Mobile gaming engagement is on the rise globally, with the latest industry data pointing to a maturing market where long-term player value is fast becoming the primary metric for success — and Asia-Pacific is leading the charge.

Measurement and analytics company Adjust released its Gaming App Insights Report: 2026 Edition today, revealing that global gaming app sessions have increased year-on-year, while the paid-to-organic ratio has climbed 61 per cent. The findings signal a broader strategic shift across the industry: studios are moving away from volume-driven acquisition models and towards precision-led growth built on retention, engagement, and monetisation data.

Across regions, APAC posted the largest increase in the paid-to-organic ratio, rising 45 per cent from 2.05 to 2.97. The surge reflects intensifying competition for users in a region that continues to draw significant investment from mobile gaming studios worldwide.

Engagement across APAC remained broadly stable, with sessions per user per day edging up from 1.69 to 1.70. Several markets, however, outperformed the regional average. Japan recorded a three per cent increase in sessions, rising from 1.76 to 1.81, while Singapore and Thailand each also posted three per cent growth. Indonesia, South Korea, and Vietnam each grew by two per cent.

On retention, APAC’s Day 1 rates held steady at 20 per cent, consistent with other global regions. Japan led the region at 25 per cent, followed by Singapore at 23 per cent, Thailand and Indonesia at 21 per cent, and South Korea at 20 per cent.

Also Read: Half of APAC consumers are tired of poor-quality AI content from brands: Report

At the subgenre level, strategy games recorded the strongest session growth of any category, climbing 57 per cent year-on-year. Casual and hyper-casual games also posted solid gains, rising 37 per cent and 31 per cent, respectively. On the install side, slots, casino, and casual games led growth, up 46 per cent, 22 per cent, and 19 per cent year-on-year. Hyper-casual, RPG, simulation, and word games also recorded growth across the same period.

The report’s findings reflect a structural evolution in how studios approach gaming app growth. Rather than prioritising install volumes alone, developers and marketers are placing greater emphasis on acquiring high-value players and sustaining their engagement over time.

Tiahn Wetzler, director of marketing at Adjust, said studios are increasingly focused on retaining high-value players, optimising creatives and channels, and building ad-to-experience flows that favour sustained play over fast turnover. “Understanding where true long-term value comes from, and the ability to connect acquisition, engagement, and monetisation data for fast decisions, is now a necessity,” Wetzler said.

April Tayson, Regional Vice President for INSEAU at Adjust, described the shift in APAC as indicative of growing market sophistication. “Studios are moving beyond pure install growth and focusing on building deeper player relationships through smarter acquisition, stronger retention strategies, and better measurement across the full player journey,” Tayson said, adding that markets across Southeast Asia in particular are showing strong engagement and retention potential.

Broader trends shaping mobile gaming in 2026

Beyond session and retention data, the report identifies several wider forces reshaping the gaming app landscape this year. Gaming App Tracking Transparency opt-in rates rose to 39 per cent in the first quarter of 2026, up from 38 per cent in the same period a year prior — a modest but continued improvement in signal quality for mobile marketers.

Also Read: Data trust remains AI’s biggest bottleneck as CIOs step into broader leadership roles: Report

The report also highlights the growing influence of direct-to-consumer strategies, AI-generated creative assets, live operations, reward-driven mechanics, and cross-platform approaches as studios look to diversify how they reach and retain players.

With competition accelerating across APAC and globally, the data suggests that the studios best positioned for sustainable growth in 2026 will be those that can connect the full arc from acquisition through to long-term player value — and act on that intelligence quickly.

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The rise of agentic AI presents a profound and dual-edged challenge to the traditional consulting industry, a sector that has long thrived now showing its age. While the technology offers the potential for unprecedented efficiency and new service lines, many consulting firms are grappling with an existential dilemma: their historical value proposition, built on the back of human labour and incremental digital solutions, is becoming obsolete.

Rather than leading clients into a new era of autonomous systems, these firms risk being left behind, still operating with a “digitalisation” mindset in an “AI-native” world. The industry’s failure to fully embrace the transformative power of agentic AI, both in its own operations and in its client services, is preventing it from reaping the true rewards of this technological revolution and even underdelivering on its promises to its clients.

The outdated model and the existential threat

For decades, the business of management consulting has relied on a well-established value proposition: it combines expert insight, proprietary frameworks, and a large human workforce to produce customised problem-solving and high-quality deliverables. This formula has been highly successful, scaling over time by hiring top university graduates and billing clients based on the scope and duration of projects.

At the core of this model were human-intensive tasks: gathering vast amounts of data, writing comprehensive reports, and creating polished, visually compelling PowerPoint decks. The value a client received was, in large part, the result of this labor-intensive process, culminating in a detailed and well-supported recommendation.

This traditional model, however, is a product of an earlier wave of digital transformation, and proving to be a poor fit for the age of agentic AI. The new generation of autonomous systems poses a direct and formidable threat to this long-standing approach. As the technology matures, it is directly capable of automating tasks that once justified significant teams and multi-month budgets. Some firms are still only in the nascent stages of this transition, with their internal AI efforts lagging behind a basic copilot subscription. Some of their so-called “AI agents” are, by some accounts, little more than simple models.

Also Read: From hype to harmony: Why agentic AI needs a platform-first mind-set to redefine CX

Preliminary strategy drafts, market scans, and benchmark reports, can now be generated in a matter of hours by advanced tools, directly compressing the value chain that traditional firms have long relied on. This commoditisation of a firm’s core output is forcing the industry to confront what has been described as an “existential” shift, yet many of their reactions are perceived as tame, defensive, and out of touch. The business is no longer about human labor as the primary means of production; it is about leveraging and orchestrating autonomous systems to achieve outcomes; a pivot many consulting firms are still struggling to make.

This resistance to change is also tied to a critical, unspoken element of the traditional consulting value proposition: providing “top cover” or a “seal of approval.” Clients would pay a premium to a well-known firm, not always to improve a solution, but to gain psychological and political leverage, a scapegoat if the plan failed. This dynamic is becoming obsolete. In an increasingly AI-driven world, it is plausible that AI itself will be viewed as a superior, more data-driven decision-maker, making the need for a human “seal of approval” from a consultant far less compelling.

Failing to grasp the true potential

The struggle of traditional consultants is not just about adapting to a new technology; it is about their fundamental failure to grasp what agentic AI truly is and the transformative potential it holds. Agentic AI represents a significant evolution beyond traditional AI systems and even the latest generation of Generative AI. At its core, an agentic AI is an autonomous system that can act independently to achieve a pre-determined goal.

Unlike traditional software, which follows a rigid set of rules, or a large language model (LLM) that is reactive to a prompt, agentic AI is proactive. It can break down a complex task into sub-tasks, plan its actions, execute them, and adapt to changing conditions with minimal human oversight. This inherent “agency” is the key distinguishing factor that empowers it to operate within dynamic, unstructured environments and orchestrate end-to-end processes.

This technological shift is not simply a matter of automating tasks; it is altering the nature of work itself. The future will not be a one-for-one replacement of human workers but the emergence of a fundamentally new organisational structure: the hybrid workforce. In this model, humans are not just supervisors but “coordinators,” “designers,” and “trainers” for AI agents.

Their roles are being redefined, and performance metrics are shifting from output quantity to more nuanced measures like innovation and strategic thinking. By remaining fixated on their old models, consultants are missing the opportunity to guide clients through this fundamental shift in organisational structure, leadership, and culture. They are still selling a product from the past, while the true market has already moved on to the future.

Also Read: Agentic AI, urban mobility & smart tourism: 2025’s travel investment hotspots

The new battlefield of cybersecurity they can’t protect

The most critical failure of the traditional consulting model lies in its inability to navigate the new Cybersecurity landscape created by agentic AI. The same autonomy and adaptability that make agentic AI so transformative for business also create a new and highly complex attack surface that shatters the static assumptions of most traditional security models.

An AI agent is not a static endpoint. It is a decentralised, adaptive entity that can operate across distributed systems, accessing multiple data sources and making independent decisions. The result is a dynamic, hard-to-predict security landscape that demands a completely new approach to defense.

Because many consulting firms are still “stuck in the old digitalisation,” they are not equipped to help their clients address these new and severe risks. The vulnerabilities are not confined to a single point but are embedded in the agent’s multi-layered architecture, leaving it susceptible to a range of sophisticated attacks.

These include “poisoned sight,” where an agent ingests malicious data that skews all its decisions, and “hijacked execution,” where sophisticated prompt injection attacks trick agents into exfiltrating data. A successful attack on a single agent can persist indefinitely, quietly rewriting the agent’s “worldview” or leaking private chat history over time.

Beyond the technical vulnerabilities, the agentic AI revolution introduces specific, high-impact security challenges that business and security leaders must address, and which consultants are often unprepared to advise on:

• “Shadow AI agents”, the proliferation of unauthorised AI agents deployed autonomously by development teams or individual users without proper IT and security oversight. This creates a critical lack of visibility, making it impossible to enforce consistent security policies.
• “Black box” problem, where many agentic systems operate with decision-making processes that are not easily interpretable by humans. This creates a crisis of accountability, where organisations cannot explain why a specific action was taken, leaving them exposed to significant legal, regulatory, and reputational risks.
• The sheer volume and exponential increase in the number of AI agents pose a monumental challenge for managing and securing their unique, verifiable identities.
• The decentralised and autonomous nature of agentic AI makes traditional, perimeter-based security models obsolete. These models were built on the assumption that internal systems are inherently trustworthy, but a decentralised network of unpredictable, autonomous agents makes this assumption invalid. The absence of a Zero Trust architecture, where no agent or system is trusted by default, is not merely a best practice; it is a fundamental security imperative that many consulting firms are simply not helping their clients implement.

Also Read: Agentic AI: The next frontier in technology

Conclusion: The path not taken

The narrative that the AI boom is leaving consultants behind is not an oversimplification. It is a direct result of their own inabilities. The firms that are “left behind” are those that remain tethered to an antiquated business model focused on billing for human labor, creating commoditised deliverables, and offering superficial “top cover” to executives.

By failing to lead clients into the full scope of the agentic AI revolution, from its fundamental impact on the nature of work to its complex and dynamic security challenges, they are failing to reap its real rewards.

The future of professional services will not be defined by a choice between human and machine but by the strategic collaboration between them. The successful enterprise will be a hybrid entity where the speed, scale, and execution of agentic AI are perfectly complemented by the creativity, empathy, and strategic foresight of human leaders.

The only way for consultants to win in this new era is to move beyond the superficial and guide their clients through the full, multi-faceted revolution of agentic AI, a path many are still not on.

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Digital PR for businesses is no longer optional, it’s a strategic necessity. The internet has transformed how consumers interact with brands. Years ago, companies relied heavily on traditional channels like newspapers, magazines, and TV for exposure.

Now, the story has changed; consumers are online, attention spans are shorter, and competition for visibility is fierce. With information at their fingertips, most people now search for brands that connect with their values before making a purchase.

That’s where digital PR services and agencies come in. By leveraging online media intelligently, digital PR builds, manages, and protects a brand’s reputation while increasing visibility and credibility.

What is digital PR and why it matters

Digital PR (Public Relations) is the strategic use of online channels to promote a brand, improve its visibility, and strengthen relationships with customers and media outlets. It goes beyond press releases — encompassing content creation, influencer collaborations, SEO, and social media engagement.

Unlike traditional PR, digital PR integrates storytelling with search optimisation, helping brands reach the right audience, secure backlinks, and position themselves as industry authorities.

Benefits of digital PR for businesses

• Builds brand awareness and recognition: Digital PR campaigns help brands gain visibility across credible platforms. When your brand appears in top-tier publications, it strengthens consumer trust and establishes your authority in the industry.
• Improves brand reputation: Effective digital PR strategies help maintain a positive public image. By sharing authentic stories, responding to media coverage, and engaging audiences directly, your brand builds credibility and goodwill.
• Drives targeted traffic and leads: Securing backlinks from high-authority sites boosts your SEO performance and sends qualified traffic to your website — increasing your chances of generating leads and conversions.
• Strengthens SEO rankings: Backlinks are one of Google’s top ranking factors. Through strategic link building and media placements, digital PR enhances your search engine visibility and drives consistent organic traffic.
• Creates valuable partnerships: Collaborating with journalists, influencers, and industry leaders through PR outreach can lead to partnerships, sponsorships, and new business opportunities.

Also Read: How Category Design drives productivity and efficiency

How digital PR strengthens modern businesses

By combining brand storytelling, authority building, and digital communication, digital PR gives businesses the tools to compete in saturated markets. It not only raises awareness but also directly supports sales growth, recruitment, and investor relations.

Here’s how digital PR for businesses plays a crucial role in sustainable growth:

• Builds positive business sentiment: Working with media professionals and influencers fosters positive perception — leading to trust, loyalty, and repeat customers.
• Boosts social media engagement: Digital PR campaigns often include social media promotion, helping you engage directly with your audience, spark conversations, and build long-term relationships.
• Improves search engine rankings: With backlinks from authoritative sites, your brand ranks higher on Google — increasing organic visibility and generating more traffic that converts.
• Enhances content reach and social proof: Digital PR amplifies your most valuable content, ensuring it reaches your target audience. This not only boosts engagement but also builds trust and social proof that reinforce your credibility.
• Encourages brand advocacy: Satisfied customers often become your strongest promoters. Through PR-driven engagement, you can turn loyal customers into advocates who spread your brand organically.
• Delivers long-term value: Unlike paid ads that disappear when budgets run out, digital PR content stays online — continuously driving backlinks, referral traffic, and brand exposure over time.

Also Read: What is digital PR, and how can you develop an effective strategy?

Digital PR vs traditional PR: What’s the difference?

Modern brands need the data-driven precision of digital PR to stay visible and credible in a competitive landscape.

Conclusion

Digital PR for businesses is no longer a “nice-to-have,” it’s a must-have strategy for brand growth and sustainability. It builds authority, drives organic traffic, and keeps your business top-of-mind in a crowded online space.

When done right, digital PR doesn’t just raise awareness — it fuels long-term success by blending storytelling, search visibility, and authentic engagement.

Whether you’re a startup or an established enterprise, investing in digital PR ensures your brand remains relevant, trusted, and influential in the years ahead.

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The layoff call came without warning, shattering more than 20 years of career building in one fell swoop. One moment, I was the Senior Vice President, planning and managing a team of 20 marketers for Singapore’s consumer banking business; the next, I was packing up my desk and receiving hushed, reluctant farewells from my colleagues.

I was just shy of reaching my fourth anniversary with the company. However, countless late nights and sacrificed weekends culminated in vain after that fateful call.

I wasn’t the newest hire, nor the highest-paid employee, and certainly not the least essential. Despite my experience and efforts, my value was reduced to a number that was eliminated to improve the company’s financial position.

The shock didn’t just affect me emotionally, but left me in a mid-career existential crisis with the realisation that no amount of corporate loyalty can keep you safe from the chopping block.

How Singapore’s younger workforce is fighting back

Ironically, Singapore’s been witnessing a slow uptrend in unemployment since 2023 despite its labour market growing. The tech sector, which once promised strong growth after the pandemic, is now one of the leading industries in terms of layoffs. As a result, a climate of uncertainty and anxiety is building among professionals at all career stages. 

Young Gen Z and millennial tech professionals are slowly realising that corporate loyalty does not equate to job security, and are taking control of their career trajectories. Now, they prioritise work-life balance and career flexibility, which manifests into embracing sabbaticals, “micro-retirement” and alternative working models to maximise their overall wellbeing.

For Singapore’s tech sector, the ripple effects are starting to take shape. Traditional tech careers usually followed linear, predictable trajectories: developer to tech lead to CTO, or marketing associate to marketing manager to CMO. Now, more tech professionals are intentionally carving out multiple career paths, developing their expertise across multiple projects simultaneously.

Younger workers are demanding for more meaningful work, to see the direct impact of their efforts and alignment between their values and what employees stand for. One of the fractional talents helping my company, Glenna Fong, is one such example.

With over 15 years of experience in media, business development, and content strategy, Glenna moved away from a stable traditional corporate role to become a Web3 token co-founder and digital pet care platform partner, while still offering fractional marketing services to young tech startups.

Flexibility is the future of work 

The unprecedented adoption of “working from home” a few years ago has fundamentally altered how we look at work. As a result, what were once considered niche like remote work, project-based contracts and freelancing have evolved from mere buzzwords into viable mainstream alternatives, allowing working professionals to reassess their definition of work.

Also Read: How founders can fund their startup without sacrificing ownership

After my retrenchment, I decided to turn towards fractional work and founded Mad About Marketing Consulting (MAMC), a fractional marketing consultancy that provides tech companies with highly experienced marketing teams on a part-time basis.

I’ve been able to step in as a part-time CMO for startups, challenging my skillsets in supporting each business’ own goals while also ensuring that these businesses receive the qualified expertise needed in order to grow, scale and compete in Singapore’s increasingly competitive landscape. 

What started as a response to my personal setback has now evolved into a model that can benefit both employers and employees that seek autonomy and impact. For startups, this immensely helps keep business costs lean, tapping into strategic expertise without incurring any executive overheads. For fractional professionals, this increases the learning velocity while reducing the risk of becoming obsolete.

A need to adapt and re-assess hiring processes

So, what does this mean for tech startups who are on the hunt for tech talent? They need to re-examine how they hire and retain these workers that look for flexibility and meaning in their professional and personal lives. Startups that can redesign their organisational structure would be able to thrive in the long-run.

Blended teams represent a promising model for startups. These hybrid structures allow permanent employees who know the ins and outs of the startup to collaborate effectively with fractional specialists. Successful clients that we’ve worked with focus on communication and cross-functional teamwork, ensuring that neither team or any department in the startup is functioning in silo.

Additionally, I strongly advocate for building flexibility and autonomy into the startup’s organisational DNA from day one. Those who democratise information access and focus on making communication dynamic result in working environments that value every individual contribution regardless of hierarchy, seniority or experience. 

Also Read: Southeast Asia’s travel tech boom: The startups powering a US$73B industry

Finding security and value in a world without guarantees

My last day in my corporate job seemed like an abrupt ending, when in truth marked the beginning of something more resilient and fulfilling than what any corporate role can offer.

Building a personal brand and robust professional network is your true safety net when building your fractional career. In the fractional economy, visibility creates opportunity. My first few clients at MAMC came through friends and relationships that I have cultivated in my over 20 years in marketing. Today, MAMC successfully serves multiple startups that value our team’s expertise while fuelling our growth.

For Singapore’s tech ecosystem to thrive amid global competition, both startups and professionals must embrace this shifting reality. The question isn’t wondering if alternative work models will be the future, but on how quickly the workforce can adapt to new norms of work where meaning and flexibility are valued.

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In this interview, e27 speaks with Ian about AIBYML SG’s approach to designing and deploying custom AI systems for enterprise environments. As organisations move beyond experimentation toward operational AI adoption, consulting partners increasingly play a role in bridging technology capability with governance, cost discipline, and measurable business outcomes.

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

Custom AI systems for operational workflows

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

Ian: AIBYML SG is an AI consulting and solution firm focused on designing, building and deploying custom AI systems tailored to real operational needs, from AI-native assistants and workflow automation to intelligent customer engagement and analytics.

Transforming workflows with end-to-end AI systems

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

Ian: One concrete way AI is creating value for our clients is through end-to-end process transformation powered by custom AI systems, rather than standalone tools. At AIBYML SG, we begin by working closely with clients to analyse their existing “as-is” workflows – identifying operational bottlenecks, manual handoffs, and hidden cost drivers.

leverage human intelligence and LLM AI

From there, we design “to-be” processes where AI is embedded in a targeted and measurable way.

A key part of our approach is selecting the most cost-effective model and architecture for each use case pairing it with clear performance metrics, investment estimates and usage projections. This allows clients to evaluate AI initiatives like any other business project. This discipline is what turns AI from an experiment into a scalable capability with positive ROI.

Also read: AI Pulse Exclusive: How Asia AI Association is advancing human-centred AI across the region

Balancing advanced models with operational sustainability

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

Ian: One recurring trade-off we help clients navigate is between using the most advanced AI models available and building solutions that are more economically and operationally sustainable at scale with open source foundation models. In many early discussions, stakeholders are understandably thrilled by the latest models because of their impressive capabilities. However, in production environments, model performance is only one part of the equation – cost, latency, reliability, data governance, and integration complexity.

Another important trade-off is between speed and organisation’s readiness. Moving quickly with a proof of concept demonstrates value, while scaling too fast without process redesign, user training, and clear benefits often lead to underutilised systems.

One thing we learned is that sustainable AI adoption requires balancing technical ambition with operational maturity. The right decision is rarely about maximising model capability – it is about maximising long-term business impact.

Adoption momentum and operational uncertainties

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

Ian: Looking back, what has worked better than expected is how rapidly our AI engineering team pivot suitable AI models embedded directly into their workflow design and tied to clear business outcomes. When we redesign the “to-be” process properly and define practical metrics — such as turnaround time, cost per case, or productivity uplift — adoption tends to accelerate.

What proved more challenging was managing uncertainty across cost, governance, and technology evolution. Clients understandably want clarity on short- and long-term AI investment, from model usage and infrastructure to maintenance and scaling. In practice, variable demand patterns and shifting pricing models make precise forecasting difficult, requiring scenario-based planning rather than fixed projections.

We also regularly navigate trade-offs between cost-efficiency and data governance. Stronger controls — private deployments, access management, auditability — reduce risk but increase operational overhead. At the same time, fast-moving advances in AI models make interoperability critical. Designing modular architectures adds upfront complexity, but protects long-term flexibility.

Also read: AI Pulse Exclusive: How CAWIL.AI is building industry-focused AI solutions across specialised sectors

AI exposing broken processes

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

Ian: One lesson from our client engagements is that AI does not fix broken processes – it exposes them.  In many engagements, we are initially asked to “add AI” to improve speed and reduce cost. However, once we analyse the existing workflow, we often discover redundancy, inconsistent data, unclear objective and undocumented exceptions. If AI is layered on these inefficiencies, it only automates complexity rather than solving it.

Another challenge is that stakeholders start by asking for a single AI feature. But once users test a prototype in their real workflow, they quickly form an “I know it when I see it” understanding and they start uncovering latent needs they couldn’t articulate upfront. Prototyping is powerful precisely because it reveals these hidden requirements through hands-on use.

Treating AI as structured transformation

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

Ian: “AI doesn’t fail because models aren’t smart enough — it fails because organisations aren’t ready enough. Teams that treat AI as a structured transformation, with clear metrics, cost discipline, and room for iteration, are the ones that turn experimentation into lasting ROI.”

From AI features to operating models

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

Ian: As AI tools become more powerful and no-code platforms lower the barrier to building applications, our strategic focus has shifted from “building AI features” to enabling sustainable enterprise capability. Basic chatbots and workflows will continue to be commoditised. Our long-term relevance depends on helping clients solve the harder problems around governance, integration, data, cost control, and operating ownership.

As part of our next strategic initiative, we will be working with regional enterprises that have experimented with multiple off-the-shelf AI tools but now face rising usage costs, inconsistent outputs, and growing compliance concerns. Our approach is to redesign their AI architecture to be model-agnostic, introduce structured cost monitoring and governance controls, and embed AI more deeply into core workflows.

Our key pivot is towards becoming an “AI operating model” partner — combining process redesign, modular architecture, and ongoing optimisation. The takeaway is simple: in the AI era, tools will keep changing, but organisations will always need partners who can turn fast-moving technology into reliable, governable, and scalable business capability.

Also read: AI Pulse Exclusive: How GenAI Fund is accelerating enterprise AI adoption across Southeast Asia

Operationalising AI beyond experimentation

This conversation highlights a growing shift from experimenting with AI tools to building sustainable operational capability. As enterprises face rising costs, governance considerations, and integration complexity, the focus increasingly turns toward process redesign, architecture flexibility, and measurable business outcomes. Organisations that successfully operationalise AI may find that long-term advantage lies less in the models themselves and more in how effectively they embed AI into everyday workflows.

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

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Grab is spending US$600 million to buy Delivery Hero’s foodpanda delivery business in Taiwan, in a move that does far more than add another pin to its map. It gives Southeast Asia’s biggest super app its first foothold outside the region, hands Delivery Hero a clean exit from one of its more valuable assets. It reshapes competition in one of Asia’s most closely watched food delivery markets.

The transaction is expected to close in the second half of 2026, pending regulatory approval and other customary conditions. If completed, Grab will take over foodpanda Taiwan’s operations across 21 cities, inheriting a business that generated around US$1.8 billion in gross merchandise value in 2025 and was profitable on an adjusted EBITDA basis before Delivery Hero’s group cost allocations.

Also Read: Grab: How we grew a business from 40 to 630,000 drivers

That last bit matters. Grab is not buying a troubled outpost in need of rescue. It is buying scale, coverage and an already functioning operation in a market where food delivery has matured beyond the early subsidy-fuelled chaos.

Why this acquisition matters for Grab

For Grab, the Taiwan deal is less a geographic vanity project than a strategic shortcut.

The company has spent years building out its delivery and mobility playbook across Southeast Asia. Still, by now, the region’s major urban markets are well mapped, fiercely competitive, and harder to expand at the pace investors once expected. Taiwan offers something rare: a developed, densely populated, mobile-first market where demand patterns are familiar, digital adoption is high, and urban logistics are complex enough to reward operational discipline.

Grab chief executive Anthony Tan called Taiwan its “ninth market and first outside of Southeast Asia”, framing the move as a natural extension of the company’s experience in dense Asian cities. Stripped of corporate varnish, the message is simple: Grab thinks the operating muscle it built in Jakarta, Bangkok, Ho Chi Minh City and Manila can travel.

There is also a financial case. Grab said the acquisition would be accretive to its 2026 revenue guidance of US$4.04 billion to US$4.1 billion and contribute at least US$60 million in incremental adjusted EBITDA in 2028. At a time when public market investors care more about earnings than expansion theatre, buying a scaled and already profitable delivery business is easier to defend than launching from scratch and burning cash for years.

The Taiwan entry also gives Grab something else: optionality. Today, the deal is about food delivery. Over time, if regulators and market conditions allow, Taiwan could become a launchpad for broader services such as grocery delivery, merchant tools, payments, and potentially mobility. Grab has not announced any such expansion, but its history suggests that once it has users, merchants and drivers on a platform, it rarely stops at one vertical.

Why the sale matters for foodpanda and Delivery Hero

For Delivery Hero, this is a strategic retreat wrapped in a decent cheque.
The German company has been under pressure to improve profitability, streamline its portfolio and show discipline after years in which food delivery companies chased growth at punishing cost. Taiwan was one of foodpanda’s stronger markets, which is precisely why it could fetch US$600 million in cash. The sale gives Delivery Hero liquidity and supports its broader strategic review.

Chief executive Niklas Östberg described the divestment as “a key first step in our ongoing strategic review”. Translation: Delivery Hero is reassessing where it wants to keep fighting and where it would rather cash out.

This is not the first attempt to sell foodpanda Taiwan. In 2024, Delivery Hero agreed to sell the business to Uber for about US$950 million, but Taiwan’s competition regulator blocked that transaction. The concern was obvious. Uber Eats was already a major player in Taiwan, and swallowing foodpanda would have dramatically concentrated the market.

That deal failed because it appeared to be a consolidation. Grab’s bid is different because it is entering Taiwan rather than merging with an existing local food delivery incumbent. That distinction could prove critical in the regulatory review.

What this means for Taiwan’s food delivery industry

Taiwan’s delivery sector was heading towards a competition cliff. The blocked Uber-foodpanda deal would likely have narrowed consumer choice, weakened merchants’ bargaining power and given one player a much tighter grip on the market.

Also Read: Driving performance: How Grab develops products that support driver-partners’ productivity

Grab’s purchase changes the script. Instead of reducing competition, the deal could preserve a two-horse race: Uber Eats on one side, a newly Grab-owned foodpanda on the other. That is not a perfect market by any means, but it is healthier than a near-monopoly.

For restaurants, especially small and medium-sized merchants, that matters. Delivery platforms are not just logistics pipes; they are gatekeepers to digital demand. When too much power sits with one platform, commission structures, promotional demands and visibility algorithms start to matter even more than food quality. A second serious player gives merchants leverage, however imperfect.

For consumers, more competition tends to mean better pricing discipline, broader choice and a stronger incentive for platforms to keep service levels high. The subsidy wars of the past may never fully return, but neither side can afford complacency.

For delivery riders, the picture is mixed. More competition can create better earning opportunities and platform incentives, but it can also intensify pressure around fees, utilisation and productivity. Much will depend on how Grab handles migration, incentives and workforce policies as it folds foodpanda Taiwan into its own systems by early 2027.

How foodpanda’s delivery business is faring in Taiwan

By the numbers, foodpanda Taiwan is holding up well.

According to the announcement, the business generated approximately US$1.8 billion in GMV in 2025. It was profitable on an adjusted EBITDA basis before group cost allocations, in a sector where profitability has often been more mythical than real, which makes Taiwan one of the sturdier delivery assets in the region.

That performance helps explain why Grab is interested and why Delivery Hero could command a meaningful cash exit even after the Uber deal collapsed.

Taiwan’s market characteristics also help. The island has a population of around 23 million, high smartphone penetration, dense urban centres, a strong convenience culture and consumers who are comfortable ordering food and groceries through apps. Those are highly attractive conditions for a logistics-heavy platform business.

Foodpanda has also built broad geographic coverage, which is not trivial. Serving multiple cities well requires more than marketing spend; it needs merchant density, rider supply, route efficiency and local operational depth. Grab is effectively buying a machine that already works.

Taiwan is attractive, but not friction-free

There is, however, a reason food delivery companies do not glide through Taiwan on bubble tea and optimism alone.

The market is competitive, operationally intense and politically sensitive. Regulators have already shown that they are willing to intervene where platform concentration becomes excessive. Labour issues around gig workers remain a live concern across Asia, and Taiwan is no exception. Merchant economics are also under scrutiny in any market where platforms become dominant.

Grab may have a cleaner antitrust case than Uber did, but approval is not automatic. Authorities will still look at how the acquisition affects future competition, whether platform practices could disadvantage merchants or riders, and how the migration from foodpanda to Grab will be managed.
That makes execution as important as strategy. Buying the asset is one thing. Retaining users, merchants and driver-partners through the transition is another. Platform migrations are delicate affairs. If incentives are mishandled, rivals can poach supply and demand with alarming speed.

Grab’s acquisition trail so far

The foodpanda Taiwan transaction is also notable because Grab has not historically relied on a rapid-fire M&A spree, unlike some tech groups. Its biggest moves have been selective and strategic.

Based on publicly disclosed acquisitions and majority-control deals, Grab has made five notable acquisitions or control transactions before this deal:

• Kudo in Indonesia in 2017, expanding into online-to-offline commerce and agent networks
• Uber’s Southeast Asia operations in 2018, the company’s most transformative deal, which cemented Grab’s regional scale in ride-hailing and food delivery
• iKaaz in India in 2018, strengthening payments capabilities
• Jaya Grocer in Malaysia in 2022, deepening its grocery footprint
• Trans-cab in Singapore in 2025, adding taxi fleet access in its home market

If the foodpanda Taiwan acquisition closes, it would become Grab’s sixth major acquisition or control deal of note. It may also be one of its most strategically symbolic, because it breaks the company’s geographic mould.

Grab’s current markets: the count needs correcting

The press release says Taiwan will become Grab’s ninth market. That means there are not “nine other markets” today. There are eight existing markets where Grab currently operates: Singapore, Indonesia, Malaysia, Thailand, Vietnam, the Philippines, Cambodia, and Myanmar.

Also Read: How mobile marketing is powering the next phase of food delivery growth in Southeast Asia

That may sound like a small detail, but in platform businesses, geography is never just geography. Each market means a separate set of regulators, labour dynamics, consumer habits, merchant relationships and unit economics. Entering a ninth market is not a line-extension exercise; it is a serious operational commitment.

The bigger message behind the deal

This acquisition lands at a moment when the food delivery industry is growing. The era when platforms could justify almost anything in the name of market share has faded. Investors now want profits. Regulators want competition. Merchants want fairer economics. Consumers still want speed and discounts, because human nature remains gloriously inconvenient.

Grab’s Taiwan move sits at the intersection of all four forces. It is expansion, but disciplined expansion. It is consolidation, but of a type less likely to kill competition outright. It is also a reminder that in Asia’s platform economy, geography still matters enormously. Dense cities, strong mobile usage and food-centric consumer behaviour remain valuable combinations.

For Grab, Taiwan is a calculated bet that its Southeast Asian logistics DNA can travel. For Delivery Hero, it is a monetisation event that supports a broader strategic reset. For Taiwan, it may be the difference between a delivery market with two heavyweight contenders and one drifting towards dangerous concentration.

That is why this deal matters. It is not just about who delivers dinner. It is about who controls digital demand, merchant access and urban convenience in a market that is too important to be left to one platform alone.

The post Grab’s US$600M deal could save Taiwan from a delivery monopoly appeared first on e27.

The cybersecurity threats facing businesses in 2026 are not merely an evolution of what came before. According to Arryaan Bhandari, Co-Founder and Chief Operating Officer of Singapore-based PQStation, they represent a structural shift. One driven by AI, accelerating attack cycles, and the looming spectre of quantum computing.

For security leaders across the Asia Pacific, the message is clear: preparation cannot wait for a crisis, a mandate, or a competitor’s breach.

In an email interview with e27, Bhandari describes 2026 as the beginning of an era in which AI compresses the timeline between a threat actor’s reconnaissance and their strike. AI-powered phishing, deepfake-enabled identity fraud, automated vulnerability discovery, and autonomous attack infrastructure are all converging to lower the barrier for launching sophisticated attacks.

“The organisations that combine AI-enabled defence with long-term cryptographic agility will be the ones that build durable digital trust,” Bhandari says.

That convergence is reshaping what cybersecurity fundamentally demands of business leaders. Detection, which is defined as catching threats as they arrive, is no longer sufficient on its own. The more urgent imperative, Bhandari argues, is architecture: how an organisation’s systems are built and whether they are designed to adapt as threats evolve. As generative AI lowers the cost and complexity of attacks, PQStation’s position is that cybersecurity must be treated not just as a detection problem, but as an architecture problem.

Also Read: Plug-and-play cooling: Carnotfleet’s bid to democratise the cold chain

Bhandari points to iterative validation as a practical starting point. Frequent proof-of-concept testing across security mechanisms — from endpoint defences to the cryptographic layer — helps enterprises identify what actually holds up under real-world pressure, rather than generating a false sense of compliance.

Critically, he cautions against waiting for regulatory mandates before acting. Organisations that move only when required will find themselves perpetually catching up. “The smarter approach is to build modularity and agility into security architecture now … so that as threats evolve — whether AI-driven or quantum-enabled — the underlying infrastructure can adapt without wholesale replacement.”

The quantum threat is not theoretical

Beyond the immediate cybersecurity threats of 2026, Bhandari identifies post-quantum cryptography as the defining long-term challenge for enterprise security. Much of today’s digital security — online banking, government communications, critical infrastructure — relies on cryptographic algorithms that a sufficiently powerful quantum computer could break.

“Quantum migration is no longer science fiction,” he says. “It is a structural inevitability.”

The challenge for enterprises, Bhandari explains, is not simply adopting new post-quantum standards. It is doing so across complex, deeply embedded systems without disrupting operations. That requires what PQStation terms “crypto-agility”, the ability to transition between cryptographic standards without mission-critical systems going dark in the process.

He recommends that organisations begin by building a clear inventory of their cryptographic assets, dependencies, and long-lived data exposure. Without that baseline, any transition will be fragmented and reactive. From there, a phased migration framework aligned with business-criticality gives security teams a structured, measurable path forward.

Also Read: Horizon Quantum’s SPAC listing signals selective return of deeptech deals

In the Asia Pacific region, Bhandari expects 2026 to function as an inflexion year. Most regulators have not yet mandated immediate post-quantum migration, but clear signals around quantum-readiness planning and cryptographic visibility are already shaping enterprise investment well before formal requirements arrive.

Financial services, government agencies, critical infrastructure operators, and healthcare organisations are the sectors most likely to face concrete guidance, and potentially structured mandates, during the year ahead.

His advice to security leaders is to move beyond minimum compliance. Documented migration roadmaps, measurable cryptographic risk assessments, and demonstrable resilience planning will increasingly become baseline expectations, not differentiators.

Ultimately, Bhandari frames the challenge for security leaders in 2026 not as one of reaction, but of readiness. Embedding security into architecture and procurement decisions, investing in internal capability, and aligning security strategy with long-term business continuity are the pillars he returns to consistently.

“In 2026,” he says, “leadership will be defined not by speed of response, but by depth of preparation.”

For businesses still treating cybersecurity threats as a compliance checkbox rather than a strategic priority, that distinction may prove to be a costly one.

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Image Credit: GuerrillaBuzz on Unsplash

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She always knew the answer. But she never raised her hand. I was tutoring a 13 year old girl who consistently scored well, but when it came to speaking up in class, she froze. “What if I say it wrong?” she whispered.

That line stuck with me.

It reminded me that the biggest barrier to learning isn’t always access to content, data, or devices. Sometimes, it’s confidence.

As edutech continues to shape the future of learning in Southeast Asia, we often talk about reach, affordability, and personalisation. But we talk far less about emotional safety, cultural expectations, and the silent learners who get left behind.

I believe there’s a confidence gap in edutech. And most platforms aren’t designed to close it.

Not every student is ready to click “submit”

Let’s be honest. Many edutech tools reward confidence: fast responses, public leaderboards, group discussions, peer review.

But what about the hesitant ones? The student afraid to speak in class, let alone in a Zoom breakout room The teen who worries more about making mistakes than making progress The adult learner who’s trying again after past failures

Also Read: The leapfrog thesis: Why embodied edutech is SEA’s path to a superior education future

If these learners don’t feel safe trying, no amount of adaptive learning will help. Because confidence isn’t just a nice-to-have. It’s foundational.

What confidence-aware edutech could look like

From my experience as a tutor and digital product builder, here’s what I believe confidence-aware platforms might consider:

• Anonymous first tries: Give students the option to practice privately before sharing. Tools like quizzes or reflections could be visible only to the learner until they’re ready to go public.
• Low-stakes feedback loops: Instead of pass/fail or right/wrong, offer feedback that focuses on effort, growth, or improvement. Think “You’re getting closer!” instead of “Incorrect.”
• Voice optional participation: Speaking up isn’t the only sign of engagement. Let learners submit written responses, use emojis, or give confidence ratings about how sure they are.
• Personalised encouragement: Let AI guide learners through gentle nudges: “Most students hesitate here, and that’s okay. Want a hint?” This kind of reassurance matters.
• Private practice modes: Create sandbox environments where users can try lessons or speak answers aloud without being recorded or judged.

Confidence is cultural

In many Southeast Asian classrooms, students are taught not to question. Silence is often seen as respect. Failure, especially in front of peers, feels deeply uncomfortable. So when we bring in bold, gamified, Western-style edutech products, we sometimes forget: confidence looks different here.

One of my adult mentees that I mentored , a 42-year old mom reentering the workforce, told me: “I don’t dare to press anything wrong. Later my son laugh at me.”

Designing for that mindset isn’t about dumbing down. It’s about meeting users where they are.

Edutech that builds confidence builds loyalty

When learners feel seen and safe, they stay. The tools that help users overcome their fears become the ones they recommend.

Also Read: Why Southeast Asia’s edutech must go beyond chatbots to truly transform learning

I’ve seen shy students become regular contributors once they trusted the environment. I’ve seen dropout risks turn into daily users just because the app didn’t shame them for missing a day.

Building for confidence doesn’t just help students. It helps retention.

Lessons from tutoring that tech often misses

As a tutor or coach, I don’t just teach subjects. I teach self-trust. I celebrate small wins. I let students explain things back to me without pressure. Most importantly, I read between the silences.

Edutech can do this too, with the right signals and mindset: Celebrate streaks, yes. But also celebrate comebacks. Track mastery, but also track courage (e.g., “You tried a harder topic today!”) Don’t just personalise content. Personalise encouragement.

Why this matters for founders

If you’re building an education startup in Southeast Asia, remember this: Your users may be smart but scared. They may log in daily but never participate. They may drop off not from lack of interest, but from fear.

If your platform only serves the confident, you’re excluding the majority.

Closing thought

We often say edutech can scale good teachers. But good teachers don’t just deliver content. They create safe spaces.

If we want to truly transform education, we must stop building just for performance. And start building for confidence.

Because confidence isn’t the reward of learning. It’s the permission to begin.

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The post Safe spaces, not just smart tools: How edutech can build confidence in learners appeared first on e27.

In this interview, e27 speaks with Dennis Yap, Founder of AI Seer, an AI venture focused on building systems that prioritise verifiable truth, traceability, and transparency in an increasingly noisy information landscape. As generative AI accelerates content production across social platforms, AI Seer positions itself around verification rather than generation, aiming to help organisations and individuals navigate misinformation more confidently.

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

Designing truth-seeking AI

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

Dennis: We create truth-seeking AIs, including a patented Multi-spectral Reality Detector and our bot @ArAIstotle which has a growing presence on Crypto Twitter has unique granular fact checking capabilities which is required for multimedia or long-form content on X unlike @grok for example. We’re also at least 3X less inaccurate than any other AI Search when it comes to news citations and provide fully transparent and traceable reasoning from credible sources.

Debunking misinformation in practice

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

Dennis: We help debunk fake news that are used in pump and dump scams on crypto twitter. See the post that @ArAIstotle is factchecking here as an example.

Protecting innovation

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

Dennis: When to patent our AI inventions vs the costs of doing so.

Also read: AI Pulse Exclusive: How Asia AI Association is advancing human-centred AI across the region

What surprised us

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

Dennis: Our X bot gaining followers was easier than expected after launching our token. Raising from the local SEA startup ecosystem has been more challenging than anticipated after ZIRP especially.

Adoption challenges

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

Dennis: Operations buy-in as people are very used to their existing workflows.

Practical advice for AI adoption

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

Dennis: Start small with explorations and use sandbox environments for testing. Look beyond LLMs, to other forms of AI that can help contain the randomness of LLMs.

Also read: AI Pulse Exclusive: How GenAI Fund is accelerating enterprise AI adoption across Southeast Asia

Looking ahead

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

Dennis: We expect to continue trying new AIs and integrating them into our workflows, especially for coding.

Final thoughts

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

Dennis: There are other frontier tech that can increase human productivity aside from AI, I am getting healthier through red light therapy for example and you can factcheck some claims about it here.

Building trust in the AI era

This conversation highlights a growing emphasis on transparency, verification, and trust as AI adoption accelerates. As generative technologies expand content creation, initiatives focused on fact-checking and traceability are becoming increasingly important in maintaining confidence in digital information environments.

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

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When regional startups map out their Southeast Asia expansion, the Philippines usually lands somewhere in the middle of the whiteboard. Not first, not last. “Emerging market” gets written next to it, which in founder shorthand tends to mean: small total addressable market (TAM), low willingness-to-pay, figure it out later.

That framing is outdated. For startups trying to prove commercialisation before burning through their Series A runway, it is also an expensive mistake — at least according to Vince Yamat, President and CEO of 917Ventures, the corporate venture builder of Globe Telecom.

Yamat has spent years sitting at the intersection of large enterprise infrastructure and startup execution, helping ventures across fintech, healthtech, adtech, and e-commerce move from experimentation to structured revenue generation inside the Globe ecosystem. His view on the Philippines is neither boosterism nor wishful thinking. It is grounded in what he sees founders consistently get wrong when they arrive here.

More scale than the label suggests

“Founders often hear ’emerging market’ and assume small, early, and low willingness-to-pay. What they miss is that the Philippines is actually one of the most efficient places in Asia to prove you can commercialise at scale. It combines a large, digitally engaged population with the kinds of real-world complexity that startups will eventually face across Southeast Asia,” Yamat says.

The numbers support that. The Philippines has 114 million people, roughly 87 million internet users, and 138 million mobile connections. Filipinos spend an average of 3.5 hours per day on social media, among the highest globally. That is one of the most digitally engaged consumer populations in Asia, accessible within a single language, a single regulatory environment, and an increasingly unified digital payments infrastructure.

The country is also the second-largest population in Southeast Asia after Indonesia. Yet it receives a fraction of venture attention. That gap between market reality and investor perception is exactly where the opportunity sits.

Why the Philippines works as a validation market

Three structural factors make the Philippines unusually useful for startups at the validation stage, Yamat argues.

The first is behavioural complexity within a single market. The Philippines compresses many of the dynamics startups will eventually face across Southeast Asia into one addressable environment: mobile-first consumers, real price sensitivity at a GDP per capita of roughly US$3,900, fragmented geography across more than 7,000 islands, and strong social commerce behaviour. Founders can stress-test pricing elasticity, retention, and distribution without the operational overhead of running a multi-country experiment.

The second is digital infrastructure that already exists at scale. GCash, built on Globe’s distribution network and part of the 917Ventures portfolio, has been used by 94 million Filipinos. “That scale has created a strong digital commerce layer across the market, giving startups access to one of the largest digitally transacting user bases in Southeast Asia,” Yamat notes. Globe itself serves around 65.8 million mobile subscribers, meaning the distribution question that stumps most market entrants is already largely solved.

The third factor is the speed of feedback. “Filipino consumers are extremely active online. Startups receive product feedback, adoption signals, and behavioural data very quickly,” Yamat says. “That matters enormously when you are trying to iterate before your next raise.” The country consistently ranks among the top markets globally for social media and messaging usage, making it one of the fastest environments in the region to pick up real user signal.

Also read: Why many funded startups still struggle to scale

What actually surprises founders once they get here

Pilot success does not automatically translate into scaled revenue. That is the first and most common reality check for regional startups entering the Philippines.

Yamat sees three patterns emerge once founders move past the initial proof of concept. “The biggest surprise is that pilot success does not automatically translate into scaled revenue. Distribution matters more than product. Reaching users often requires partnerships with telcos, fintech platforms, or large enterprises. Price sensitivity is real. And offline still matters — even digital products often require physical marketing or field activations to move beyond early adopters.”

Many startups arrive with a purely digital growth playbook and quickly discover that hybrid go-to-market strategies are not a compromise but a requirement. “Many startups come in with a purely digital growth mindset and realise that hybrid GTM strategies may work better here,” Yamat says. The market rewards founders who adapt fast and penalises those who insist on replicating playbooks built for more homogenous consumer environments.

Velocity and the case for structured enterprise access

This is where the structural gap in the Philippine ecosystem becomes most relevant for founders looking to move quickly.

Corporate engagement has historically been slow. Startups often spend months trying to identify the right business sponsor inside a large organisation, navigating layers of process before anything resembling a real pilot gets off the ground. “Large companies still operate in silos, which makes integration and deployment harder. Startups often don’t know who the real business sponsor is,” Yamat says.

Velocity by 917Ventures was built to close that gap. Rather than treating startups as vendors to be evaluated, the programme structures commercialisation partnerships directly with the Globe Group and its portfolio companies across fintech, adtech, consumer, and enterprise platforms. “Velocity exists so that startups don’t have to navigate the Globe Group alone,” Yamat explains. “The programme is designed to make collaboration easier and faster, helping startups work directly with the right business units from day one.”

Each engagement starts with a clear enterprise sponsor and a defined use case. Pilots are designed to run within 3-6 months and measured against concrete commercial outcomes, not just technical milestones. In some cases the programme also includes equity or staged investment options, aligning incentives on both sides from the start.

The first startup to go through Velocity illustrates the model well. Netopia AI, creator of the behavioural AI platform Predikta, is currently working with Brave Connective Holdings and its subsidiaries AdSpark and Inquiro to test how predictive behavioural insights can improve marketing intelligence and audience segmentation inside a real enterprise environment. “For Netopia, the value is exposure to large-scale consumer datasets and complex enterprise workflows, which helps refine the accuracy of its models and how insights are delivered to decision-makers,” Yamat says. For the enterprise side, it is a structured way to evaluate whether predictive tools can improve campaign outcomes before broader deployment.

That dynamic, a startup refining its product inside a real operating environment while the enterprise evaluates real outcomes, is what commercialisation actually looks like. It is different from a demo, a hackathon, or a pilot that never leaves the sandbox.

Also read: From VC-first to capital stack: Rethinking funding in Southeast Asia

The sectors worth watching

Four areas stand out as strong validation opportunities in the Philippine market right now.

“We are particularly bullish on digital trust and security, customer experience platforms, adtech and data, and vertical AI,” Yamat says. As digital adoption grows, demand for identity verification, fraud prevention, and secure transaction infrastructure is accelerating. Customer experience platforms are well-suited to the Philippine consumer’s behaviour across chat, messaging, and mobile. The digital advertising market is maturing quickly, with brands moving toward data-driven marketing and customer analytics. And vertical AI, particularly domain-specific applications integrated with enterprise data in telecom, fintech, and customer engagement, represents the next defensible layer for startups building in the region.

“These sectors align closely with the infrastructure and distribution platforms already present in the Philippine ecosystem,” Yamat adds. For startups, that alignment matters. It means the path from pilot to enterprise deployment is shorter because the underlying infrastructure already exists and is already in use at scale.

A regional launchpad, not a consolation market

The longer-term case for the Philippines is bigger than validation alone.

The country already supports one of the world’s largest IT-BPM workforces of around 1.7 million people, a talent base well-positioned to evolve alongside AI and automation. Yamat believes that over the next decade, this could translate into stronger capabilities in AI-enabled services, data operations, and digital product support, shifting the Philippines from a consumer market to a more active node in how regional technology gets built and refined.

The distribution dynamics are also structurally different from most markets. “One major difference between the Philippines and ecosystems like Silicon Valley is corporate distribution power. Telecom, fintech, and digital platforms already reach tens of millions of users. Over time, we may see corporates increasingly become startup distribution engines,” Yamat says.

The Philippines is unlikely to compete with Singapore as a capital hub or with Vietnam as an engineering centre. Its role is different and arguably more useful for founders at the commercialisation stage. “The Philippines could increasingly serve as a regional launchpad for commercialisation — a place where startups test adoption, validate business models, and build partnerships before expanding into larger but more fragmented Southeast Asian markets,” Yamat says.

For startups serious about Southeast Asia, that is not a secondary market. It is where the real work begins.

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The e27 team produced this article sponsored by 917Ventures

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