The race to integrate artificial intelligence (AI) into business is well underway in Southeast Asia (SEA). But as the adoption curve steepens, one truth remains clear: consumers across the region are not merely craving automation—they want AI experiences that still feel human.

SleekFlow’s recent whitepaper, AI Transformation in SEA, sheds critical light on how AI is being implemented in the region and why the next frontier isn’t about choosing between humans or machines—but about blending both.

This article explores how SEA businesses are riding the AI wave, why the human element still matters, and what’s at stake for those failing to keep up.

From hype to habit: AI is now business as usual

What was once considered futuristic is now foundational. Across Southeast Asia, AI adoption is far from experimental. In Indonesia, 87 per cent of businesses are already using AI-powered tools.

Singapore follows closely with 77 per cent, while Malaysia sees 67 per cent of its businesses integrating AI into operations. These technologies—ranging from chatbots and CRM automation to predictive analytics and omni-channel engagement platforms—are no longer optional; they’re essential for scalability and smarter operations.

And yet, despite the widespread uptake, ROI remains top-of-mind. In fact, 40 per cent of businesses said a “proven ROI” would most encourage them to invest further—suggesting that while the AI hype has normalised, real-world results are now the true north.

Also Read: How blockchain can help combat ongoing fraud in the Halal food industry in SEA

AI-powered customer experience is the new moat

The battleground for customer loyalty in Southeast Asia has shifted dramatically. According to SleekFlow, 80 per cent of businesses in the region are now deploying AI in customer service—and they’re not merely testing the waters. Satisfaction rates are high, particularly in markets where personalisation plays a significant role.

In Indonesia, 86 per cent of consumers say they’re more likely to make a purchase when offers are personalised. Malaysia follows with 80 per cent, and Singapore with 73 per cent. These figures underscore how much personalised engagement drives conversions.

Moreover, the demand for speed is rising—45 per cent of Southeast Asian consumers expect a response from businesses in under three minutes. In this context, speed, relevance, and convenience are no longer added benefits; they have become baseline expectations.

AI must feel human or consumers will walk

Here’s where the story gets nuanced.

When asked if they preferred AI or human customer agents, 41 per cent of SEA consumers answered: it depends. They recognise AI’s strengths—fast booking (70 per cent), multilingual support (66 per cent), and speedy responses (63 per cent)—but they also value emotional intelligence, personalised care, and complex problem-solving. These remain the domain of human agents.

Notably, 73 per cent of shoppers prefer businesses where AI is managed by humans. The message? Consumers aren’t afraid of AI—they just want assurance that a human is still in the loop.

Also Read: Fertile ground for partnership: How agritech boom in SEA holds a promise for Latin America

Looking ahead, SEA customers expect mobile-first experiences and ethical, sustainable AI use. Companies that ignore these signals may find their brand loyalty eroding—no matter how advanced their tech stack.

Real brands, real AI transformation

AI-powered service is no longer a niche strategy—it’s now essential. And major SEA platforms are setting the bar:

• TikTok Shop: Its Seller Assistant, an AI chatbot, helps sellers manage listings and get 24/7 guidance—cutting down human intervention and boosting platform scalability.
• Shopee: Through Shopee Live and its chatbot “Sophie,” which resolved 18 million support chats in 2023 (with an 80 per cent resolution rate), the company merges social commerce with AI.
• Lazada: Launched LazzieChat, an OpenAI-powered assistant, across Singapore, Indonesia, and the Philippines. It personalises product recommendations and boosts shopper engagement.

Even Google has entered the fray, launching a comprehensive AI shopping mode that includes an upgraded Shopping Graph, virtual try-ons, dynamic product discovery, and checkout assistants—all built with contextual intelligence at its core.

What happens to the laggards?

The divide between AI adopters and traditional businesses is growing fast—and it’s more than a tech gap. It’s a competitiveness gap.

Only 30 per cent of non-AI businesses rate their operations as efficient, compared to 80 per cent of AI-driven companies. The cost of delay is real: higher overhead, poor scalability, slower time-to-market, and reduced customer satisfaction. In a region moving this quickly, falling behind could mean falling off entirely.

Conclusion: AI isn’t replacing people, it’s reinventing experience

The big takeaway? The future isn’t AI versus humans. It’s AI with humans.

SEA consumers are sending a clear message—they’ll embrace AI, but only if it augments human connection, not replaces it. For businesses, the challenge now is to create experiences that blend intelligence with empathy, speed with sincerity.

Those who get this right will not only meet rising expectations—they’ll redefine what it means to lead in the AI era.

The time to act is now.

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Artificial Intelligence has reshaped customer service, especially for organisations trying to reduce operational costs and speed up support delivery. But while automation improves efficiency, a significant percentage of customers still want the option to speak with a real person. This preference becomes even stronger when emotions run high or the issue is complex. Businesses that overlook this reality risk weakening customer loyalty and damaging their brand experience.

A balanced AI-human support model offers a far stronger approach than fully automated systems. It ensures customers receive the speed of technology and the reassurance of human interaction when it matters most. The insights below break down why hybrid support has become essential and how businesses can implement it effectively.

Why hybrid support outperforms pure automation

AI tools are impressive, but they have a clear limit. They excel in situations that rely on rules, predefined workflows, and repetitive tasks. They struggle when customer intent becomes unclear or when emotional intelligence is required.

Many companies have adopted bots as a complete replacement for human support. The goal was understandable: lower costs and higher productivity. However, this shift also introduced new problems. Automated systems often fail to understand context, escalate issues correctly, or adapt to edge-case scenarios. Customers end up stuck in repetitive loops, frustrated, and ready to leave for a competitor.

A hybrid support model solves this by combining automation with human expertise. AI handles predictable inquiries at scale. Human agents step in for conversations that require reasoning, empathy, or negotiation. This blended approach reduces operational strain while protecting customer satisfaction.

Also Read: Creating sustainable futures: The vision of steady-state societies and still cities

Where AI adds the most value

AI becomes a powerful asset when used for tasks that demand accuracy and speed rather than judgment. Here are key areas where automation performs best:

• Repetitive and routine interactions: Questions like order updates, returns, refund timelines, password resets, and account details can easily be resolved by AI systems. These workflows follow clear paths and do not require nuanced interpretation. Automating them saves time for both customers and support agents.
• Continuous availability: Customers today expect immediate responses, regardless of time zone. For companies serving global users, 24/7 support is no longer optional. AI ensures round-the-clock availability without the need for large overnight teams.
• Handling sudden spikes in volume: Seasonal sales, promotions, viral campaigns, and new product launches often create traffic surges that overwhelm human teams. AI can manage thousands of queries simultaneously, preventing long wait times and abandoned interactions.

When used strategically, AI becomes a stabilising force in customer service operations. But relying on it exclusively leaves a major gap that only human agents can fill.

Where human agents are irreplaceable

Technology enhances customer experience, but it cannot replicate genuine human understanding. Human agents remain the backbone of strong customer relationships for three core reasons:

• Emotional intelligence and empathy: Many support situations require more than a correct answer. A customer dealing with a billing mistake, a broken product, or a missed service appointment is often stressed or frustrated. These conversations demand patience, tone control, and emotional awareness—skills no automated system can genuinely deliver. Humans can listen, interpret emotion, and respond with sensitivity. This connection is often the difference between customer retention and customer loss.

• Solving complex or multi-step issues: AI struggles with unexpected variables or issues that require negotiation or problem-solving beyond scripted flows. Human agents interpret context, ask clarifying questions, and analyse multiple possibilities before offering a solution. This adaptability is essential in industries such as finance, healthcare, travel, and technology, where problems regularly extend beyond a simple ruleset.

• Building trust and long-term loyalty: High-value customers stay because they trust the people behind a brand. A meaningful interaction with a knowledgeable and empathetic agent often does more for retention than any promotional offer. This relational value cannot be automated.

Executing a smooth AI-to-human handoff

A hybrid support strategy only works if the transition between AI and human agents is seamless. Poor handoff experiences are one of the biggest causes of customer frustration. A well-designed system includes the following elements:

• Sentiment-based routing: If a customer expresses confusion, irritation, or repeated failed attempts to resolve a problem, the system should instantly transfer the conversation to a human agent. No customer should feel trapped in an endless loop of scripted responses.
• Complete conversation history: When an agent joins the conversation, they must see everything the customer has already shared. Asking the customer to repeat their issue signals inefficiency and damages trust. A clean handoff improves first-contact resolution and shortens handling time.
• Intelligent prioritisation: Not every conversation needs a human, and not every customer issue is urgent. Smart routing categorises inquiries and directs them to the right tier of support. This reduces backlog and increases efficiency.

Also Read: How to use blockchain to fund and create a greener future

Steps to build a high-performing hybrid support model

Creating a balanced system requires more than purchasing AI software. The strategy behind the technology is what makes the difference.

• Analyse the customer journey: Review historical support tickets and identify patterns. Determine which interactions consistently require emotional support or complex reasoning and which can be automated reliably. Mapping these touchpoints helps you build a workflow that aligns with real customer needs.
• Be transparent about AI usage: Customers should always know whether they are interacting with a bot or a human. Hiding automation creates distrust. A simple notification such as “You are chatting with our virtual assistant” establishes clarity and sets expectations.
• Equip and train your support team: Human agents should view AI as a co-worker, not a threat. Give them tools that surface customer insights, past interactions, and relevant knowledge base articles instantly. Better support systems make agents faster and more accurate, improving overall service quality.

Why hybrid support has become the new standard

Automation alone cannot deliver a complete customer experience. Human agents alone cannot handle modern support volume efficiently. The most successful organisations combine both intelligently.

The goal is not to automate everything; it is to create interactions that feel relevant, responsive, and personal. When AI manages routine work, human agents have the bandwidth to focus on conversations that matter most. This leads to stronger relationships, higher satisfaction, and better long-term loyalty.

A hybrid model ensures:

• Faster response times
• More accurate resolutions
• Better emotional support
• Reduced operational costs
• Consistent satisfaction across channels

Companies that adopt this approach gain a competitive advantage because they respect what customers want: speed when possible, human connection when necessary.

Final thoughts

A well-designed AI-human hybrid system allows organisations to deliver personalised support at scale. AI handles predictable tasks with unmatched efficiency. Human agents manage the situations that define customer trust. When both elements work together, customers experience a level of service that feels smooth, reliable, and genuinely helpful.

If your business is looking for stronger support performance, improved customer satisfaction, and a more efficient workflow, adopting a hybrid approach is the most practical and effective strategy.

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Over the past decade, Singapore has emerged as one of the world’s most connected economies. Its investments in fibre networks, data centres, and cloud infrastructure have laid the foundations for a thriving digital ecosystem, one that almost every mature market in the world is chasing.

By the end of 2025, the global digital transformation market is forecast to exceed US$1 trillion (around US$1,009.8 billion), underscoring the accelerating pace of enterprise modernisation.

As businesses across Asia accelerate their transformation journeys, one thing has emerged clearly: infrastructure, which once was a solid backbone of digital progress, has now evolved to also become the springboard for intelligent innovation.

Digital transformation has matured from being a technology race to becoming a strategy for business resilience. By the end of 2025, global spending on digital technologies is expected to reach US$2.8 trillion — a figure that reflects not only the scale of transformation but also the urgency with which enterprises are modernising. In Singapore, this is evident across every sector. From financial services and logistics to manufacturing and the public sector, digitalisation is reshaping how value is created and delivered.

Infrastructure as intelligence

For years, digital infrastructure was seen as a cost centre, a means to enable connectivity. Today, it is increasingly viewed as a competitive advantage. Modern networks do far more than transmit data; they enable agility, automation, and real-time insights. The convergence of cloud computing, artificial intelligence (AI), and edge technologies is creating a new kind of digital backbone — one that learns, adapts, and scales dynamically.

For example, hybrid cloud environments powered by intelligent networks are helping enterprises move workloads seamlessly across geographies. In data-intensive industries such as finance and media, networks that are low latency make it possible to process vast amounts of data in real time, opening new possibilities for automation and analytics.

Also Read: Singapore’s workforce is facing its biggest reset yet and AI is forcing the shift

These are the kinds of capabilities that form the invisible infrastructure behind Singapore’s ambition to be a Smart Nation. And it has become a national priority too, as digital defences are being set up to protect critical infrastructure from any cyber threats.

Beyond connectivity: Building digital ecosystems

True transformation happens when infrastructure, applications, and data are integrated as one ecosystem. In Singapore, this convergence is already taking shape. Enterprises are combining connectivity with cloud-native services to build systems that are both smarter and more responsive. Financial institutions, for instance, are using AI to detect fraud faster, while logistics players are leveraging predictive analytics to manage supply chain volatility.

At the heart of these innovations lies a robust, flexible digital fabric — the interconnected networks and cloud platforms that make secure, real-time collaboration possible. As data volumes grow and applications become more distributed, infrastructure must shift from static to intelligent, capable of supporting data flows wherever they create value.

The next challenge: Bridging capability with culture

Despite widespread enthusiasm for digital transformation, many organisations struggle to deliver. Around 70% of enterprises fail to meet their digital‑transformation objectives, often hindered by cultural resistance, the pressure to demonstrate rapid ROI, and limited budgets.

Even with strong infrastructure readiness, companies still face barriers such as talent shortages and internal silos. To unlock the full potential of intelligent infrastructure, businesses must pair it with the right digital mindset, one that prioritises agility, experimentation, and collaboration.

International studies indicate that the majority of digital value is realised by transforming existing operations rather than solely by pursuing disruptive new ventures. McKinsey estimates that around 70% of digital value comes from refining existing operations and business models. Instead of chasing flashy pilot projects, companies should focus on optimising processes, distribution, and margins.

Effective outcomes increasingly depend on collaborative approaches. Technology providers, system integrators, and enterprises are jointly shaping solutions that are practical as well as innovative. In this broader landscape, organisations like Colt are witnessing how intelligent connectivity helps enable real-time data flows in finance and supports the digitalisation of manufacturing ecosystems.

Also Read: Why Singapore startups are sleeping on their secret weapon (spoiler: it’s not AI)

From foundation to advantage

As Singapore continues its Smart Nation journey, its digital infrastructure will remain a defining enabler of progress. But the focus is shifting: from building faster networks to building smarter ecosystems. The future belongs to enterprises that view infrastructure not as a utility, but as a strategic differentiator that fuels data-driven decision-making, operational resilience, and innovation at scale.

In the digital economy, connectivity is no longer enough. Intelligence is the new infrastructure, and Singapore is well-positioned to lead this next leap forward.

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Indonesia’s Ministry of Communication and Digital (Kemkomdigi) has launched an investigation into the alleged misuse of Grok AI, an artificial intelligence feature integrated into X, over concerns that it is being used to generate and distribute immoral content, including manipulated personal photos created without consent.

The probe follows preliminary findings by the ministry indicating that Grok AI lacks explicit and adequate safeguards to prevent the creation and dissemination of pornographic content derived from real images of Indonesian citizens. Authorities warn that such misuse poses serious risks to an individual’s privacy and their right to control their own image.

Also Read: Building with intention: The ethical dilemma of AI innovation and responsible creation

“Preliminary findings show that there are no specific arrangements in Grok AI to prevent the use of this technology in the creation and dissemination of pornographic content based on personal photos. This risks causing serious violations of citizens’ privacy and self-image rights,” said Alexander Sabar, Director General of Digital Space Supervision.

Kemkomdigi stressed that the digital manipulation of personal images goes beyond moral concerns, framing it as a direct deprivation of an individual’s control over their visual identity. The ministry noted that such violations can lead to psychological distress, social harm, and long-term reputational damage, particularly for women and minors.

In response, the ministry is coordinating with Electronic System Operators (PSEs) to ensure the deployment of stronger protection mechanisms. These include enhanced content moderation systems, preventive measures against the creation of immoral deepfakes, and faster response processes for reports related to privacy and self-image violations.

“Every PSE is obliged to ensure that the technology they provide does not become a means of privacy violations, sexual exploitation, or destruction of a person’s dignity,” Sabar said.

The ministry also reiterated that compliance with Indonesian laws and regulations is mandatory for all digital platforms operating in the country. Failure to cooperate or comply could result in administrative sanctions, including the suspension or termination of access to Grok AI services and the X platform within Indonesia.

Under Indonesia’s newly enacted Criminal Code (Law Number 1 of 2023), which came into force on January 2, 2026, pornographic content is explicitly regulated. Article 172 defines pornography as material containing obscenity or sexual exploitation that violates moral norms. On the other hand, Article 407 stipulates penalties ranging from a minimum of six months to a maximum of ten years’ imprisonment, or fines in accordance with the law.

Sabar added that victims of photo manipulation, immoral deepfakes, or violations of self-image rights are encouraged to pursue legal remedies, including reporting cases to law enforcement agencies or filing complaints with the ministry.

“We appeal to all parties to use imitation intelligence technology responsibly. The digital space is not a lawless space; there is privacy and the right to self-image of every citizen that must be respected and protected,” he said.

The investigation places Grok AI under growing regional and global scrutiny. Regulators in markets such as India, France, Malaysia, and Turkey have also raised concerns about the misuse of generative AI, signalling the possibility of tighter controls, feature restrictions, or even platform blocks if existing safeguards remain insufficient.

While there is no official data on Grok’s adoption in Indonesia, overall AI usage in the country is estimated to range between 59 per cent and 65 per cent. Grok, which is tied to X’s premium user base, is believed to account for only a small fraction of that figure, especially when compared to widely used tools such as ChatGPT, Google’s Gemini, and local models like Sahabat-AI, which support Bahasa Indonesia and indigenous languages. Among premium smartphone users, Samsung’s Galaxy AI reportedly records adoption levels of up to 87 per cent.

Also Read: Building AI on a foundation of accountability

The case underscores intensifying pressure on AI providers to embed ethical safeguards by design. Companies such as OpenAI and Meta already deploy strict content filters and usage policies to limit harmful outputs, while emerging techniques, including image alteration and deepfake detection via metadata and AI signatures, are gaining traction.

For Indonesia, the Grok AI investigation reflects a broader regulatory push to protect privacy, curb non-consensual deepfakes, and assert that accountability in the digital space applies equally to advanced AI systems and the platforms that deploy them.

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The narrative of Southeast Asia’s tech landscape in 2025 has become a tale of one city’s absolute dominance over its peers. Singapore-based firms have effectively cornered the market, accounting for a staggering 91 per cent of all funding witnessed by tech companies across the region.

According to the “SEA Tech Annual Funding Report 2025” by Tracxn, the city-state secured a massive US$4.7 billion in total capital throughout the year. This concentration of wealth highlights Singapore’s status as the region’s primary haven for investors during a period of global economic recalibration.

Also Read: From US$107M lows to a US$491M finish: SEA’s volatile 2025

The gap between Singapore and other regional hubs is now a chasm rather than a mere lead. Jakarta, traditionally the second powerhouse of the region, trailed far behind with just US$212 million, representing a mere 4 per cent of the total funding pool.

Other major cities, including Bangkok, Kuala Lumpur, and Ho Chi Minh City, barely moved the needle, with Bangkok raising US$61 million and Kuala Lumpur securing US$41.3 million.

This disparity suggests that investors are increasingly prioritising the mature regulatory framework and deep liquidity available in Singapore over the high-growth, high-risk emerging markets nearby.

Large-scale late-stage deals were the primary engine behind this capital concentration. Major highlights included Princeton Digital Group’s US$1.3 billion Series C round and Digital Edge’s US$640 million Series D round, both of which were anchored in Singapore. These mega-rounds demonstrate that while the region as a whole may be facing headwinds, Singapore remains a global magnet for “big ticket” infrastructure and fintech investments.

Also Read: Singapore surpasses San Francisco as world’s top hyper-growth startup hub

The city-state’s prowess is not just limited to late-stage capital; it also remains the most fertile ground for new founders. Singapore accounted for 41 per cent of all new companies founded in the region over the last two years, significantly outpacing Jakarta’s 7 per cent. With institutions like SEEDS Capital and Integra Partners leading the charge in early-stage investments, Singapore has built a self-sustaining ecosystem that its neighbours are currently struggling to replicate.

Singapore is acting as the region’s giant lighthouse, drawing in nearly every dollar of capital while the rest of the Southeast Asian coast remains largely in the dark.

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The modern data centre is under unprecedented pressure. The surge of AI-driven applications, e-commerce data, and the rollout of 5G has created an insatiable demand for processing power. However, with this comes a significant challenge: heat. As chip densities increase and GPUs become more power-hungry, traditional air-cooling systems can no longer keep pace. Today, cutting-edge data centre racks can consume over 20,000 watts, pushing these systems to the brink.

In Southeast Asia, where digital infrastructure is rapidly expanding, data centres are under immense pressure to deliver faster, more efficient performance. Having spent years at the intersection of technology and infrastructure, I’ve seen firsthand how these advances have exposed a critical issue: our existing cooling systems are no longer sustainable. The future of data centres—and Southeast Asia’s digital revolution—requires a new approach. Liquid cooling is no longer a luxury; it’s an essential solution to the relentless heat generated by today’s technological innovations.

Why liquid cooling is crucial for AI and data centres 

AI’s rapid growth has revolutionised industries but has also introduced a critical heat management challenge. High-performance GPUs, the backbone of AI and machine learning applications, produce excessive heat that air-cooling systems struggle to handle. This inefficiency leads to higher operational costs and raises concerns about sustainability and system reliability.

Liquid cooling represents a transformative shift. By efficiently transferring heat away from components, it allows for higher rack densities and minimises the risk of system failure due to overheating. Liquid cooling can make chips run more efficiently and release their potential performance.This makes liquid cooling indispensable for mission-critical AI applications, where uninterrupted performance is key.

We see this shift gaining momentum across the industry. For instance, NVIDIA’s latest Blackwell GPUs are designed with liquid cooling in mind, reflecting a broader industry move towards more advanced cooling solutions. Liquid cooling systems have proven their ability to deliver improved thermal management, reduced energy consumption, and optimised space utilisation.

Southeast Asia’s advantage: A clean-slate approach

Meanwhile, Southeast Asia’s digital transformation offers a unique advantage. As e-commerce booms and 5G rolls out across the region, countries like Indonesia—with over 200 million projected internet users by 2025—are at the forefront of this growth. Unlike established markets burdened by legacy infrastructure, Southeast Asia has the opportunity to build from scratch, integrating advanced technologies like liquid cooling from the outset.

Also Read: Can alternative proteins help build a more secure and sustainable food system?

This clean-slate approach allows data centres to meet soaring demand without the inefficiencies and environmental costs associated with outdated systems. We’ve seen how incorporating liquid cooling from the ground up enables greater efficiency and scalability for future technologies, giving Southeast Asia a competitive edge in the global digital economy.

Sustainability and smarter management

As Southeast Asia’s tech infrastructure grows, so does its environmental impact. Reducing energy consumption is not only a business imperative but a necessity for governments and companies aiming to meet stringent environmental goals. Liquid cooling plays a pivotal role in addressing these challenges, offering up to 40 per cent energy savings compared to traditional air-cooling systems. These energy reductions help data centres lower both operational costs and their carbon footprint, making them more sustainable.

Incorporating AI-driven management systems into liquid cooling solutions further optimises energy use based on real-time conditions. This smart management enables data centres to adjust cooling dynamically, predict potential failures, and optimise water usage, paving the way for a more efficient, future-proof infrastructure.

The future of data centres in Southeast Asia

The demand for faster, more powerful data processing will only intensify as AI, 5G, and digital services continue to evolve. Southeast Asia’s relatively recent entry into the data centre market presents a unique opportunity: the chance to embrace cutting-edge technologies like liquid cooling without being weighed down by outdated infrastructure.

Liquid cooling is not just a solution for today’s high-performance systems—it is a prerequisite for the future. The energy savings, performance enhancements, and environmental benefits make it the ideal cooling solution for next-generation data centres. Businesses that invest in liquid cooling today will be well-positioned to lead the region’s digital transformation.

The question isn’t whether Southeast Asia is ready for liquid cooling—it’s whether it can afford not to adopt it. In an increasingly data-driven world, the choices made today will define the region’s ability to compete tomorrow. The future belongs to those who embrace the most efficient and sustainable technologies available now.

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

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In Southeast Asia, the old assumption that companies must choose between profitability and impact no longer holds. The most successful ventures are showing that in emerging markets, commercial growth and social outcomes often reinforce each other.

When eFishery first introduced smart fish feeders in Indonesian ponds, sceptics doubted smallholders would adopt such technology. Yet adoption spread quickly, demonstrating that solutions addressing basic needs can scale commercially while improving livelihoods. This kind of dual outcome, revenue growth alongside measurable community benefit, is becoming one of the region’s defining opportunities.

Across agritech, healthtech, and edutech, founders are proving that purpose fuels profit. Here’s how.

Founder Stories: The Double Bottom Line in Action

Agritech: eFishery’s US$200M Bet on Smallholder Farmers

The problem is clear. Around 40 per cent of aquaculture feed in Southeast Asia is wasted (FAO), keeping farmers in cycles of poverty. Feed can consume up to 60 per cent of a farmer’s income, leaving little margin for resilience.

The solution combines IoT sensors with AI-driven feeding. This reduces feed costs by up to 20 per cent while boosting yields by about 30 per cent.

The results are significant:

• 250,000+ livelihoods improved
• 5M tons of CO₂ avoided through efficient feeding
• A strong signal that investors are backing models that align profitability with farmer well-being

eFishery illustrates how tackling one inefficiency—feed waste—can generate impact at scale: higher incomes for smallholders, reduced environmental pressure, and a stronger supply chain for one of SEA’s core food sources.

Healthtech: Doctor Anywhere’s prescription for equity

Healthcare in SEA has long been defined by gaps: distance to clinics, affordability, and shortages of trained professionals. For rural families, even basic check-ups can mean a day’s travel and high costs.

Doctor Anywhere’s pivot from corporate wellness into rural telehealth during COVID-19 showed how digital tools can bridge these divides. The platform now delivers teleconsultations at around US$5, roughly 40 per cent cheaper than offline visits in parts of Indonesia.

“If you can’t reach a clinic in Borneo, the doctor should come to you. Our tech makes healthcare borderless.” – Lim Wai Mun, Founder of Doctor Anywhere

Its impact is measurable:

• 5M users accessing US$5 teleconsultations
• 40 per cent cheaper than offline visits in Eastern Indonesia
• US$140M Series C at 2.5X valuation jump (2022)

This case highlights a broader principle: the strongest healthtech models don’t just digitise existing systems. They reimagine them for contexts where scarcity, not abundance, is the norm.

Also Read: Driving social impact with tech in Southeast Asia: Building for outcomes, not optics

Why impact measurement wins trust

Investors increasingly expect startups to measure outcomes beyond revenue. It is no longer enough to show financial KPIs; impact dashboards are becoming part of the due diligence process.

Take GrowSari, a B2B platform in the Philippines serving sari-sari stores. By tracking metrics such as income growth (15 per cent for 50,000 stores), GrowSari demonstrated that its platform directly improved livelihoods. This, in turn, helped it secure funding and build credibility with partners.

The lesson is simple: measurable outcomes create trust. Tools like B Corp certification and IRIS+ standards provide shared language for investors and startups to align. Startups that adopt these frameworks early differentiate themselves in an increasingly competitive funding environment.

“Investors used to ask, ‘What’s your EBITDA?’ Now they demand ‘Show us your impact dashboard.’” – Shiyan Koh, Partner at Hustle Fund (early backer of GrowSari)

Investor perspectives: The case for capital

“The best companies solve problems so essential, their business model becomes antifragile.” – Peng T. Ong, Co-Founder of Monk’s Hill Ventures

Why are investors leaning into impact?

• Regulation: Indonesia’s SDG Indonesia One has mobilised over US$3 billion for sustainable development, much of it climate-focused.
• Consumers: Nearly three-quarters of SEA millennials say they prefer ethical brands.
• Performance: Studies show impact startups had a 22 per cent higher survival rate during COVID-19.

The logic is clear: ventures solving essential problems are less vulnerable to downturns. They build resilience because their markets — health, education, food, energy — remain critical regardless of economic cycles.

Also Read: Report: Singaporeans are among the most optimistic about the economic impact of AI

Green shoots: Funding momentum

The data reflects this shift.

Impact startup funding grew from US$150M in 2020 to US$850M in 2024, a 467 per cent increase.

The number of deals nearly quadrupled, showing deepening investor appetite.

These deals span cleantech, agritech, inclusive fintech, and healthtech—indicating broad demand across sectors.

This momentum suggests impact is not a niche play. It is increasingly becoming the mainstream thesis for venture and growth capital in the region.

The road ahead

“Profit is oxygen, but purpose is our heartbeat. Without both, you don’t have a business—you have a spreadsheet.” – Steve Melhuish, PropertyGuru Founder & Impact Investor

The next wave of SEA innovation will be defined by whether startups can align profitability with measurable outcomes. For founders, this means baking impact into KPIs from the start, whether it’s farmer incomes, patient access, or school retention rates. For investors, it means embedding metrics like IRIS+ into due diligence, alongside EBITDA and ARR.

Funding models that value both profit and purpose are no longer fringe experiments. They are setting new benchmarks for what successful businesses look like in Southeast Asia.

The message is clear: in emerging markets, the smartest capital is chasing ventures where impact and profit are the same story.

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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.

Enjoyed this read? Don’t miss out on the next insight. Join our WhatsApp channel for real-time drops.

Image courtesy: DALL-E

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For a long time, vision boarding was dismissed as a soft practice — something aesthetic, emotional, and often unserious. Cut out magazine clippings. Pin a dream house. Manifest abundance. Hope the universe listens.

But in recent years, vision boarding has quietly re-emerged — not as a trend, but as a response. A response to speed. A response to overload. A response to a world where execution is no longer the bottleneck — direction is.

Today, many people are moving faster than ever, yet feel more stuck than they did a decade ago. They are productive but uncertain. Busy but misaligned. Surrounded by tools, yet unsure which ones matter. And increasingly, the problem isn’t capability — it’s clarity.

This is where vision boarding, redefined, starts to matter again.

When everything accelerates, thinking becomes fragile

Artificial intelligence has fundamentally changed how fast we can move from idea to action. Writing, designing, analysing, automating — tasks that once took weeks can now happen in hours, sometimes minutes.

Speed, however, has a side effect.

When execution becomes effortless, it exposes a deeper weakness: Many people have never been trained to think clearly about what they are building, why they are building it, and who they are becoming in the process.

Decision fatigue is no longer an abstract concept. It’s daily lifeWhat should I focus on this quarter? What opportunities do I say yes to? Which version of success actually fits my life? Without a strong internal reference point, faster tools don’t free us — they fragment us.

And this is where vision boarding has evolved from a motivational exercise into something far more strategic.

Vision is not about dreams — it’s about direction

The most misunderstood thing about vision boarding is the assumption that it’s about dreaming.

In practice, the most effective form of visioning has very little to do with fantasy. It’s about conceptualisation.

Before anything meaningful is built — a company, a career shift, a body transformation, a creative identity — there is always a quiet phase that comes first. A phase where ideas are held loosely, articulated imperfectly, and refined through reflection.

Thinking. Verbalising. Then acting. This sequence matters.

Many people skip the first two steps because they feel inefficient. They want action. They want momentum. But action without conceptual clarity creates movement without meaning — progress that looks impressive but leads nowhere specific.

Vision boarding, at its core, is simply the discipline of slowing down long enough to decide what kind of life you are actually designing.

Also Read: Founder income: The unspoken truth about wealth, autonomy, and design

From goals to identity: The rise of the “NextSelf”

Traditional goal-setting focuses on outcomes: Revenue targets, follower counts, job titles, and timelines. These can be useful, but they are also fragile. When circumstances change, goals collapse. When motivation dips, goals feel heavy.

A more resilient approach is identity-based visioning.

Instead of asking, “What do I want to achieve?” The better question becomes, “Who am I becoming?”

This idea of a “NextSelf”, a future version of you defined by values, boundaries, rhythms, and priorities, changes how decisions are made in the present.

When visioning is anchored in identity:

• Opportunities are filtered, not chased.
• Trade-offs become clearer.
• Daily actions feel coherent rather than reactive.

The future stops being aspirational and becomes directional.

You don’t act in hopes of becoming someone someday. You act as the person you are designing yourself to be.

Why static vision boards no longer work

The old version of vision boards assumed a stable world. One where you could map a five-year plan and reasonably expect the terrain not to shift dramatically beneath you.

That assumption no longer holds.

Careers pivot faster. Industries mutate. Personal priorities evolve. Many people experience identity drift — achieving externally while feeling internally disconnected from the life they are living.

Static vision boards fail because they freeze desire in time.

Modern visioning needs to be iterative, reflective, and context-aware. It must allow for revision without guilt. It must support multiple time horizons — not just “someday,” but the next three months, the following year, the next decade.

In this sense, vision boarding starts to resemble a mental operating system rather than a collage.

Where AI fits — and where it shouldn’t

AI does not replace vision. If anything, it highlights its absence.

When people lack clarity, AI amplifies confusion. When people have intent, AI becomes a powerful ally.

Used thoughtfully, AI can support visioning by:

• Helping articulate abstract ideas into language.
• Visualising possibilities that are hard to imagine alone.
• Prompting reflection through structured questioning.
• Acting as a guide through the process, rather than a generator of answers.

The most effective framing is not AI as creator, but AI as companion.

Think of it like a guided scrapbook — still personal, still human, but with a gentle structure that helps ideas move from vague to visible, from emotional to executable.

Importantly, the clarity still comes from the individual. AI simply helps surface it.

Also Read: Designing spaces for longevity: How everyday environments shape health in Asia

Manifestation, revisited (without the mysticism)

Manifestation is often misunderstood as passive optimism: Think positively, and good things will happen.

In practice, manifestation has always been practical.

You think deliberately. You verbalise intentionally. You act consistently. Vision boarding formalises this process.

By externalising thought — writing it down, visualising it, speaking it aloud — people reduce internal noise. Decisions become easier because they are measured against something larger than mood or impulse.

This isn’t about controlling outcomes. It’s about aligning behaviour.

When vision is clear, action follows naturally.

Vision as a skill, not a personality trait

One of the most damaging myths is that some people are “visionary” and others are not.

In reality, visioning is a skill — and like any skill, it can be learned, practised, and refined.

Those who appear decisive are often not more confident; they are simply clearer. Those who move fast are often not more capable; they are simply less distracted.

As the world grows noisier, the ability to design one’s future deliberately – rather than inherit it by default – becomes a form of leverage.

Not just for founders or creators, but for anyone navigating modern life.

Designing before doing

The irony of our era is that we have more tools than ever to build anything – yet fewer moments to ask whether we should.

Vision boarding, in its evolved form, is not about predicting the future. It’s about reducing noise in the present.

It creates a pause between stimulus and response. A space where identity leads action, not the other way around.

In a world obsessed with speed, that pause might be the most strategic move of all. Because the future doesn’t belong to those who move fastest.

It belongs to those who know where they are going.

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December’s funding rebound offers a useful, but nuanced, signal for Southeast Asia’s tech ecosystem. The 49.71% month-on-month jump is less a return to exuberance and more an affirmation that capital is selectively re-engaging where conviction is highest.

Airwallex’s US$330M round did the heavy lifting, underscoring a clear reality: late-stage capital has not disappeared, but it is now reserved for category leaders with proven global relevance, strong governance, and clear paths to scale.

Strip out that single deal, however, and the picture becomes more instructive. The steady flow of mid-sized and early-stage rounds suggests investors are rebuilding the pipeline rather than chasing momentum. With nine early-stage and six seed deals in December, VCs appear more comfortable underwriting future optionality than stretching valuations at the growth stage. This aligns with a broader regional reset in 2025, where discipline replaced speed and capital efficiency became non-negotiable.

The year’s extreme volatility—from February’s US$107M trough to July’s US$1.67B spike—reflects an ecosystem recalibrating after years of excess. The encouraging takeaway is the Q4 climb. October through December shows sequential recovery, hinting that the market may have found a more stable floor.

Heading into 2026, the message for founders is clear: capital is available, but only for those who can demonstrate resilience, clarity of execution, and realistic ambition in a more sober funding environment.

REGIONAL

Nadiem Makarim indicted in US$125M Chromebook graft case: The Chromebook procurement process between 2019 and 2022 failed to meet basic planning and procurement standards. Crucially, the devices were found to be essentially unusable certain regions due to inadequate infrastructure.

Manus to join Meta in acquisition deal: Manus AI positions itself as an “execution layer” for AI, transforming advanced capabilities into scalable and reliable systems that can perform end-to-end work in real-world settings. Its agent has already processed 147T+ tokens and powered 80M+ virtual computers in just a few months.

Hong Kong’s Buy&Ship secures US$12M to scale AI-driven cross-border commerce: Investors include MLC Ventures, MemeStrategy, Cool Japan Fund, and Altara Ventures. Funding backs AI automation, Southeast Asia growth, US expansion plans and early steps toward IPO for cross-border e-commerce platform globally.

Singapore’s data centre firm DayOne bags over US$2B Series C: Investors include Coatue and the Indonesia Investment Authority. Capital will be used to develop its Finland platform in Lahti and Kouvola, and to grow its presence in Singapore, Johor, Batam, Thailand, Japan, and Hong Kong.

Iterative, Antler invest in US$1M round of Singapore AI startup i10x: i10X offers a workspace that lets users access multiple AI models and tools in one platform. The funding will support product development, infrastructure expansion, and team growth.

Vietnam’s digital tech sector hits US$198B revenue: The sector reported a 26% rise from 2024 and 16% above the annual goal. Its contribution to GDP reached nearly US$40.9B, up 10% YoY. Hardware and electronics exports hit US$178B, up 35% from 2024 and 12% higher than targeted.

FEATURES & INTERVIEWS

From US$107M lows to a US$491M finish: SEA’s volatile 2025: The full-year funding trajectory for 2025 was defined by extreme volatility. The region experienced a dramatic peak in July 2025, when total funding reached a staggering US$1.67B, a figure nearly triple the next highest month.

INTERNATIONAL

Airwallex to invest US$234M in Netherlands: The firm said it will expand its Amsterdam team by 60%, bringing the local headcount to roughly 70 by the end of 2026. Airwallex provides a platform for businesses to handle international payments and multi-currency accounts.

Zomato fires 5,000 delivery workers monthly over fraud, CEO says: Deepinder Goyal said many terminations are related to repeated fraud, such as delivery partners falsely marking food as delivered or failing to return change to customers. He also said 150K-200K gig workers also leave the company voluntarily each month.

Chinese cyberattacks on Taiwan hit 2.6M a day: According to the island’s National Security Bureau, sectors such as energy, emergency services, and hospitals saw the largest YoY rises in attacks. They included distributed denial-of-service and man-in-the-middle techniques, aiming to steal information.

Self-driving tech, AI take centre stage at CES as automakers dial back EV plans: Just as automakers have hit the brakes on EV plans and look for their next money maker, a slew of auto suppliers and startups are lining up to show off their latest autonomous vehicle hardware and software.

South Korea’s labour minister rebukes Coupang over data breach: The online retailer faced scrutiny in a parliamentary hearing after it reported a breach affecting 33.7M customers. The Minister Kim Young-hoon linked the incident to what he called a pattern of alleged cover-ups at Coupang.

France, Malaysia probe xAI’s Grok over sexualised deepfakes: The probes follow similar condemnation from India, which ordered X to restrict Grok from producing obscene or illegal content and warned of potential loss of legal protections if action is not taken within 72 hours.

SEMICONDUCTOR

Trump orders cancellation of US$2.9M chip deal on security grounds: The order targets HieFo’s purchase of chip and wafer fabrication operations from Emcore, announced in May 2024. It requires HieFo to divest the technology within 180 days due to “credible evidence” that the current owner is a citizen of China.

Taiwan indicts ex-TSMC engineer, others in 14nm chip trade theft: The accused include Chen Li-ming, a former TSMC engineer, a current TSMC employee surnamed Chen, and a Tokyo Electron employee surnamed Lu. They are charged with reproducing trade secrets and destroying evidence.

AI demand drives chip prices higher, lifts Samsung, Micron: Chipmakers have shifted production towards high-bandwidth memory for AI servers, reducing supply for other products such as flash chips for USB drives and smartphones. Some memory chip prices have more than doubled since February 2025.

Nvidia debuts open-source AI tools for autonomous vehicles: Alpamayo is a suite of open-source AI models, simulation tools, and datasets to support autonomous vehicle (AV) development. Nvidia said its new tools can be adapted for use in AV stacks and may help accelerate level 4 autonomy.

AI

AI adoption in Southeast Asia: Balancing automation gains with the rising threat of cyberattacks: As AI and edge automation scale across Southeast Asia, enterprises must secure distributed infrastructure against AI-driven and quantum-era threats.

Why AI startups across Southeast Asia are shipping themselves into churn: AI startups in the region ship rapidly, but users can’t keep up. The resulting velocity-comprehension gap erodes trust, predictability, and retention—unless founders slow changes, align UX, and communicate mental models.

The Agency: AI-augmented development in action: A solo founder plus seven AI agents built a near-beta e-commerce platform in eight days, proving AI agencies enable choreography, faster decisions, scalable product development, and a new team model.

Singapore’s workforce is facing its biggest reset yet and AI is forcing the shift: From finance to creative roles and frontline operations, AI tools are increasingly woven into daily workflows. Yet a growing gap remains between the pace of adoption and the readiness of the workforce to use these tools effectively.

The dawn of housing abundance: Why AI will collapse construction costs by 90%: A full supply-chain analysis shows AI and robotics could slash construction costs 70-90%, cut build times 75%, and shift housing scarcity from economics to policy through labour and energy automation.

THOUGHT LEADERSHIP

Meta × Manus: The misread AI deal: Meta bought Manus not for smarter models, but for execution scars—hard-won reliability, failure recovery, and trust at scale—avoiding reputational risk of relearning real-world agent mistakes across billions of users globally.

How startups and VCs can propel Indonesia’s energy transition: Amid climate urgency, ASEAN’s digital growth is driving surging energy demand, especially in Indonesia, creating a massive opportunity for renewable energy, data centres, and climate-tech entrepreneurs to replace fossil fuels.

Asia’s US$4T tokenisation boom: Why the region will lead the global financial revolution by 2030: Asia is leading tokenisation by pairing mobile-first markets with regulation to move programmable finance into production.

How to use blockchain to fund and create a greener future: With a blockchain-based recycling programme, one can earn tokens in exchange for dropping off recyclables like plastic containers, cans, and bottles. It’s already working in Northern Europe.

Stop making it yours, make it everyone’s victory: The founder’s greatest role is not to be the smartest person in the room, but to be the Chief Stakeholder Manager, who ensures that every essential person is maximally motivated because they know, without doubt, that your company’s success translates directly into their success.

The classroom: An untapped testbed for human-centric AI: As SEA works to build strong AI ecosystems, responsible edutech is poised to become a foundation for long-term digital growth. The World Economic Forum finds that technology skills, including AI, are expected to see rapid growth in demand.

Creating sustainable futures: The vision of steady-state societies and still cities: Discover the transformative vision of steady-state societies and still cities, and how they can create sustainable futures for our planet and communities.

The post Ecosystem Roundup: SEA’s volatile 2025 — Funding swings, Nadiem Makarim case, Meta–Manus deal appeared first on e27.

i10X, a Singapore-based startup that enables users to access the world’s most powerful AI models through a single platform, has raised US$1 million in a pre-seed funding round.

The capital injection was led by a group of early-stage investors, including Iterative, Antler AI Disrupt, and PPR Ventures, marking a significant milestone for the startup as it seeks to scale its product and operational infrastructure.

Also Read: The AI revolution in emerging markets: Local models, global impact

The startup intends to utilise the newly raised funds to accelerate product development, expand its technical infrastructure, and support team growth. While headquartered in Singapore, i10X also maintains an office in Berlin, reflecting its ambitions for an international footprint.

Founded by Patrick Linden (co-founder of match.asia and Deep Green Group), Rene Linden (founder of Blue Zone Tech GmbH and co-founder of Deep Green Group), and Pawel Netreba (co-founder of Bfab and former executive at Foodpanda), i10X operates as a unified AI workspace, allowing users to access a diverse range of AI capabilities through a single interface.

The platform currently aggregates more than 500 specialised AI agents and integrates major foundational models such as ChatGPT, Claude, and Gemini.

The pre-seed round validates i10X’s approach as a “meta-layer” for AI tools, addressing fragmentation in subscriptions and workflows. It positions the startup to scale in a competitive Singapore hub, where AI investments are surging, with plans for infrastructure growth and team expansion.

In terms of market positioning, i10X claims to serve 100,000+ users.
This early traction highlights its potential to capture market share from siloed providers.

Also Read: The AI-first era: Why the model is the new runtime and how Asia can lead

i10X disrupts AI access by bundling top models like GPT, Claude, Gemini, and Grok, plus specialised agents for tasks like SEO, code review, and image generation, into one US$25/month workspace. Users conserve up to 90 per cent on costs compared to US$385/month for separate subscriptions, eliminating logins and tab-switching for seamless productivity. Features like real-time model comparisons and unlimited usage target professionals, creators, and startups, simplifying adoption beyond tech-savvy users.​

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