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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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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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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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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.

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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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In today’s hyper-connected marketplace, cyberattacks are no longer a peripheral IT issue; they are a direct threat to shareholder value, business continuity, and corporate reputation. The most profound crisis impacting your organisation’s resilience and growth is the staggering global deficit of cybersecurity talent.

This is not an HR challenge but a strategic vulnerability demanding proactive Leadership and an innovative approach to securing the professionals essential for your defence and market Leadership. The urgency for executive engagement is underscored by the fact that even educational institutions—the primary source of future talent—are prime targets for exploitation.

Deconstructing the deficit: Why your talent strategies may be undermining performance

The gap between cybersecurity expertise demand and supply stems from systemic misalignments that impact your ability to innovate, manage risk, and operate securely:

• The acceleration trap: Technology, particularly AI and IoT, evolves faster than traditional training, leaving businesses without graduates who possess immediately applicable skills, thereby impacting their speed to market and vulnerability to threats.
• The “entry-level experience” mirage: Outdated hiring practices that demand extensive experience for entry-level roles create an artificial barrier, narrowing the talent pool and increasing recruitment costs.
• The awareness abyss: The strategically vital career paths in cybersecurity are poorly understood, and socio-economic barriers prevent businesses from tapping into vast, undeveloped talent pools.
• The homogeneity handicap: A lack of diversity deprives your organisation of the varied perspectives and problem-solving approaches essential for tackling sophisticated threats and fostering innovation.
• The siren song of opportunity elsewhere: In key regions, the “brain drain” of skilled professionals to markets with better compensation creates a critical vacuum in local expertise, impacting operations and talent acquisition.

Forging sentinels: Talent development as a strategic corporate imperative

Addressing this crisis demands strategic investment in a holistic talent ecosystem and a long-term commitment to your organisation’s resilience and brand trust:

• K-12 — Cultivating future cyber strategists: Businesses should support initiatives that instil a cybersecurity mindset from an early age. This is a long-term investment in the talent pipeline and a cyber-aware customer base, offering an opportunity for strategic corporate partnerships.
• Higher education — The crucible of expertise and innovation: Actively partner with universities to ensure curricula are integrated with real-world industry needs, securing a pipeline of top-tier talent through investment in labs and faculty.
• Vocational training and agile certifications: Gaining Immediate Impact: Leverage boot camps and certifications for accelerated access to job-ready skills. These programs are crucial for upskilling your workforce and ensuring operational readiness.

Also Read: From grid to code: Why good cybersecurity will help deliver net zero

The Asia Pacific crucible: A high-stakes environment for your business

The Asia-Pacific region, a dynamic engine of growth, is also a primary target for cyber adversaries, presenting unique operational risks. Here, the talent shortage is exacerbated by challenges like the digital divide and varying regulations. Yet, this environment offers immense opportunities for businesses to lead. Through regional collaboration and investment in local talent, your organisation can pioneer models for cyber resilience and secure a sustainable advantage.

Beyond rote learning: The pedagogical revolution your workforce needs

Ineffective, “click-through” compliance training fails to mitigate real risks. To cultivate genuine cyber resilience, businesses must champion a pedagogical revolution that builds a more capable workforce through:

• Problem-based learning: Immersing teams in authentic, complex industry scenarios.
• Strategic gamification: Using game mechanics to instil rapid, high-stakes decision-making skills.
• Hyper-realistic simulations: Investing in “flight simulators for cyber defenders” to improve incident response and reduce the impact of breaches.
• Capture the flag competitions: Fostering practical skills and identifying top emerging talent.

These approaches are foundational to developing the adaptive professionals needed to outmanoeuvre adversaries and protect critical assets.

The technological vanguard: AI, IoT, and the quantum horizon – Strategic implications

Emerging technologies are reshaping your organisation’s risk landscape:

Artificial Intelligence: AI is a powerful ally, but it is also weaponised by attackers. Your future professionals must be AI collaborators, able to leverage their power while understanding their ethical limitations.

• Internet of things: The explosion of connected devices creates a larger attack surface. Your business needs specialists who can secure these vulnerable endpoints to prevent operational disruptions.
• Quantum computing: This looms as a potential “black swan” event that could shatter current encryption. Planning for post-quantum cryptography is now a matter of prudent risk management and fiduciary responsibility.

The core skill for your future workforce is adaptability. Training must shift from focusing on specific tools to cultivating the capacity for continuous learning—a strategic imperative for achieving business agility.

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

The unified front: Strategic alliances as a non-negotiable imperative

The scale of the cybersecurity challenge requires deep, sustained collaboration between government, academia, and industry. This means strategically investing in integrated ecosystems for resource sharing and creating robust apprenticeship and internship pathways. Acknowledging that retaining emerging talent is difficult for large corporations, innovative B2B partnerships are key.

Forward-thinking companies can engage specialised firms that find, train, and nurture young cybersecurity professionals. These firms provide pre-formed, job-ready teams that plug directly into larger enterprises, offering a flexible, scalable, and efficient solution to the talent pipeline problem.

Architecting your future defence: Pillars for decisive corporate action

To ensure operational resilience and enduring shareholder value, your business, under C-suite direction, should champion these strategic pillars:

• Advocate for visionary national strategies: Support holistic cybersecurity education roadmaps that align with business needs and objectives.
• Invest strategically in human capital: Prioritise continuous training and treat talent as a critical asset.
• Champion diversity as a competitive differentiator: Recognise that a diverse talent pool drives innovation and comprehensive risk management.
• Forge unbreakable alliances: Collaborate with peers, government, and academia to share best practices and mitigate systemic risks.
• Revolutionise pedagogy: Invest in modern learning methods to build an adaptive, future-ready workforce.
• Embrace global synergy: Foster international cooperation to address borderless threats impacting your global operations.

The challenge is immense, but so is the opportunity for visionary leaders to spearhead the solution. By strategically investing in human talent and fostering a culture of collaboration, your organisation can defend its present and confidently architect a secure and prosperous digital future.

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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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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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For years, flexible work in the Philippines was treated as a nice-to-have, the sort of employee benefit that sat somewhere between free coffee and mental health webinars. That era is over. In 2026, flexibility is no longer a cultural add-on. It is becoming a basic market condition for hiring, retention and even regional competitiveness.

According to the Philippines Talent Market Report 2026 by recruitment agency Monroe Consulting, 78 per cent of candidates now prefer hybrid or remote work, while 83 per cent say work-life balance is the main reason behind that preference. Yet 49 per cent of employers still believe full-time office work is the most effective model for their business. That gap is not just philosophical. It is increasingly expensive.

Also Read: Why remote working is the future for startups

In a country where commuting in Metro Manila can eat up hours a day, and where rising transport costs, extreme weather and infrastructure stress shape daily life, flexibility is not simply about convenience. It is about economics, resilience, and access to talent.

Manila’s commute problem has become a labour market problem

Any executive hiring in the Philippines already knows the dirty little secret of office-first policies: the job offer is evaluated not only by salary and title, but also by EDSA traffic, flood risk, transport costs, and the sheer unpredictability of getting home. For many professionals, especially mid-career talent with families, hybrid work functions like a wage supplement even when it does not appear on the payslip.

That is why the Monroe data matters. The report suggests that, even in a selective hiring environment where employers are more cautious, flexibility remains one of the few levers that can materially expand the candidate pool. Organisations that insist on rigid attendance models are not merely defending culture; they are also defending the status quo. They are shrinking supply in a market already short of experienced talent.

This has major implications beyond Metro Manila. The Philippines is an archipelago, and talent has never been distributed as neatly as office landlords might prefer. The same report shows that 75 per cent of respondents are based in Metro Manila. Still, the next layers of talent are visible in CALABARZON, Cebu, Davao, Pampanga, Baguio, Iloilo, and Bacolod. Hybrid and remote models allow companies to tap those pools without forcing every capable worker into the capital’s cost structure.

For startups, scale-ups and regional tech firms, that is a strategic opening. A Singapore-based company building in Southeast Asia does not need to think about the Philippines only as a Manila market. It can think in terms of distributed teams across talent nodes with different cost profiles, sector strengths and availability.

Flexibility is becoming a filtering mechanism for scarce skills

The Monroe report is particularly clear on one point: hiring is becoming more selective, not less competitive. That combination matters. When demand concentrates around digital, leadership, and highly specialised roles, the best candidates do not have to compromise on working arrangements. Employers do.

Also Read: Rethinking remote work: The engagement issue at the heart of work-from-home

This is especially visible in sectors where skills shortages are already acute. Technology, professional services, shared services, healthcare support, e-commerce, and data-related roles are increasingly shaped by candidates who benchmark not just locally but also regionally. Filipino professionals know they are competing in a more open market. Global employers know it too.

That makes flexibility less of an employee welfare issue and more of a commercial pricing issue. A company that offers a below-market salary but meaningful autonomy may still stay in the race. A company that offers market salary but demands rigid office presence may not.

This is one reason contract and project-based hiring are gaining traction. Monroe notes that employers are increasingly using fixed-term contracts, project roles, and temporary assignments to address skill gaps quickly without committing to permanent headcount. In the Philippines, where digital transformation programmes often move faster than formal workforce planning, flexible work and flexible hiring are becoming twin responses to the same constraint.

The productivity argument is losing its old force

One reason office-first thinking has persisted is the assumption that people are less productive when unseen. That argument is looking shakier. Monroe reports that roughly two-thirds of employers say their current work arrangements have either maintained or improved productivity. The tension, then, is no longer mainly about outcomes. It is about managerial comfort.

That distinction matters because businesses can solve for process, collaboration, and performance. They cannot solve for talent scarcity by wishing people back into long commutes.

The Philippines is also a market where organisational maturity varies sharply. Large enterprises, BPO operators, multinationals, and newer tech-led companies often have the systems to manage output and distributed teams. Traditional firms, by contrast, may still be navigating supervision through visibility. That creates a widening gap in employer attractiveness.

It also helps explain why cross-border employers are making inroads. If a skilled Filipino professional can work remotely for a regional company with better tools, stronger management practices, and clearer performance metrics, the local employer is no longer competing only with nearby offices in Makati or Bonifacio Global City. It is competing with the broader Asian labour market.

The real prize is not convenience. It is labour market reach

What makes the flexibility debate more consequential in the Philippines is that it intersects with several structural realities: a large English-speaking workforce, rising digital capabilities, strong services exports, and the growing willingness of companies to organise work across borders. In that environment, hybrid work is not just a human resources issue. It is a market-access issue.

Also Read: Why 2025 is a milestone year for startup funding in the Philippines

A rigid model can exclude parents, carers, workers outside central business districts, provincial specialists and people unwilling to pay the time-and-money tax of five-day office routines. A more flexible model can pull them all in. That is not ideology. It is labour supply arithmetic.

For the startup ecosystem, this is especially important. Southeast Asian firms often talk about talent shortages as if they are abstract. In the Philippines, the shortage is frequently self-inflicted. Employers are demanding a narrow labour profile in a country that could offer them a much broader one.

The hard truth is that flexibility has moved beyond symbolism. In the Philippines, it now shapes who applies, who stays, who relocates and who quietly rejects an offer before the first interview round is done.

Companies that still frame it as a perk are reading an old market map. The road has moved.

The post Flexible work is no longer a perk in Philippines, but the price of talent appeared first on e27.