The Philippine white-collar job market may look stable on the surface, but the data suggests something more fragile beneath. What appears to be low turnover is, in many cases, not a sign of employee satisfaction but of hesitation. With 54% of professionals considering a move within the next year, and 66% willing to leave even after a counteroffer, the foundations of this “stability” look increasingly temporary.

This creates a dangerous illusion for employers. Companies that interpret low attrition as loyalty risk being blindsided when delayed decisions suddenly convert into exits. The reality is that many employees have already disengaged; they are simply waiting for the right opportunity, timing, or market conditions to act.

What has changed is not just compensation expectations, but awareness. Filipino professionals are benchmarking themselves regionally, exposed to global opportunities through remote work and digital networks. As a result, traditional levers like reactive salary increases or counteroffers are losing effectiveness.

For founders and executives, the implication is clear: retention is no longer a reactive function. It requires proactive engagement: transparent career pathways, flexible work structures, and management quality that builds trust before resignation letters appear.

The risk is not a gradual rise in turnover, but a sudden correction. And when that wave comes, companies unprepared for it may find themselves scrambling for talent in an already constrained market.

Regional

SEA tech funding surges to US$2.8B in Q1 2026, more than doubling YoY: Late-stage deals and mega-rounds in enterprise tech drove the acceleration, with Singapore-based firms accounting for 93% of all funding. DayOne’s US$2B Series C was the quarter’s largest single round.

Bybit invests US$8M in Hata to crack Malaysia’s regulated crypto market: The dual-licensed Kuala Lumpur exchange now has US$12.2M in disclosed fundraising, as Bybit bets on compliance-first growth in a tightly supervised market where licensing is the real competitive moat.

Nium bets on a future where stablecoins swipe like credit cards: Singapore’s Nium has partnered with Coinbase to let businesses send, receive, and convert USDC across its cross-border payments network spanning 40-plus licences and more than 190 countries.

Netbank lands fresh Series B to power the invisible rails of Philippine fintech: Led by Altara Ventures, the round backs Netbank’s pitch to be the licensed banking layer underneath other fintechs, after the company reported 88% revenue growth and profitability in FY2025.

Airwallex to launch in Indonesia and Vietnam this year: The payments giant acquired licensed entities in both markets and recently received full approval in Malaysia, where it grew its team 66% in 2025 and plans to double headcount by year-end.

SEA’s fintech boom: market demand is real, but the numbers need context: UnaFinancial’s study crowns SEA as Asia’s most fintech-dense subregion at 14 companies per million people, but Singapore’s outsized 619-per-million density masks a far more modest picture across the rest of the region.

The real opportunity in ASEAN’s EV market lies in regional coordination: Dongfeng’s experience entering Malaysia and managing ASEAN operations from Singapore shows that winning the EV race will depend on centralised strategy and localised execution, not technology alone.

SEA’s next-gen leaders earn global spotlight in WEF 2026 cohort: Eighteen innovators from Indonesia, Singapore, Vietnam, Thailand, Cambodia, and the Philippines were named to the World Economic Forum’s Young Global Leaders class, spanning healthtech, fintech, climate action, and digital inclusion.

Vietnam startup visa gap: why founders are renting, not residing: Despite 8.02% GDP growth and a 17.9% rise in its startup ecosystem, Vietnam lacks a purpose-built startup visa, leaving foreign founders cycling through e-visas while Thailand and Malaysia actively court them with accessible programmes.

Korea-Vietnam to sign more than 70 MOUs in AI, infrastructure, energy: During President Lee Jae Myung’s state visit to Hanoi, Samsung, SK, LG, and Hyundai joined more than 500 executives at a business forum covering AI ecosystems, batteries, and Korean railway exports to Ho Chi Minh City.

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Interviews & Features

Flexible work is no longer a perk in the Philippines, but the price of talent: With 78% of candidates preferring hybrid or remote arrangements, rigid office mandates are shrinking the already-scarce talent pool, particularly for digital, leadership, and highly specialised roles.

Tsuklio brings US$155-a-week dinners to Singapore’s convenience economy: Japan’s Tsuklio, which has served over 30M meals across 46 prefectures, is targeting dual-income households and working professionals with a dietitian-supervised, central-kitchen subscription model in its first overseas market.

The new PR playbook: why proof, not narratives, wins investors: Southeast Asian VCs now demand traction, scalable models, and founder credibility, making consistent market signalling across concept, community, and corporate dimensions the most effective fundraising tool for startups in 2026.

The Vietnam startup visa gap: why founders are renting, not residing: Foreign founders drawn by Vietnam’s booming digital economy find existing investor visa thresholds too high for pre-revenue startups, putting Vietnam at a structural disadvantage compared with Thailand’s and Malaysia’s founder-friendly programmes.

The human touch advantage: why AI alone won’t win Singapore’s customer economy: Braze’s 2026 research reveals that while 93% of marketing leaders trust AI for customer insight, only 53% of consumers feel accurately understood, pointing to a widening trust gap that real-time context, orchestration, and transparency must close.

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International

Bitcoin surges 2.75% as US-Iran ceasefire extension lifts risk appetite: A 95% correlation with the S&P 500 over 30 days confirmed that Bitcoin is acting as a high-beta macro proxy, with a US$187.33M short squeeze amplifying the move toward the critical US$78K-US$8K resistance zone.

Why institutional money is buying crypto while geopolitical risks mount: Bitcoin ETFs drew US$272.59M in net flows while whale accumulation, including a single US$80M Ethereum purchase, and the SEC’s new five-bucket token taxonomy are together laying a more structural floor under crypto valuations.

Anthropic hits ~US$1T secondary valuation, surpassing OpenAI: Driven by limited share supply and strong institutional demand on Forge Global, Anthropic’s secondary price now exceeds OpenAI’s roughly US$880B, following its January 2026 funding round backed by Singapore’s GIC and Coatue.

SoftBank seeks US$10B margin loan backed by OpenAI shares: The two-year facility follows a US$40B bridge loan secured in March and Vision Fund 2’s commitment of US$30B to OpenAI, as SoftBank deepens its debt-fuelled bet on the AI arms race.

Tencent and Alibaba in talks to invest in DeepSeek at US$20B-plus valuation: The Chinese AI startup, owned by hedge fund High-Flyer Capital Management, is raising at least US$300M in its first-ever external funding round, with deal terms still subject to change.

OpenAI in talks to invest up to US$1.5B in private equity joint venture: The venture, internally called DeployCo, would see OpenAI contribute an initial US$500M in equity, with a targeted US$10B valuation at a funding close expected in early May.

South Korea’s economy grows 1.7% in Q1, fastest pace in five and a half years: Strong chip exports rising 5.1% and a rebound in both construction and facility investment drove the outperformance, beating the central bank’s 0.9% forecast by a wide margin.

Vingroup scraps 4.8GW LNG plant in favour of wind, solar, and storage: Chairman Pham Nhat Vuong cited Middle East war-related supply risks as the trigger for the pivot, while VinFast targets breakeven in 2027 and 300,000 vehicle deliveries in 2026.

Elon Musk bought US$1.4B of SpaceX shares from employees in 2025: The purchase added to a March board-approved plan granting Musk 60M more shares, tied to growing SpaceX’s valuation from US$1.1T to US$6.6T and building AI data centres in space.

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Cybersecurity

SEA’s digital paradox: US$300B in growth, US$3.2M per breach: With over 135,000 ransomware attacks recorded in 2024 alone, cybersecurity has become the foundational trust layer of the region’s digital economy, a competitive moat and investor signal, not merely a cost centre.

Cyber risk is a business risk: why communication defines corporate resilience: Penta’s analysis of 4.8M global cybersecurity mentions found that response quality matters more than breach severity, companies that communicate transparently and act quickly recover faster than those that stay silent.

The trust layer: how cybersecurity became hospitality’s most valuable asset: RedDoorz’s repeat booking rate of approximately 70% is built on a security-by-design architecture that keeps AI workloads within its own data warehouse, masks all PII, and treats every customer-facing automation as a potential attack surface.

Why trust is the only currency that matters in the AI era: PwC’s 2026 Global Digital Trust Insights survey found 60% of organisations rank cyber risk among their top three strategic priorities, yet only 6% say they are fully prepared, making trust-by-design a competitive differentiator rather than a baseline.

Architecting cyber defence: transforming the talent deficit into strategic advantage: The global cybersecurity talent gap is a strategic vulnerability, with systemic misalignments including outdated hiring, brain drain, and lack of diversity limiting organisations’ ability to innovate, manage risk, and operate securely across Asia-Pacific.

Australia working with Anthropic over Mythos AI cybersecurity vulnerabilities: Early tests of the model found thousands of major vulnerabilities, prompting the Australian government and central banks of both Australia and New Zealand to monitor the release, with experts warning autonomous AI tools could accelerate sophisticated attacks on banking systems.

Why endpoint security is so important for small businesses: Remote work and BYOD policies have elevated endpoint devices to the frontline of cybersecurity, with ransomware, phishing, and IoT vulnerabilities making endpoint protection a must-have rather than a nice-to-have for businesses of any size.

Data privacy for startups: simple steps to protect sensitive documents: Phishing, poor access management, and lack of encryption are the most common vulnerabilities facing fast-moving startups, but basic controls — encryption by default, role-based access, MFA, and regular training — can build a strong compliance foundation without large budgets.

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Semiconductor

TSMC shows smaller, faster chips without pricey new ASML tool: The foundry’s A13 process enters production in 2029, while its 2028 packaging target of 10 large chips with 20 memory stacks far exceeds Nvidia’s current Vera Rubin design, though heat, material expansion, and cracking remain unresolved engineering hurdles.

ASMPT sees Q2 revenue beat driven by AI semiconductor demand: The Singapore-based assembly and packaging equipment maker guided for Q2 revenue of US$540M-US$600M, above consensus, after Q1 revenue of US$507.9M beat estimates and profit from continuing operations reached HK$326.4M.

Samsung workers rally at Pyeongtaek chip campus ahead of planned strike: About 40,000 employees gathered after wage talks collapsed, with three unions threatening an 18-day strike from May 21 to June 7 demanding that bonuses be funded by 15% of annual operating profit, over 80% of the largest union’s members are in the semiconductor division.

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AI

Singapore’s AI adoption surges, but data complexity raises security risks: Hitachi Vantara’s research shows 66% of Singapore respondents have already succeeded with AI, yet only 23% believe they have industry-leading readiness for long-term ROI, as fragmented data environments and expanding attack surfaces become the defining constraints.

The rise of one-person AI companies and why micro-SaaS is at the centre of it: AI is enabling founders to move from team scaling to system scaling, with micro-SaaS — niche, subscription-based, AI-operated — emerging as the dominant model for lean founders who build systems first and companies second.

Why generative AI is raising the ceiling of custom software ROI: Generative AI has not simplified software development, it has amplified both good and bad decisions, lowering the floor by making more projects viable while raising the ceiling by compressing iteration cycles, with human product judgment remaining the decisive variable.

Why AI projects fail without strong data governance: A 2024 Deloitte benchmark found fewer than one in ten organisations have a governance framework robust enough to track data lineage, bias, and model oversight, a gap that compounds sharply as systems move from pilots to agentic, autonomous production deployments.

How are the companies you invest in leveraging AI?: With 90% of AI startups failing, investors must distinguish between AI-enabled incumbents bolting on AI to existing stacks and AI-native startups built from the ground up, continuous iteration, clear use cases, and defensible market position separating survivors from casualties.

The foundation of Southeast Asia’s tech future: Southeast Asia’s complexity — across languages, cultures, and regulations — is actually a forcing function that produces globally-ready AI startups, while the Singapore-Johor data centre corridor illustrates how physical infrastructure is now shaping where and how AI workloads run.

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Thought Leadership

From fragmentation to shared futures: re-wiring global digital cooperation from an Asian frontline:ASEAN’s 2030 digital masterplan, anchored in the Hanoi Digital Declaration, positions Asia not as a case study on the margins but as a design input for global norms on AI safety, data flows, submarine cables, and digital ID interoperability.

Empowering GEDSI: how OVOP can bring better inclusivity for Indonesia’s farmers: Cassava prices collapsing to below US$0.06 per kilogram expose a governance failure in Indonesia’s agricultural supply chain, one that the One Village One Product framework could fix by giving smallholder farmers a collective market identity that middlemen cannot easily undercut.

AI as a question of national security and independence: Governments building critical services on a handful of dominant AI platforms risk the same fragility seen in WTO paralysis, TPP withdrawal, and financial sanctions, making domestic chip production, data centre investment, and sovereign AI governance a matter of national resilience, not just innovation policy.

Why integrated communications drive stronger business outcomes: In a region expected to generate over US$1T in digital value over the next decade, fragmented PR, content, social, and digital marketing erodes momentum, integration compounds impact by ensuring every channel reinforces a single narrative and generates real-time learning.

On-chain data and Web3 security: insights from industry experts: Panellists at SMU’s security forum agreed that on-chain analytics — combining graph analysis, game theory, and machine learning — gives blockchain security a structural advantage in detecting fraud, validating smart contracts, and transitioning from reactive to proactive defence.

Earth Day: the surprising connection of cybersecurity and sustainability: Strong cybersecurity practices reduce energy consumption through efficient data transmission, extend device lifespans by preventing breach-driven replacements, and protect the critical infrastructure that underpins climate resilience, making cyber hygiene an environmental act as much as a security one.

Asia’s fintech hubs are not just shaping finance; they are redefining economic paradigms: Singapore, China, and India lead, but Vietnam, the Philippines, and Indonesia are rapidly emerging — driven by mobile-first consumers, regulatory sandboxes, and cross-border payment connectivity frameworks that are turning the region into the world’s fintech proving ground.

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The rapid proliferation of AI agents across enterprise environments is reshaping how organisations build and operate software, according to Datadog’s State of AI Engineering 2026 report. Based on telemetry data drawn from thousands of organisations running AI in production, the findings paint a picture of an industry accelerating into complexity—and beginning to encounter the operational limits that come with it.

Two findings stand out. First, the shift toward multi-model strategies is no longer a niche approach; it has become standard practice. Second, AI agents running in production are hitting a hard capacity ceiling, with rate limit errors emerging as the single most common cause of failure.

A multi-model world takes shape

A year ago, OpenAI commanded a 75 per cent share of enterprise LLM usage among Datadog customers. That figure has since fallen to 63 per cent: not because OpenAI lost ground in absolute terms, but because the broader market expanded rapidly around it. The number of Datadog customers using OpenAI more than doubled over the same period, even as Google Gemini and Anthropic Claude gained 20 and 23 percentage points of market share, respectively.

The more telling shift is happening inside organisations themselves. More than 70 per cent now deploy three or more models, and the proportion using more than six models nearly doubled year-on-year. Rather than selecting a single default provider, engineering teams are assembling model portfolios. They are matching lightweight models to extraction and tagging tasks and reserving frontier models for synthesis and reasoning.

This approach offers genuine advantages. Teams can optimise for cost, latency, and output quality at each stage of a workflow. But it introduces significant operational overhead. Coordinating API calls across disparate providers makes it harder to enforce safety and compliance standards consistently and leaves systems more vulnerable when any single provider throttles requests or degrades in performance. The report recommends that teams adopt modular routing mechanisms—such as a gateway service—rather than rely on direct provider API calls scattered across their environments.

Also Read: From fragmentation to shared futures: Re-wiring global digital cooperation from an Asian frontline

The compounding nature of this challenge is also reflected in how organisations manage model versions. Teams are quick to test new releases but slow to retire older models already running in production. Each additional model in the fleet increases evaluation burden and operational risk, a form of AI-specific technical debt that accumulates quietly until it becomes difficult to unwind.

AI agents stall at the capacity ceiling

The second major finding concerns how reliably AI agents perform once deployed. Datadog’s analysis of LLM call failures in customer traces reveals that in February 2026, five per cent of all LLM call spans reported an error with 60 per cent of those errors were caused by exceeded rate limits. The following month, the overall error rate fell to two per cent, but rate limit errors still accounted for nearly a third of failures, totalling approximately 8.4 million incidents in March alone.

The implication is significant. As AI agents take on more complex, multi-step workflows such as orchestrating tool calls, chaining model requests and operating with greater autonomy are running up against the throughput limits of model providers. Reliability, at scale, is becoming a function not just of code quality or prompt engineering, but of infrastructure capacity.

Datadog’s report recommends a combination of operational patterns, including request budgeting and backpressure systems, alongside prompt-level optimisations to reduce unnecessary token consumption.

“AI is starting to look a lot like the early days of cloud,” said Yanbing Li, Chief Product Officer at Datadog.

The parallel is instructive. Cloud computing unlocked enormous capability but demanded an entirely new discipline of operational management. AI agents appear to be following the same trajectory and organisations that invest in observability and reliability infrastructure now may find themselves considerably better positioned as the technology continues to mature.

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Image Credit: Igor Omilaev on Unsplash

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Southeast Asia (SEA) has emerged as Asia’s most fintech-dense subregion, according to a new study by UnaFinancial, an international fintech group headquartered in Singapore. The research maps fintech concentration across 19 economies using a per capita metric, arriving at a weighted average of 14 companies per million people for the subregion.

On the surface, it is an impressive figure. Look closer, however, and the story becomes more nuanced.

The density figures are not simply an artefact of investor enthusiasm or regulatory permissiveness. They reflect something more fundamental: a large and underserved population that traditional banking has consistently failed to reach. Across markets including Indonesia, the Philippines, and Vietnam, significant portions of the adult population remain unbanked or underbanked, relying on informal financial systems for payments, credit, and savings.

Fintech companies operating on mobile-first platforms and alternative credit-scoring models have moved into that gap at considerable speed. The proliferation of digital wallets, buy-now-pay-later (BNPL) services, and peer-to-peer (P2P) lending platforms across the region speaks to genuine consumer demand rather than supply chasing a non-existent market.

Where traditional banks required branch infrastructure, credit histories, and formal employment records, fintech operators have found ways to serve customers who lack them.

Also Read: The US$80K Bitcoin wall: What happens next could define the next quarter

This dynamic matters because it distinguishes SEA from fintech markets, where density is primarily a function of regulatory arbitrage or institutional capital seeking returns. The underlying demand in this region is structural, tied to demographic scale, rising smartphone penetration, and decades of underinvestment in conventional financial infrastructure. That foundation gives the ecosystem a degree of durability that pure capital-driven booms typically lack.

One city is doing a lot of heavy lifting

It is important to note that a substantial portion of the statistics is driven by a single market: Singapore, which registers a density of 619 companies per million, by far the highest of any economy in the study.

Singapore’s position is the product of specific and largely unreplicable conditions. As a city-state with a sophisticated regulatory environment, deep capital markets, and a long-standing policy of attracting international financial services firms, it functions more as a regional headquarters hub than as a representative SEA market. Many of the fintech companies counted in its figures are operationally focused elsewhere in the region or globally, using Singapore primarily as a base for licensing, fundraising, and corporate structuring.

Strip Singapore out of the subregional calculation, and the weighted average would fall considerably. The remaining markets—each contending with fragmented digital infrastructure, varying regulatory maturity, and populations spread across thousands of islands and rural provinces—present a more modest picture.

Also Read: Nium bets on a future where stablecoins swipe like credit cards

Treating Singapore’s density as indicative of broader regional progress risks overstating how far the ecosystem has actually developed in the markets where most SEA residents live.

Apart from that, a high company count per capita says nothing about whether these companies are financially sustainable, adequately regulated, or genuinely serving their stated customer base. Fintech markets that expanded rapidly during the low-interest-rate environment of the early 2020s are now under pressure, with funding harder to secure and profitability timelines under greater scrutiny.

The consumer demand underpinning SEA’s fintech growth matters. But demand alone does not guarantee that the companies formed to meet it will survive long enough to deliver on their promise. As the sector matures, the more meaningful measure of progress will not be how many fintech firms exist per million people. It will be how many of them are still serving those people a decade from now.

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We have spent the last three years in a storm of hype. Every week, a new model that promised to change the world; every month, companies scrambled to integrate whatever appeared to be the “next big thing.” But as we look toward 2026, the wind is changing. We are moving from the era of building the basics of AI to the era of living with it.

The conversation has moved away from how impressive the technology looks in a demo. What matters now is whether it delivers consistent, measurable value to a real human being. Here is my view on the seven major trends that will define our lives in 2026.

Software is no longer the “moat”, data is

For decades, building complex software was like building a castle. If you had the best code, you had the highest walls, and no one could touch you. That era is essentially over. In 2026, writing software will be trivial. AI can write production-ready code instantly. The “Moat” (your defensive business advantage) is no longer the app itself—it is the data inside it.

Imagine two companies launch a tennis coaching app. One has slightly better software; the other has 10 years of proprietary data on how professional athletes serve. In 2026, the second company wins instantly. Data, not software, is the new foundation of advantage.

AI moves off the screen, and into the world

AI is breaking free from the confines of the screen. We are entering an era of ‘presence-based’ hardware – devices are designed not just to respond, but to exist alongside us in specific environments. We are starting to see specialised AI hardware. Think of a small desk device that acts specifically as a “Doctor’s Assistant,” listening to patient symptoms and drafting notes securely.

By 2026, we will see them begin to converge into a new category of consumer hardware- something that might eventually challenge the smartphone itself. The new generation of devices will not simple compute on demand, they will be ambient, contextual and present.

Also Read: Bridging the last mile: How AI can transform agriculture, health, and education in SEA

Small is the new big (SLMs)

For a long time, the race was to build the biggest “Brain” possible (Large Language Models). This is giving way to a more pragmatic approach.

Giant, general-purpose systems are powerful, but they are also expensive, slow and difficult to control. The future belongs to smaller, specialised models trained to do one job exceptionally well. For instance, a bakery does not need AI that understands geopolitics. It needs someone who understands inventory, suppliers, and recipes. Small Language Models make AI systems easier to debug, easier to trust, and easier to compose. This allows multiple focused intelligences to work together.

The “agentic” factory

The way we build products is being redesigned from the ground up. The traditional development cycle of humans designing, coding and testing has already begun to erode. By 2026, teams will increasingly operate through fully agentic workflows.

Humans will define objectives and constraints. AI agents will design interfaces, write code, and attempt to break the system through automated testing. The human becomes the Architect, not the bricklayer. This will make software development faster and cheaper than we ever imagined.

Video becomes precise and controllable

Until now, AI-generated video has been impressive but unreliable. Small changes often produced unintended distortions, limiting serious adoption. In 2026, that changes. Advances in model precision are enabling object-level control within moving video. Creators will be able to modify a single element—such as the colour of a car—without affecting the rest of the scene. Video generation moves from novelty to utility, becoming a precise, surgical tool rather than an unpredictable experiment.

Also Read: The agritech challenge in Indonesia: Can AI and mobile apps enhance productivity?

Fighting the “slop”

The internet is flooding with AI-generated “slop”—low-quality, spammy content that feels like junk food for your brain. Social platforms are finally taking the gloves off. Expect aggressive new measures to filter out this low-effort noise. We will see a premium placed on human-verified reality. “Verified Human” might become the most valuable badge on the internet this year.

Protecting our minds

Perhaps the most sensitive frontier is psychological rather than technical. As AI companies become more conversational, empathetic and available, they can also become more addictive. Imagine an AI friend that knows exactly what you want to hear, 24/7. It is incredibly validating, but can be potentially manipulative.

2026 will be the year of regulation and ethical design. We will see features that prevent AI companions from becoming “digital sugar”—addictive and unhealthy. Just as we have warnings on physical products, we might start seeing “dependency warnings” on 9hyper-realistic AI chat apps. The goal will not be to eliminate companionship, but to ensure it remains healthy.

The verdict

2026 isn’t about AI becoming “smarter”. It is about AI becoming reliable, specific, and safe. It means we stop obsessing over the technology itself and start focusing on what really matters: human potential.

For business leaders, the takeaway is simple. Stop asking “How can we use AI?” Instead, start asking “what unique data do we own that no AI can replicate?” In a stabilised AI world, data, not the technology itself, will be the castle that will matter for the next decade.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

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In the global technology landscape, the conversation around artificial intelligence is often dominated by the race for ever-larger models and the dazzling capabilities of generative applications. For many, AI is a feature—a new button to press, a smarter chatbot, an enhanced recommendation engine.

However, for the dynamic and rapidly digitising economies of Southeast Asia, this perspective is not just limiting; it is a fundamental miscalculation. To unlock the projected US$1 trillion in regional GDP uplift by 2030, the region’s startups, enterprises, and policymakers must embrace a more profound paradigm: AI as core infrastructure.

This is not merely a semantic distinction. Treating AI as a feature means bolting it onto existing systems, a superficial enhancement to legacy processes. Treating it as infrastructure means building the entire enterprise on a new foundation, reimagining workflows, business models, and value creation from the ground up.

For Southeast Asia, a region defined by its vibrant complexity, this infrastructural approach is not just an opportunity—it is a necessity.

The complexity advantage: A launchpad for global-ready AI

What makes Southeast Asia the ideal launchpad for the application layer of AI is the very fragmentation often cited as a business challenge. The region’s diversity across languages, cultures, and regulatory frameworks acts as a powerful forcing function, compelling founders to design for scale and adaptability from day one. This environment makes it nearly impossible to succeed with narrow, single-market solutions, inadvertently creating a generation of startups building inherently global-ready AI.

Several real-world problems unique to the region are proving to be fertile ground for this new breed of AI infrastructure companies:

“Being based in Asia is for us a very good starting point because most of the world’s business processes are actually outsourced to Asia in general. So we’re using that base as a foundation for building a global company.” — Christian Schneider, CEO, fileAI

This proximity to complex, real-world workflows provides an unparalleled advantage. While Western counterparts may theorise about enterprise automation, Southeast Asian startups are building it at the source, creating horizontal platforms capable of navigating the intricate realities of global business process outsourcing (BPO), cross-border compliance, and hyper-localised customer engagement.

Also Read: How are the companies you invest in leveraging AI? 

From AI-first to AI-native: A foundational shift

The most forward-thinking companies in the region are already moving beyond simply being “AI-first.” A recent study found that 29% of businesses across ASEAN have now adopted AI, a significant increase from 21% the previous year, marking a 38% year-over-year growth. More importantly, a strategic shift is underway from merely experimenting with AI to fundamentally re-architecting operations to be “AI-native.”

This transition requires what Carro’s COO, Zi Yong Chua, warns against avoiding: building “AI for AI’s sake.” Instead, it demands a focus on tangible business value and an enterprise-ready foundation built on precision, preparation, and people. It means focusing on narrow, high-value use cases that deliver immediate ROI, doing the hard groundwork of data preparation, and investing in talent. This shift is evident in the rise of indigenous and sovereign Large Language Models (LLMs), such as Thailand’s open-source Typhoon model, which are being developed to support local languages and reduce reliance on foreign tech stacks.

The physical infrastructure paradox

The concept of AI as infrastructure is not just a metaphor; it is a physical reality. The exponential growth in AI adoption is colliding with the hard constraints of energy and data centre capacity. A single rack of AI servers can consume 40–60 kW of power, a tenfold increase over traditional cloud computing racks. This has created an infrastructure paradox in the region.

Singapore, long the undisputed data hub of Asia, is running out of power. With data centres already consuming nearly seven per cent of the nation’s electricity, a moratorium was placed on new construction, only recently lifted for operators meeting the strictest sustainability standards. This has pushed demand across the border to Johor, Malaysia, which has rapidly become the region’s new hyperscale frontier, with abundant land and power to support the massive, liquid-cooled data centres required for AI workloads.

This Singapore-Johor corridor is a prime example of how physical infrastructure is shaping the future of AI, creating a cross-border digital ecosystem where data-intensive training and latency-sensitive inference are run in different sovereign territories.

Also Read: AI, seed-strapping, and the new playbook: Why customers are the best VCs

The future is horizontal

As the region’s AI maturity grows, the strategic imperative is shifting from siloed, vertical solutions to powerful horizontal platforms. The most valuable AI companies will not be those that solve one problem well, but those that provide the foundational building blocks for others to innovate upon. This approach, championed by companies like fileAI, focuses on creating proprietary AI components that allow users to construct and automate a multitude of complex workflows.

This platform-based model is the essence of AI as infrastructure. It democratises access to powerful capabilities, enabling a broader ecosystem of businesses to become AI-native without each having to build its own core models from scratch. It is a strategy that recognises that the true value of AI lies not in a single application, but in its ability to become a pervasive, foundational layer of the new digital economy.

For Southeast Asia, the path forward is clear. The startups, corporations, and governments that recognise and invest in AI as fundamental infrastructure—both digital and physical—will be the architects of the region’s future. The trillion-dollar opportunity is not in building more features, but in laying the rails for a new era of innovation.

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Tech funding across Southeast Asia climbed to US$2.8 billion in the first quarter of 2026, more than doubling the US$1.3 billion recorded in the same period a year earlier and rising 146 per cent from the US$1.1 billion raised in Q4 2025, according to a new report by market intelligence firm Tracxn.

The figures, published in Tracxn’s SEA Tech Funding Report for Q1 2026, point to a broad acceleration in venture capital activity across the region, driven largely by late-stage deals and a cluster of mega-rounds in enterprise tech.

Late-stage funding was the primary engine of growth, reaching US$2.2 billion in Q1 2026, a 243 per cent increase from US$650 million in Q4 2025 and a 115 per cent rise from US$1 billion in Q1 2025. Early-stage investment also gained ground, rising 40 per cent quarter-on-quarter to US$487 million.

Seed-stage activity was the sole exception, falling 30 per cent from Q4 2025 to US$105 million, though it remained 39 per cent above the year-earlier figure of US$75.3 million.

Enterprise sectors drive capital inflows

Enterprise Applications and Enterprise Infrastructure were the standout sectors of the quarter. Enterprise Applications attracted US$2.4 billion, up 288 per cent from Q4 2025 and 74 per cent year-on-year. Enterprise Infrastructure saw even sharper growth, pulling in US$2.2 billion against just US$153 million in Q4 2025, representing a 1,368 per cent increase.

Also Read: Bybit invests US$8M in Hata to crack Malaysia’s regulated crypto market

Fintech, by contrast, had a difficult quarter. The sector raised US$192 million, down 69 per cent from US$613 million in Q4 2025 and 93 per cent below the US$2.6 billion recorded in Q1 2025.

Q1 2026 also saw five funding rounds of US$100 million or more, compared with two in Q4 2025 and three in Q1 2025. The largest was a US$2 billion Series C raised by DayOne, a company operating in the enterprise infrastructure space. Energy platform EPG secured US$200 million across two Series B rounds, while Bangkok-based enterprise software firm Amity Solutions closed a US$100 million Series D.

Three tech companies listed publicly during the quarter—BIM, The Assembly Place, and Toku—match the IPO count from Q4 2025. No SEA tech company had gone public in Q1 2025.

Acquisition activity eased slightly, with 13 deals recorded versus 14 in Q4 2025 and 21 in Q1 2025, marking declines of seven per cent and 38 per cent, respectively. The quarter’s most notable transaction was KKR and Singtel’s acquisition of ST Telemedia Global Data Centres for US$6.6 billion, making it the highest-valued deal in the region during the period. HCL Technologies’ purchase of Finergic for US$14.7 million was the next largest disclosed acquisition.

Singapore-based tech firms accounted for 93 per cent of all funding across the region in Q1 2026, reinforcing the city-state’s position as the dominant hub for SEA tech investment. Bangkok was the second-largest contributor, accounting for four per cent of total funding.

On the investor side, 500 Global, Antler, and Iterative were the most active at the seed stage. Vertex Ventures, SEEDS Capital, and Gobi Partners led early-stage activity, while Asia Partners and EDBI were the top late-stage investors in the ecosystem.

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At Echelon Philippines 2025, a powerhouse panel tackled one of the most critical questions facing startup leaders: how does tech accelerate scale?

Moderated by Judge Calimbahin III of Endeavor Philippines, the discussion brought together Thomas Abentung of Founders Launchpad, Juancho Jimenez of Openspace VC, Camille Ang of Hive Health, and Brian Ip of Omni HR. Together, they explored the right timing to scale, identified the types of businesses that simply aren’t built for rapid growth, and unpacked how company needs shift across different funding stages — offering sharp, actionable insights for founders navigating the journey from startup to scale-up.

The post Echelon Philippines 2025 – How tech accelerates scale: What startup leaders must build, buy, or learn appeared first on e27.

Southeast Asia’s digital economy is one of the great growth stories of the twenty-first century. A market that generated roughly US$40 billion in Gross Merchandise Value a decade ago has surged past US$300 billion in 2025, driven by over 200 million new internet users who have leapfrogged legacy systems and embraced mobile-first, digital-native lifestyles.

Fintech platforms, super-apps, cross-border e-commerce, and digital identity services have become the connective tissue of daily life across Indonesia, Vietnam, the Philippines, Thailand, Malaysia, and Singapore. Yet beneath this remarkable momentum lies a structural vulnerability that threatens to undermine the entire edifice: a widening gap between digital adoption and digital security.

The central argument of this article is not merely that cybersecurity matters. It is that cybersecurity has evolved into something far more fundamental — the trust layer upon which the entire digital economy is built. In the same way that contract law and property rights enabled market economies to scale, robust cybersecurity infrastructure is the prerequisite for digital commerce, digital finance, and digital governance to function at scale. For founders, investors, and policymakers operating in the SEA tech ecosystem, this reframing carries profound strategic implications.

The threat landscape is not a future problem — it is a present one

The scale of the challenge is already significant. The average cost of a data breach in ASEAN reached US$3.2 million in 2024, a six per cent year-over-year increase, with financial institutions in Vietnam and tech firms in Singapore among the most targeted sectors.

More than 135,000 ransomware attacks were recorded across Southeast Asia in 2024 alone, with 67 per cent of all regional cyber incidents concentrated in just a handful of high-growth markets. Over half of SEA consumers encountered scams on a weekly basis in 2023, and 66 per cent of organisations reported data leaks in the same period.

These are not abstract statistics. Behind each breach is a startup that loses its customer database, a fintech that watches its fraud rates spike, or a logistics platform whose operations are held hostage by ransomware. A single high-profile incident can destroy years of brand equity in a region where consumer trust is still being established.

As one regional expert bluntly observed, “a single breach can destroy trust, slow fundraising, and damage partnerships”. In a market where digital adoption is still accelerating, that trust, once broken, is exceptionally difficult to rebuild.

Also Read: Rethinking cybersecurity practices as Non-Human Identities (NHIs) surge

From cost centre to competitive moat

The traditional framing of cybersecurity as a cost centre — a necessary but unglamorous line item in the IT budget — is dangerously outdated. For startups operating in the SEA ecosystem, cybersecurity is increasingly a competitive differentiator and an investor signal. The question is no longer whether to invest in security, but how to make that investment visible and strategic.

Consider what a strong cybersecurity posture communicates to the market. It signals operational maturity, which is precisely what investors scrutinise during due diligence. It signals data stewardship, which is what enterprise clients and government partners require before signing contracts. And it signals resilience, which is what consumers increasingly demand before entrusting a platform with their financial and personal data.

In a region where private funding grew 15 per cent to US$7.7 billion in the past twelve months, and where investor attention is shifting toward governance and sustainability alongside growth metrics, the ability to demonstrate a credible security posture is a tangible fundraising asset.

The most forward-thinking founders in the region are already internalising this logic. Rather than treating security as a post-product-market-fit concern, they are embedding it into their architecture from day one — adopting encryption standards, least-privilege access controls, and secure coding practices as foundational choices rather than retrofits. As one practitioner advises, “cyber must be designed into products and operations early, because outsourcing everything can create a false sense of safety”.

The zero trust moment for SEA startups

Perhaps no concept better captures the paradigm shift underway than Zero Trust architecture. The traditional perimeter-based security model — which assumed that anything inside the corporate network could be trusted — was already strained before the pandemic. The explosion of remote work, cloud-native infrastructure, and API-driven ecosystems has rendered it effectively obsolete.

Zero Trust operates on a fundamentally different premise: never trust, always verify. Every user, device, and application must continuously authenticate itself, regardless of location or prior access history. This model is particularly well-suited to the SEA startup context, where teams are distributed across geographies, infrastructure is predominantly cloud-based, and third-party integrations are ubiquitous. The Asia Pacific Zero Trust market was valued at US$20 billion in 2024 and is projected to reach US$102 billion by 2033, reflecting a compound annual growth rate of 20 per cent. This is not a niche trend; it is the emerging baseline of enterprise security.

For startups, adopting Zero Trust principles early is not just a security decision — it is a scaling decision. As companies grow, the complexity of managing access, identities, and integrations multiplies. Building on a Zero Trust foundation means that security scales with the business rather than becoming a bottleneck.

The emerging cybersecurity startup ecosystem

One of the most encouraging developments in the SEA tech landscape is the emergence of a dedicated cohort of cybersecurity startups that are building the trust infrastructure the region needs. These companies are not simply reselling global security tools; they are building context-specific solutions that address the unique challenges of the SEA market — fragmented regulatory environments, high SME concentration, mobile-first user behaviour, and rapidly evolving threat vectors.

Also Read: In Southeast Asia, cybersecurity is booming but funding is not

This emerging ecosystem is remarkably diverse, addressing the full spectrum of trust and security challenges. In the digital identity space, startups are developing solutions for biometric verification, decentralised identity, and automated Know-Your-Customer (KYC) processes, which are fundamental for enabling trusted onboarding at scale for the region’s booming fintech and e-commerce sectors. Others are focused on application security, providing tools for mobile app hardening, secure code review, and API protection—capabilities that are critical for the integrity of super-apps and SaaS platforms.

To combat the ever-growing sophistication of attackers, a cohort of startups is leveraging AI for threat intelligence, offering advanced detection, threat hunting, and automated incident response services that help address the region’s significant cybersecurity talent gap. In parallel, a growing number of companies are tackling compliance and governance, building platforms for automated regulatory reporting, data privacy management, and audit readiness.

These tools are vital for startups looking to expand across borders and demonstrate a mature governance posture to investors. Finally, a crucial segment is dedicated to fraud prevention, using behavioural analytics, real-time transaction monitoring, and deepfake detection to protect consumer trust in digital financial services, which remains a primary target for cybercriminals.

This ecosystem is not merely defensive. Startups that help organisations embed trust, manage risk, and scale securely are forming a critical layer of the region’s digital stack. They are, in effect, the infrastructure providers of the trust economy.

The regulatory tailwind

Regulatory momentum is also aligning with this shift. Singapore’s amendments to its Cybersecurity Act in 2024 broadened coverage to essential services, while Malaysia’s Cyber Security Act 2024 introduced mandatory incident reporting and annual risk assessments for critical sectors. The ASEAN Digital Economy Framework Agreement (DEFA), currently under negotiation, represents the world’s first regional agreement on digital economy governance, with cybersecurity and data protection among its central pillars.

Also Read: AI and cybersecurity in healthcare: Building resilience for better patient care

While regulatory fragmentation remains a challenge — Indonesia and the Philippines still lack dedicated cybersecurity legislation — the direction of travel is clear. Compliance is becoming a baseline expectation, and startups that build with regulatory readiness in mind will be better positioned to scale regionally without costly retrofits.

A trust layer for the next decade

Southeast Asia’s digital economy is at an inflection point. The next decade will be defined not just by the pace of digital adoption, but by the quality of the trust infrastructure that underpins it.

Consumers are becoming more sophisticated; they are making conscious choices about which platforms to trust with their data and their money. Investors are becoming more discerning; they are asking harder questions about security posture, incident response, and governance. Regulators are becoming more assertive; they are setting higher bars for compliance and accountability.

In this environment, cybersecurity is not a constraint on innovation — it is the condition for it. The startups that will define the next chapter of SEA’s digital economy will be those that treat security not as a feature to be added, but as a value to be embodied. They will be the companies that understand, at the deepest level, that in the digital economy, trust is the product.

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