whose pushback is read as executive maturity. Whose mistakes are treated as learning curves. Whose communication style feels “leadership-ready,” and whose feels like it still needs work.

One of the more uncomfortable truths in global companies is this: your passport and your fluency can still influence your credibility more than your judgment should.

I have seen this firsthand. I have seen people with better local market instincts, sharper commercial judgment, and stronger execution struggle to influence decisions because they did not package their views in the style most familiar to HQ. I have also seen people gain trust faster because they sounded right to the centre of power, even when their understanding of the market was thinner.

This is where the meritocracy story starts to break.

Also Read: Cybersecurity is the trust layer powering Southeast Asia’s digital economy

A company can have offices in ten countries, employees across multiple time zones, and all the right language about inclusion. But if influence still concentrates around one accent, one nationality cluster, or one headquarters culture, then it is not as global as it thinks it is.

It is simply internationally staffed.

That distinction matters.

Language inside a company is not just a communication tool. It is also a filter for power.

Google Translate can help people understand each other. It cannot equalise authority. Translation can preserve meaning, but not always force. It can enable participation, but not necessarily influence.

Research supports that distinction. A 2024 study in the Journal of World Business found that migrant professionals in multilingual organisations experience language-based discrimination in both physical and virtual workspaces. Digital work does not automatically erase old hierarchies. Sometimes it simply moves them onto new platforms.

Anyone who has worked in a multinational company has seen this dynamic. The meeting may be in English. The deck may be translated. The collaboration tools may be shared by everyone. But some voices still land more easily than others. Some accents are heard as polished. Some styles are read as senior. Others have to work twice as hard just to sound equally credible.

Too many companies still confuse fluency with competence.

And once that happens, inequality shows up everywhere: who gets visibility, who gets invited into strategic conversations, who is trusted with ambiguity, who gets stretch assignments, and who remains categorised as strong support rather than future leadership.

This is not unique to one region.

In some US companies, speed and confidence are rewarded so quickly that reflection can be mistaken for hesitation. In some European companies, process is so valued that it can quietly protect legacy gatekeepers. In some Asian companies, hierarchy runs so deep that respect can start to look a lot like silence.

Different styles. Same underlying question.

Who actually gets permission to influence?

That, to me, is the real measure of workplace equity. And it has very little to do with perks.

A company can offer flexibility, wellness programs, polished values statements, and all the language of modern culture. None of that changes much if the same profiles continue to be trusted fastest, promoted fastest, and heard most clearly.

In many global workplaces, some employees are doing two jobs at once: the actual job and the constant cultural translation required to be seen as credible. They are translating not only language, but tone, behaviour, and working style to fit the comfort zone of the dominant culture.

Also Read: Who gets to build and benefit from the digital health economy?

Invisible labour is rarely acknowledged, but it shapes careers

And this issue does not stop at HR. It shows up in product decisions, market strategy, hiring patterns, and customer understanding. A company that does not distribute influence fairly inside the organisation will struggle to understand diverse users outside it. A company that sidelines local voices in meetings will often sideline local realities in strategy. A company that centralises authority too tightly in HQ will keep mistaking proximity for insight.

So yes, the digital economy is global.

But many workplaces inside it are still operating with a much older model of power: influence travels more easily if you have the right passport, the right accent, and the right proximity to headquarters.

Until companies confront that honestly, equity will remain something they describe better than they design.

In the end, the real test of an equitable digital economy is not how many countries a company operates in. It is how fairly it distributes influence inside its own walls.

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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.

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The Philippines is pioneering a service-sector transformation powered by artificial intelligence (AI), according to the Philippine Private Capital Report 2026 by Foxmont Capital Partners. This shift carries powerful implications for Southeast Asia, where services dominate employment, but productivity gains remain uneven.

By embedding AI across processes and emphasising system-driven operations, the Philippines aims to transition from job-led growth to value-led productivity growth, a strategic imperative for the whole region.

Breaking the labour-intensity mould

Historically, sectors such as retail, IT-business process management (IT‑BPM), logistics, and financial services across Southeast Asia — and especially in the Philippines — have scaled primarily by increasing headcount. That model has been effective at creating jobs, but it creates limits on economic efficiency because output per worker grows slowly.

Also Read: The hidden tax on Philippine SMEs: Unreliable infrastructure

Foxmont’s report highlights that nearly 70 per cent of the productivity benefit from AI-enabled customer service transformations comes from people and process changes — workflow redesign, multi‑skilling, performance incentives, and clearer process ownership — rather than technology alone. In other words, AI is most powerful when it forces firms to redesign how work gets done.

Philippine firms that align talent, incentives, and operating models around AI-enabled processes can scale output significantly without proportional labour growth. This matters not just for competitiveness, but for the quality of jobs: employees can be shifted away from repetitive tasks into higher‑value roles such as quality assurance, relationship management, analytics, and product improvement.

The IT‑BPM sector: a case study in potential

The Philippines’s IT‑BPM sector — a cornerstone of its services export economy — illustrates the transition and highlights the gap between experimentation and full transformation. While a large share of firms have introduced AI tools for specific tasks (Foxmont notes that many firms have some AI integration), only a small minority achieve high AI maturity where AI is a core, governed part of operating infrastructure rather than a set of one-off pilots.

Global firms such as JP Morgan show a roadmap: AI moved from proof-of-concept to entrenched infrastructure through governance frameworks, cross-functional adoption (product, compliance, HR, ops), and continuous measurement of outcomes. Automation of routine tasks freed talented staff to focus on strategic work, producing measurable productivity uplift. Southeast Asian IT‑BPM hubs can adopt similar governance and measurement disciplines to accelerate value capture.

For the Philippines, the prize is clear. IT‑BPM already contributes significant export revenues and employment; raising AI maturity could boost revenues per employee, improve margins, and sustain competitiveness against lower‑cost or more-automated hubs.

Reimagining retail and logistics with e-commerce and data

E-commerce platforms have already shown how digitalisation redefines productivity. In the Philippines, players like Shopee and Lazada and a growing ecosystem of logistics and payments partners have decoupled growth from physical store expansion. Digital merchants can reach millions with relatively small teams by using data-driven merchandising, demand forecasting, and automated fulfilment.

Also Read: AI leapfrog: Paving the way for an AI-first tech ecosystem in the Philippines

The stark productivity differences between online and traditional retail demonstrate the greater return on integrating AI into the retail value chain: personalised recommendations, dynamic pricing, localised inventory placement, and automated customer support all lift revenue per worker. Logistics, meanwhile, gains from route optimisation, demand smoothing, and predictive maintenance, areas where machine learning drives immediate cost reductions and service reliability.

Across Southeast Asia, similar patterns are emerging: countries with stronger digital payments, denser fulfilment networks, and better consumer data capture are able to extract larger productivity gains from AI-enabled retail and logistics.

Government, education and policy levers in the Philippines

AI-driven transformation requires coordinated policy and investments in human capital. In the Philippines, multiple levers are being exercised:

• Public agencies, industry groups, and universities are increasingly partnering to build AI talent pipelines and curriculum updates that combine technical skills with domain knowledge (customer service design, logistics operations, financial compliance).
• Upskilling programmes from both private sector firms and technical-vocational institutions emphasise multi‑skilling — blending AI supervision, data literacy, and complex problem solving — which the Foxmont report identifies as a major source of productivity gains.
• Regulatory frameworks around data protection and fintech/financial services create the legal foundation for scalable data use and cross-border services. Strong governance and clear rules are essential to attract responsible capital and institutional buyers.
• For Southeast Asia more broadly, governments that accelerate practical AI skilling, incentivise workflow redesign pilot projects with measurable KPIs, and support cloud and data‑infrastructure deployments will see faster realisation of productivity benefits.
• Financing and private capital: shifting from pilots to scale

Private capital plays a catalytic role. Venture investors, private equity, and corporate venture arms are increasingly funding startups and incumbents that embed AI into service delivery — from AI-enabled contact centres to smart logistics and lending platforms. However, the transition from pilot to enterprise-scale deployment often requires patient growth capital and operational know‑how, not only software licenses.

The Philippine Private Capital Report 2026 emphasises the need for investors to support the organisational changes that technology demands: redesigning workflows, retraining staff, and establishing governance with measurable business outcomes. Investors who fund end-to-end transformations — rather than point solutions — are more likely to unlock durable value.

Regional implications and cooperation

Southeast Asia has several structural advantages for AI-enabled services growth: a young, digitally fluent workforce; rapidly expanding urban middle classes; high mobile penetration; and growing regional trade in services. Yet the region risks lagging if firms and governments treat AI as a tactical technology rather than a strategic re-engineering tool.

Collaboration across ASEAN — in standards, cross-border data flows, skilling frameworks, and start-up ecosystems — can accelerate adoption. Shared frameworks for responsible AI, interoperable digital identities, and regional talent exchanges would lower the cost of scaling services across markets.

Moreover, investors and multinational corporations can leverage the Philippines as a testing ground for service‑sector transformation: its sizable IT‑BPM base, growing e-commerce market, and active domestic investor community make it an attractive locus for pilots that can be replicated regionally.

Risks and how to manage them

The path to value-led growth is not automatic. Key risks include:

• Skill mismatches: rapid tech adoption without serious upskilling can create displacement or hollow-job growth. Address this with coordinated industry-academia training and transition programmes.
• Uneven regional development: productivity gains concentrated in a few cities can widen domestic inequality. Policies that support regional hubs (e.g., Cebu, Davao) and remote work can distribute benefits.
• Governance gaps: weak data protection or unclear AI accountability can undermine trust. Strengthening legal frameworks and industry standards is essential.
• Capital misallocation: funding narrow pilots without change-management budgets prevents scale. Investors should mandate transformation roadmaps and outcome metrics.

Conclusion

The Philippines’ evolving experience offers a compelling narrative for Southeast Asia: AI adoption is not just about automation, but about fundamentally redesigning service value chains to sustain economic growth. When technology is paired with workflow redesign, deliberate upskilling, governance and outcome‑based investments, services can become far more productive — creating better jobs, higher firm-level value, and stronger regional competitiveness.

Also Read: Echelon Philippines 2025 – Making AI work: How leaders turn AI into business value

For Southeast Asia, the strategic imperative is clear: move beyond tool adoption to system-driven transformation. The countries that do will capture the next wave of service-led prosperity; those that don’t risk being outpaced by more disciplined and value-focused competitors. The Philippines is already showing the way — and the rest of the region would do well to pay close attention.

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In a landmark event for Southeast Asia’s tech scene, Thai artificial intelligence (AI) powerhouse Amity has just raised a whopping US$100 million in its Series D funding round, the largest generative AI-focused capital raise ever in the region.

This fresh injection of cash puts Amity on a fast track to becoming a global AI contender, with ambitions to list publicly via an initial public offering (IPO) in 2027.

Also Read: Leading global from SEA: Lessons from scaling SaaS, cultures, and team from Amity Group’s journey

What does Amity do?

At its core, Amity is a Thailand-founded software and AI group that specialises in building business tools powered by AI. Its primary customers are enterprises in industries such as retail and telcos, sectors where AI can fundamentally reshape operations and customer engagement.

Through its AI Research & Application Centre (ARAC) in Singapore, Amity develops AI models tailored to specific industries and integrates them into a suite of companies under its umbrella. These companies include Amity Solutions, which focuses on agentic AI (more on that shortly); Amity Accentix for voice AI; Tollring for communications analytics; and EGG Digital for marketing and retail analytics.

Simply put, Amity builds AI that understands the unique problems of particular industries (“vertical AI”) and then uses this intelligence to automate and improve tasks, from customer service to marketing and beyond.

Breaking down vertical AI

Vertical AI is all about crafting AI tools customised for specific industries or business functions, rather than generic one-size-fits-all platforms. For example, AI that knows the retail sector inside out can predict sales trends accurately and recommend optimised marketing strategies, or AI designed for telecoms can analyse massive volumes of voice data to identify service improvement opportunities.

This contrasts with horizontal AI systems, which are general-purpose and may not perform as well on industry-specific challenges. Amity’s bet on vertical AI is rooted in its belief that targeted solutions deliver more measurable and direct returns on investment for companies.

The financial boost and what Amity plans to do with it

With this fresh US$100 million round—on top of the US$60 million announced late last year—Amity’s total funding has climbed to approximately US$160 million. The company is riding a revenue run rate of over US$100 million, up more than 10 times since 2022. More than 75 per cent of its earnings before interest, taxes, depreciation and amortisation (EBITDA) came from its European operations in 2025, signalling its reach beyond Southeast Asia.

Most of the capital will be directed at scaling up three strategic pillars. First, Amity will strengthen ARAC in Singapore, expanding its team and developing more advanced vertical AI models and “agentic AI” — software that doesn’t just analyse information but autonomously executes business processes end to end. This blend of research and practical application is key to pushing the boundaries of what AI can do.

Second, it plans rapid expansion through acquisitions: aggressively buying targeted software companies in Europe and Southeast Asia to build out its portfolio and broaden its market footprint.

Also Read: Scaling smart in Southeast Asia: What startups can learn from Amity’s journey

Third, Amity intends to integrate these diverse capabilities into a cohesive ecosystem to fast-track the commercialisation and adoption of AI solutions by enterprises. The goal is clear: establish itself as a regional leader in AI with a growing global presence.

The IPO goal and what it means

With a public listing targeted for 2027, Amity will aim to capitalise on its momentum and become one of the few Thai AI companies to reach this milestone. To date, Thailand’s tech IPO landscape remains nascent, especially for AI startups. The success of Amity could pave the way for more homegrown AI firms to access public markets and grow unabated.

Thailand’s AI landscape: a region on the rise

Although Southeast Asia has lagged behind giants like the US and China in AI adoption, countries such as Singapore and Thailand are quickly ramping up their capabilities. Thailand, in particular, has seen intensified government focus and investment in AI in recent years, coupled with a growing tech talent pool.

Key drivers include Thailand’s national AI development strategy, increased cooperation between academia and industry, and the growing number of startups entering the AI space. The government’s support has streamlined AI research initiatives and incentivised digital transformation across traditional industries such as manufacturing and retail.

However, the commercialisation of AI in the country is still finding its feet. Many businesses remain in pilot or early adoption stages. Realistically, the journey from research breakthroughs to scaling AI tools that deliver tangible business value is ongoing. This context makes Amity’s trajectory even more remarkable, as it has crossed from startup to scale-up status with a clear revenue stream and a growing international footprint.

The wider implications

Amity’s funding round was led by EDBI, the investment arm of Singapore’s SG Growth Capital, alongside Singapore-based growth equity firm Asia Partners, Indonesia-based VC SMDV, and Malaysia’s CMLIM Capital. Their backing reflects growing confidence that Southeast Asia can produce leading AI companies capable of competing globally.

Yeung Chia Li, Senior Partner at EDBI, highlighted how Amity’s Singapore AI hub strengthens its capacity to meet global enterprise demand and boost AI adoption across industries. “Amity’s expansion in Singapore, including AI research, product development, and ready go-to-market capabilities, will position the company well for the future,” she said.

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

Asia Partners’ Vorapol Supanusonti also pointed out the strength of Amity’s ‘Build, Buy, Bridge’ strategy — combining organic research, disciplined mergers and acquisitions, and integration — presenting a compelling approach to capturing the vast enterprise AI opportunity in Southeast Asia and Europe.

Asia’s AI ecosystem is maturing

With AI revolutionising every sector and region hungry for customised, scalable solutions, Amity’s rise is a clear signal that Southeast Asia’s AI ecosystem is maturing. By combining deep research, aggressive growth plans, and a commitment to tailored AI, Amity could well become the torchbearer for Thai and regional AI ambition.

It isn’t just about technology; it’s about showcasing that Southeast Asian startups can raise significant capital, develop cutting-edge AI solutions, and play on the global stage. For those watching the AI race unfold in Asia, Amity’s journey is worth following closely.

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In this interview, e27 speaks with Bell Beh, CEO and Co-Founder of Buzz, a travel payment platform focused on building digital infrastructure for underserved cross border travellers, starting with APAC-MENA and Muslim friendly travel. As AI capabilities expand across industries, Buzz is applying vertical AI models to address the unique needs of halal travel, pilgrimage logistics, and cross-border payment experiences across APAC and MENA.

This conversation forms part of e27’s broader AI Pulse coverage, which examines how organisations across the region are building, deploying, and governing AI in real-world settings.

Building AI companions for Muslim travel

e27: Briefly describe what your organization does, and where AI plays a meaningful role in your work or offering.

Bell: Buzz is a travel payment platform, specialising in building the Muslim travel infrastructure. At the core of our offering is BAE (Buzz AI Experiences), wee have built three AI travel companions, AI Tour Guide (BAE for Global Travel), first use case was launched with the Singapore Land Authority in 2024, Omani BAE, and Hajj & Umrah BAE — each designed to support different Asian travel needs from leisure to pilgrimage.

AI is crucial in delivering halal-aware recommendations, prayer-time–sensitive itineraries, multilingual assistance, and culturally relevant support across APAC,MENA and other unfamiliar territories. It also powers smart booking flows and secure cross-border payment optimization to support Muslim travellers globally.

Real-time guidance and booking integration

e27: What is one concrete way AI is currently creating value within your organisation or for your users or customers?

Bell: Our AI Tour Guide (Global BAE) creates value by giving travellers contextual tips and recommendations in real time, then guiding them straight into booking and payment flows globally. For faith-based journeys, Hajj & Umrah BAE provides halal-aware guidance and dynamically adjusts plans around prayer times, nearby halal dining, visa requirements, and local customs. This reduces friction and uncertainty during travel, improves user confidence, increasing booking conversion, and driving higher payment transaction volume on our platform.

Also read: AI Pulse Exclusive: How CoBALT is designing AI that teams can actually trust

Prioritising domain-specific AI models

e27: What was a key decision or trade-off you had to make when adopting, building, or scaling AI?

Bell: A key decision we made was choosing to build domain-specific AI models for Muslim travel instead of relying purely on large generic LLMs. This meant slower initial scaling and higher training effort, but it ensured cultural accuracy, halal compliance, and pilgrimage-specific intelligence that generic models often miss.

We prioritised depth and trust over speed, because in faith-based travel and cross-border payments, precision and contextual relevance matter more than volume.

Conversion gains and regulatory complexity

e27: Looking back, what has worked better than expected, and what proved more challenging than anticipated?

Bell: What worked better than expected was how quickly AI-driven personalization translated into measurable conversion and transaction uplift, especially when embedded directly into booking and payment flows. Our direct partnership with the Indonesian Hajj authority (BPKH) further validated that purpose-built AI for pilgrimage travel is not just a consumer feature, but institutional-grade infrastructure.

More challenging than anticipated was aligning AI deployment with regulatory, compliance, and cross-border payment requirements across multiple jurisdictions. In faith-based and financial contexts, accuracy, trust, and governance standards are significantly higher than typical travel use cases. Also, both travel and payment are heavily regulated, so applying licenses on both sides to reach the Agentic AI use case was challenging, especially when we are building the infrastructure layer.

AI must align with regulation and trust

e27: What is one lesson about applying AI in real-world settings that leaders or founders often underestimate?

Bell: One lesson founders often underestimate is that AI must align with regulation and operational reality, not just product vision. In sectors like travel and payments for us at Buzz, AI cannot bypass licensing, compliance, or trust requirements — it must integrate with them.

Agentic AI may look seamless in demos, but in the real world, automation is only as strong as the regulatory rails and human oversight behind it.

Also read: AI Pulse Exclusive: How Explico is building AI teachers can actually rely on

Building AI through vertical use cases

e27: Based on your experience, what is one practical recommendation you would give to organisations that are just starting to explore or scale AI?

Bell: Start with a clear vertical use case, not a generic AI deployment. AI delivers real value when it is deeply embedded into a specific workflow — whether that’s booking, payments, or customer guidance — rather than layered on as a chatbot.

Treat it as a 3-year progression, and don’t expect AI to be a magic pill: Year 1 focus on data readiness, safety, and assisted experiences; Year 2 integrate AI into core operations with human-in-the-loop and compliance-by-design; Year 3 scale toward more agentic automation once regulatory rails, partnerships, and governance are proven.

In a progressive manner, solve one high-friction problem end-to-end, ensure it aligns with compliance and operational realities, and scale from there.

From tour guide to agentic travel assistant

e27: Over the next 12 months, how do you expect your organisation’s use of AI, or the role of AI in your industry, to evolve?

Bell: Over the next 12 months, we expect AI to shift from being primarily an AI Tour Guide to becoming a Agentic AI Travel Agent that can execute—within regulated boundaries—more of the Plan – Decide – Act – Execute. It‘s no longer just suggestiona/ assisting with travel itineraries. It’s execution layer for our Vertical AI trained since 2024 with various governments.

For Buzz, this means deeper integration of BAE into partner inventory and cross-border payment rails across APAC–MENA, with stronger compliance, auditability, and human-in-the-loop controls.

Across the industry, AI will move from chat-based experiences to workflow-native automation, but adoption will be paced by regulation, trust, and licensing readiness—especially in travel fintech and Muslim travel infrastructure.

Also read: AI Pulse Exclusive: How Spacely AI is bringing generative AI into spatial design workflows

Final thoughts on vertical AI

e27: Anything else you want to share with the audience?

Bell: 2026 is the year of vertical AI, choose one niche and execute well.

The rise of vertical AI in specialised sectors

This conversation highlights how vertical AI is emerging across specialised sectors where cultural context, regulatory compliance, and domain expertise are critical. In areas like Muslim travel and cross-border payments, AI systems increasingly function as infrastructure embedded into booking, guidance, and transaction workflows. As technology evolves, organisations may find that the most durable advantage comes from combining deep domain knowledge with carefully governed AI systems.

For more interviews, analysis, and real-world perspectives on how organisations across the region are applying AI in practice, click here.

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For three decades, startups operated in an open global system. Markets were accessible, supply chains were stable, and capital moved freely. Growth depended on building a strong product and scaling across borders.

That environment is changing.

The global system is becoming more fragmented. Countries are relying less on universal institutions and more on smaller, issue-based partnerships. These arrangements are selective, flexible, and often temporary. They are driven by strategic interests, not shared rules.

This shift has created a new structure for the global economy. Instead of a single integrated system, there are now multiple overlapping networks. Growth, capital access, and market entry depend on how well a company is positioned within these networks.

This is the alliance economy.

From global markets to alliance networks

In the past, companies expanded into markets. Regulations were broadly aligned, and scaling was a commercial decision.

That is no longer the case.

Expansion is now shaped by political, regulatory, and technological constraints. Countries are forming partnerships around specific objectives such as supply chain security, technology standards, and energy access. These partnerships are not permanent. They evolve based on interests.

As a result, market access is no longer universal. It is conditional.

Companies are not just entering markets. They are entering systems defined by alliances. These systems determine how data can be used, which technologies are allowed, and how capital flows.

Growth now depends on alignment.

Infrastructure is the new control point

Power in the current system is tied to control over critical infrastructure.

Three areas matter most.

Compute determines AI capability and digital competitiveness. Energy enables industrial and digital systems to function. Semiconductors are essential inputs for nearly all modern technologies.

These are not just economic assets. They are strategic assets that determine whether a country can operate independently.

As a result, countries are prioritising control over these areas. Alliances are often formed around shared infrastructure, access to supply chains, or mutual dependencies.

For founders and investors, this shifts where value sits.

Applications capture demand. Infrastructure captures control.

The most resilient businesses will either control these layers or enable them.

Also Read: Transition climate risk: Navigating the future of sustainable real estate

Middle powers are creating new opportunities

Not all countries are aligning with major powers. Many are pursuing strategic autonomy.

Countries such as India and Indonesia are engaging with multiple partners while retaining flexibility. They participate in international initiatives but set clear limits on their involvement. This allows them to benefit from cooperation without full alignment.

At the same time, they are building domestic capabilities. India is investing in AI standards, talent development, and semiconductor production to reduce reliance on external systems.

This creates a different type of market.

These countries are not just participants. They are platforms that connect multiple systems.

For companies, this means:

• Greater openness to capital
• Evolving regulatory frameworks
• Opportunities to shape new ecosystems

These environments are more complex, but they offer more room for positioning.

Implications for business strategy

The alliance economy changes how companies should approach growth.

Market access is no longer determined only by demand. It is shaped by regulatory alignment, data governance, and political considerations. Entering a market requires understanding its position within the global system.

Technology decisions are now strategic. Choices such as cloud providers, AI models, and data infrastructure affect where a company can operate. Different regions require different standards, and these standards are not always compatible.

Supply chains are also more exposed. Dependencies on specific countries or suppliers create vulnerabilities. Disruptions can occur quickly and with little warning. Companies need to build alternatives, even if this reduces efficiency.

Capital is no longer neutral. The origin of investment can influence how a company is treated in different markets. It affects partnerships, compliance requirements, and long-term access.

Growth is no longer just operational. It is structural.

Where value is moving

Value is shifting toward businesses that support the underlying structure of the system.

Infrastructure is becoming more important. Data centres, compute capacity, energy systems, and logistics sit at critical points in the value chain. These areas are less exposed to short-term volatility and more aligned with long-term demand.

There is also increasing value in companies that can operate across systems. As regulations and technology standards diverge, businesses that can bridge these differences become more valuable. This includes payments, compliance, and data integration.

Demand for sovereignty-focused technology is also rising. Governments and organisations want control over data, infrastructure, and systems. This drives demand for cybersecurity, local cloud solutions, and AI governance tools.

Emerging markets that maintain flexibility are becoming key areas for growth. Southeast Asia, India, and parts of the Middle East are positioning themselves as connectors between systems. This creates opportunities for companies that can navigate multiple environments.

Key risks

An alliance-based system introduces new risks.

Misalignment is a primary concern. Companies that conflict with local regulations or political priorities may lose access to markets.

Dependency is another risk. Relying on a single supplier, market, or technology stack increases exposure to disruption. Diversification is necessary, not optional.

Exclusion risk is increasing. Changes in alliances or policies can restrict access to markets or technologies. These changes are often outside a company’s control.

Complexity is also rising. Operating across multiple systems increases coordination costs and operational challenges. Each additional market adds new constraints.

Risk is no longer just competitive. It is structural.

Also Read: The shifting geopolitics of sustainability, energy, and climate

A practical approach

Founders need to adjust their strategy.

Diversification reduces exposure. Relying on a single market, supplier, or capital source creates risk.

Local understanding is critical. Each market has its own regulatory and political context. These factors must be assessed early.

Resilience should be built into operations. Systems need to adapt to disruptions in supply chains, regulations, and market conditions. This may require accepting higher costs.

Partnerships are increasingly important. Local partners provide access, knowledge, and credibility. In many cases, partnerships are more effective than direct expansion.

Finally, focus should be on structural trends. Infrastructure, energy, and critical technologies are aligned with long-term priorities. These areas are more likely to sustain growth.

Conclusion

The global economy is not becoming less connected. It is becoming more structured around alliances.

These alliances are shaped by infrastructure, technology, and strategic interests. They determine how markets function and how companies grow.

For founders and investors, the shift is clear.

The world is no longer a single market. It is a network of systems.

Success depends on positioning within those systems.

Companies that understand this and adapt early will be better placed to sustain growth in the years ahead.

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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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