Today’s workforce is undergoing rapid transformation. As AI reshapes every industry, organisations and employees are discovering new ways of working, creating a need for different professional skills and knowledge. For employees, this has both opened opportunities and sparked anxiety.

Many are experiencing FOBO (Fear of Being Obsolete), with nearly half of professionals worrying their skills will be outdated within five years. At the same time, 94 per cent say they would stay longer at an organisation that invests in career development, showing that up-skilling opportunities are a top priority for professionals.

Yet, despite the necessity and demand for learning, skills gaps remain from digital fluency to problem-solving and adaptability. This work landscape is proving to be particularly challenging for Gen Z, who are newer to the workforce and must learn foundational professional skills at a time of rapid change. Older employees may also find this integration of new technology overwhelming and need support with digital skills.

The challenge for organisations is clear: provide employees with the learning support they need to prepare for the future of work. Edutech offers a pathway to achieving this goal by delivering scalable, engaging, and personalised learning opportunities tailored for modern employees.

Drive continuous up-skilling and adaptability with micro-learning

With AI accelerating the pace of change, organisations can no longer afford to only deliver employee training in all-day sessions once or twice per year. Instead, edutech tools enable managers to embed learning into the flow of everyday work with micro-learning. Mobile-friendly and bite-sized training formats ensure learning can happen anytime, anywhere, and are especially appealing to Gen Z as digital natives. These sessions are easier to fit into employees’ busy schedules without disrupting work routines, while also making learning a continuous process that can be quickly adapted according to changing needs.

Micro-learning can be designed to help employees build skills and knowledge step-by-step as they need it. This lets employees see the relevance of the training right away, which is a key factor in keeping learners engaged and helps employees avoid information overload.

Also Read: The future of edutech: Personalising learning for all

Edutech can also make it easier for employees to track their learning progress, filling knowledge gaps and developing new skills at their own pace. For employers, integrated reporting helps track participation across training sessions, identify skill gaps, and refine future learning strategies. With full visibility of their workforce’s strengths and weaknesses, and how they respond to the training in real time, trainers can continuously adapt their approach to be more efficient and impactful.

Add interactivity to make learning engaging and effective

Traditional training methods like long modules, static slide decks, and one-way seminars often fail to keep employees motivated. With edutech, trainers can design learning experiences that are interactive, using gamification, real-time feedback, and adaptive learning paths that make sessions memorable and effective.

In fact, research has shown that interactive learning lowers employee attrition rate by 37 per cent.

A new innovative approach to training doesn’t need to take a lot of extra time or effort, either. Organisations can use AI to transform existing training materials into interactive or even gamified experiences. AI-enhanced edutech can also make it easier to personalise learning, giving employees highly relevant training that’s suited to their needs and learning styles. With the right tools, even compliance training or technical refreshers can become experiences employees look forward to.

Encouraging collaboration and knowledge sharing

Beyond individual learning, an AI-ready workforce requires collaboration and collective problem-solving. Peer-to-peer learning and knowledge exchange sessions can be a powerful way to connect teams while promoting learning. However, many employees would hesitate to give a presentation to their colleagues even with valuable information, simply for fear of boring their coworkers.

Edutech platforms can help professionals turn these dry sessions into exciting and energising activities by using friendly competition or collaborative challenges. Session hosts can test their coworkers’ knowledge with gamified quiz questions, and use live polls, Q&As, and brainstorming to ensure everyone has a voice, even in hybrid or global teams. Employees can also use AI tools to create these peer learning sessions, helping them build AI skills at the same time.

Also Read: Edutech in SEA is ripe for acceleration. This is why they can help build a more inclusive society

Preparing today for tomorrow’s workforce

As AI transforms industries at a lightning-fast pace, the workforce must evolve just as quickly. Edutech can play a crucial role in this transformation by making learning engaging, accessible, and collaborative, and enabling organisations to deliver it at scale across their workforces.

Organisations that invest now in embedding edutech into their talent strategies will not only be better equipped to future-proof their workforce; they can also unlock new levels of productivity, retention, and innovation. Ultimately, the intersection of AI and edutech is about empowering people with the confidence, curiosity, and collaboration skills they need to thrive in the years ahead.

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In the creator and startup world, “community” has become a buzzword.

Everyone wants one. Creators launch Telegram groups. Founders open Slack channels. Professionals start networking circles.

But most communities don’t monetise. And it’s not because of low engagement. It’s because there is no economy running behind them.

At our recent “Community That Converts” session, this pattern became obvious. The room was filled with creators, early-stage founders, and corporate professionals trying to pivot. They didn’t lack ambition. They didn’t lack skill. Many of them already had audiences.

What they lacked was structure.

A group is not an ecosystem

There’s a misconception that if you gather enough people in one place, value will naturally circulate.

It doesn’t. A group is a container. An ecosystem is infrastructure.

An ecosystem has:

• Defined roles.
• Defined value propositions.
• Defined price points.
• Defined outcomes.
• Defined pathways for exchange.

Without these, what you have is a connection. Not commerce.

And connection alone is not sustainable.

Even charities need funding to operate. Even volunteer-driven movements require resources. In today’s economy, value is transacted through money. If no monetary exchange exists, sustainability becomes fragile.

The hard truth is this: If your community has no internal economy, it will eventually stall.

The “more content first” trap

One recurring belief we encountered was this: “I need more content first.” More posts. More reach. More followers. But content amplifies what already exists.

If the value proposition is unclear, more content amplifies confusion. If the offer is undefined, more visibility magnifies the gap. People cannot pay for what they do not understand.

And many community builders avoid pricing not because they are unsure of their audience, but because they are unsure of their own value.

Also Read: Customer churn analysis: How can startups get it right?

Monetisation is not hard selling — it is a measurement

Monetisation is often framed emotionally, as something uncomfortable or aggressive. But monetisation is simply an exchange of value transacted through money. Money measures clarity.

If no one is willing to pay, one of three things is usually happening:

• The outcome is vague.
• The positioning is weak.
• The offer is undefined.

You cannot expect payment without a price tag. You cannot expect sustainability without structure.

Consider this in professional terms. You do not pay an intern a manager’s salary. You do not pay a junior consultant a partner’s rate. Price is determined by positioning, experience, outcome, and brand equity.

The same applies to communities.

If members do not know:

• What they are offering,
• What problem do they solve?
• What outcome do they deliver?
• What they charge,

There can be no internal economy. And without economy, there is no conversion.

From individual hustle to layered ecosystems

A monetisable community is not about everyone paying one central figure. It is about enabling structured value exchange within the ecosystem.

Imagine a business-focused environment that includes:

• A strategist.
• A videographer.
• A photographer.
• A PR consultant.
• A lead generation specialist.
• A copywriter.

Each has a defined value proposition. Each has pricing. Each understands positioning.

When someone in the ecosystem needs support, they do not go outside. They transact within. That is when a community becomes infrastructure. That is when it converts. The platform itself becomes the enabler of value exchange.

Belonging is necessary, but directional

Belonging matters. But belonging without direction becomes noise.

Communities thrive when members share a similar outcome. An investment-focused group works because members aim for capital growth. A health-driven group works because members prioritise wellbeing. A business-focused ecosystem works because members want leverage, revenue, and growth.

The shared ambition defines the economy. Not just shared interests, shared direction.

Also Read: From bridge rounds to global awards: Startups across Asia keep building

Why most communities fail

Most communities fail because they are built emotionally, not structurally.

They prioritise:

• Inclusiveness without tiers
• Engagement without offers
• Networking without pricing
• Connection without defined outcomes

It feels good initially. But without an economic layer, energy dissipates. The most sustainable communities are both inclusive and exclusive. Inclusive in knowledge-sharing and access. Exclusive in-depth, commitment, and paid tiers.

Open the front door. Structured inner rooms. Free distribution. Paid progression.

That structure is what enables revenue, confidence, clarity, and leverage — not just for the founder, but for the members themselves.

The blueprint: What makes a community convert

A converting community requires five foundational elements:

• Clear value proposition: Members must know exactly what they offer and to whom.
• Defined outcomes: The community must rally around a specific ambition or transformation.
• Structured pricing: Offers must be priced clearly. No ambiguity. No hidden discomfort.
• Tiered access: Free access for exposure. Paid tiers for depth and accountability.
• Facilitated exchange: The platform actively enables members to transact within the ecosystem.

When these layers exist, monetisation is not forced. It becomes natural. Because value is visible.

The bigger shift

The creator economy is maturing. Visibility is abundant. Content is easy. AI compresses execution.

What differentiates sustainable founders now is not output. It is ownership. Ownership of:

• Audience channels.
• Pricing structures.
• Ecosystem design.
• Internal economies.

A large audience without structure is fragile. A smaller, well-architected ecosystem is durable.

A community that converts is not about building a room full of people. It is about building a marketplace of defined value.

And once value can be exchanged clearly, sustainably, and repeatedly, conversion is no longer accidental. It is engineered.

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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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Yesterday, while grabbing coffee after church, a friend vented to me, “Aleks, why does my dad’s generation trust AI-generated influencers so much? They treat them like real people with credible opinions, but won’t listen when I tell them to look for actual facts.”

It instantly hit me: the marketing world is facing the exact same problem. There’s a massive disconnect between what we think AI is doing and what the audience actually feels. Recent Braze research highlighted by MarTech proves this point perfectly: while 93 per cent of marketers are convinced AI helps them understand customers better, only 53 per cent of consumers feel brands accurately predict their needs.

We find ourselves in a “high-capability, low-trust” paradox. While marketing teams are sprinting ahead with AI adoption, consumers remain deeply sceptical about how and why brands are using these tools.

The core issue isn’t a technology problem; it’s a trust problem. And for brands looking to scale across diverse markets in Asia and beyond, realising that difference is the key to survival.

The rise of the AI intermediary

The implications of this trust gap are profound. Today, 19 per cent of consumers are already using AI intermediaries to interact with brands, a number expected to surge to 46 per cent in the near future. However, more than half of consumers expect brands to use AI in self-interested ways (like cutting costs) rather than to actually improve the customer experience.

When your customers view your technology as a barrier rather than a benefit, visibility and value clarity matter more than ever. Marketers are no longer just optimising for search results or social algorithms; they are optimising for how an AI assistant interprets, filters, and recommends their brand.

This perception gap cannot be solved with better internal dashboards or more efficient media buying alone. It requires transparent, tangible value demonstration. The customer needs to see and feel how AI makes their experience better.

Enter creative differentiation: The META’s perspective

How do brands bridge this gap? The answer lies in moving away from algorithmic homogenisation and leaning heavily into what Meta defines as creative differentiation.

Consumers don’t want to feel targeted by a machine; they want to feel understood by a brand. For example, in our company, SOMIN, we recognise that as the most powerful application of AI, which isn’t finding cheaper ways to serve the same generic ad — it’s using AI to fuel ad diversification and rapid content expression development.

Also Read: When AI stops being a feature and starts being infrastructure

When brands rely on a single, rigid visual or message, ad fatigue sets in, and the AI comes across as a cold, calculating retargeting tool. By introducing ad diversification, brands can break out of this trap. We use AI-powered insights to analyse audience behaviours, motivations, and cultural nuances, allowing brands to develop a wide array of tailored “content expressions.”

This means a single campaign can dynamically present different visual cues, messaging angles, and ad formats based on what genuinely resonates with a specific, hyper-local audience segment.

When AI is used to drive creative differentiation, the consumer experience shifts dramatically. Instead of feeling stalked by repetitive, self-serving corporate messaging, consumers are served varied, highly relevant content that speaks to their specific pain points and interests. The AI stops feeling algorithmic and starts feeling authentic.

The path forward

The brands that succeed in the next era of digital marketing will be the ones that can explain their AI usage through actions, showing how it improves customer outcomes rather than just internal operational efficiency.

As the MarTech data suggests, moving fast breaks things, and right now, it’s breaking customer trust. Rebuilding that trust requires connecting AI capability with genuine cultural relevance. By embracing diversification and prioritising diverse content expressions, brands can finally prove to their customers that AI isn’t just about the bottom line; it’s about building a better, more personalised relationship.

Are you experiencing the AI trust gap in your customer interactions? It might be time to rethink how your creative speaks to your audience.

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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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myFirst, a Singapore kids’ tech company selling “first devices” for children, has secured over US$8 million in a Series A round led by Vertex Ventures Southeast Asia & India, as investors chase a category many parents already treat as unavoidable: giving children connected tech, but trying not to hand them the keys to the entire internet.

The company sits in the fast-growing space between two uncomfortable extremes — kids borrowing a parent’s smartphone, or kids getting their own and immediately colliding with adult platforms, adult content, and adult incentives. myFirst’s answer is a tightly controlled ecosystem built around its myFirst Fone watchphone and the myFirst Circle family app, which it says is already used by more than one million families across 60 countries.

Also Read: How myFirst aims to provide a safer social media experience for children

“We started myFirst because our own kids wanted to use technology, but everything out there was built for adults,” said founder and CEO G-Jay Yong.

A safety-first ecosystem built for children, not retrofitted from adult tech

myFirst’s technology stack is designed around a simple idea: children should be able to communicate and create without being exposed to the open social web.

At the hardware level, the flagship watchphone is positioned as a compromise product: kids can call and message, but parents aren’t effectively giving them a pocket computer with an app store. The company highlights GPS tracking, safety zones (geofencing), and an SOS button—features aimed at reassurance and rapid response rather than entertainment.

The ecosystem approach goes further than a single device. myFirst sells a range of kid-targeted gadgets (watchphones, cameras, headphones, drawing tablets and more) paired with connected services. The point is less about piling up screens and more about creating controlled entry points into digital behaviour: communication, creativity, and self-expression.

The core safety design principles, as described by the company, include:

• Closed networks over open platforms (children interact only within approved circles)
• Parental controls baked into the product, not bolted on after the fact
• Encrypted environments for sharing and messaging
• No ads, reducing the risk of behavioural targeting and engagement traps
• Reduced exposure to strangers by limiting who can contact or view a child’s content

Taken together, myFirst is trying to sell parents something the mainstream internet struggles to offer: a smaller, safer digital world that’s still functional.

myFirst Circle: social networking without the stranger-danger business model

The biggest differentiator is myFirst Circle, which myFirst describes as a “closed, ad-free social network designed specifically for children”.

Also Read: GeckoLife wants to protect the digital privacy of you and your children

That sets it apart from traditional adult social media in three key ways:

• Access is permissioned: kids share moments only with approved family and friends, rather than broadcasting to the public or algorithmic discovery feeds.
• The environment is parent-controlled: the platform is designed around guardians managing contacts and boundaries, rather than expecting children to self-moderate.
• It’s not ad-driven: without advertising as the engine, there’s less incentive to maximise time spent, provoke engagement, or collect extensive behavioural data.

In other words, myFirst Circle is attempting to keep the “social” part (sharing, reacting, staying connected) while stripping out the parts that have made adult social platforms a headache even for adults.

Where the money goes: retail, telcos, and a push outside Southeast Asia

The Series A funding will be used to deepen the kidstech ecosystem and expand distribution, with myFirst pointing to retail and telco partnerships as its main route into new markets.

The company says it plans to scale across North Asia, the Middle East, the US, and Europe

It also namechecked large retailers Walmart and Best Buy as partnership examples, signalling a strategy built around mainstream consumer shelves and carrier bundles rather than niche online-only sales. For a kids’ device category—where trust, warranties, and physical retail visibility matter—that approach could be decisive.

Jessica Koh, Senior Executive Director at Vertex Ventures SEA & India, framed the bet as a shift in consumer behaviour: “We see a structural shift in how families introduce children to technology, driving demand for purpose-built products rather than adaptations of adult platforms.”

The real battle: defining “first tech” before the smartphone does

myFirst is effectively trying to claim the moment when a child moves from offline to online before a smartphone becomes inevitable. The company’s wager is that parents will pay for a safer on-ramp if the products are credible, not clunky, and don’t feel like a punishment device.

Also Read: Unlikely mentors: What kids can teach you about entrepreneurship

The challenge, as always in children’s tech, is balancing freedom and safety without turning the experience into surveillance theatre. But with fresh capital and an explicit global expansion plan, myFirst is pushing its case that kids shouldn’t have to start their digital lives on platforms built for adults—and parents shouldn’t have to choose between connection and chaos.

myFirst as one of the first 15 semifinalists of e27‘s TOP100 programme in 2023

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Agents Stack positions itself as an advisory board for the C-suite at a time when AI is reshaping how enterprises operate. Founded in February 2025 by Aanchal Gupta, the consultancy works with senior leaders navigating AI transformation, offering expertise across AI, digital transformation, cybersecurity, sustainability, ethics, and governance.

Rather than pushing tools, Agents Stack focuses on tightly defined, strongly guardrailed use cases designed to deliver measurable outcomes. The company works with clients across banking, financial services and insurance, manufacturing, maritime and real estate, among others.

Its premise is straightforward: efficiency gains from AI are only sustainable when governance comes first.

“When you deploy AI, how do you make sure that it’s secure and has ethical practices and governance built into it by design?” Gupta said in a call with e27.

For Agents Stack, governance is not an afterthought but the foundation upon which digital efficiency is built. It works closely with customers not only on strategy but also on change management and implementation, helping organisations embed AI responsibly within their operations.

Also Read: Bridging the AI trust gap: Why ad diversification and creative differentiation are the future of customer connections

Before formally launching, Gupta spent much of 2025 meeting more than 1,000 C-level executives across the Philippines, Singapore, Malaysia, Thailand, the Middle East, Europe, and India. The objective was not to pitch, but to listen.

The most consistent feedback was not a lack of tools, but too many of them. Executives cited an overload of cybersecurity products and information, coupled with limited visibility over actual risk exposure. What they sought was a trusted partner that could consolidate and simplify the landscape, cut through vendor noise and provide clear oversight of cyber threats. That insight now shapes the company’s strategic direction.

In 2026, Agents Stack’s priorities centre on critical infrastructure, operations and supply chain risk — areas Gupta sees as the most pressing vulnerabilities in the coming year. Global expansion is also high on the agenda, alongside helping customers consolidate vendors to reduce complexity and cost.

Geographically, the company plans to extend its footprint into the Middle East, the European Union, Japan, South Korea and Africa. Its service scope is expanding in parallel, with end-to-end risk advisory spanning climate and nature risk, operations risk, supply chain risk and AI risk.

The emphasis on operations technology and supply chain exposure reflects a broader shift in the cybersecurity landscape. As hardware and software become more tightly integrated in sectors such as energy, railways and defence, the attack surface widens.

Also Read: Purpose or drift? America’s Iran strategy, global shockwaves, and Tehran’s post-strike trajectory

According to Gupta, operations and supply chain risk in critical infrastructure will be among the most significant threat vectors in 2026, particularly as AI-driven systems become more prevalent.

In the Asia Pacific, governments and regulators are sharpening their focus on these vulnerabilities. Policies targeting data protection, operational resilience and supply chain transparency are gaining traction. Gupta expects regulatory attention on operations and supply chain risk to intensify, given the growing exposure created by digital transformation.

At the same time, she argues that long-term resilience will depend on capacity building. Agents Stack is prioritising public-private-education integration across Asia Pacific to strengthen talent pipelines and foster collaboration. With limited cybersecurity talent and rising costs, enterprises cannot address every risk simultaneously. Strategic prioritisation is essential.

As generative AI and automation accelerate, Gupta advises organisations to adopt a calculated approach. Security leaders must prioritise high-risk parameters and accept that not every vulnerability can be mitigated at once. “There is too much noise with a lot of tools and vendors on data visibility and protection,” she said. What matters is meaningful coverage of the most critical risks.

In an environment defined by rapid technological change and regulatory complexity, Agents Stack is positioning itself as a steady hand for the C-suite — one that combines governance by design with practical risk prioritisation. As it expands globally in 2026, the company’s bet is that clarity, consolidation and trust will matter more than ever in the age of AI-driven transformation.

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Image Credit: Agents Stack

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South Korean President Lee Jae Myung’s stop in Singapore before heading to the Philippines was more than ceremonial diplomacy — it was a strategic signal.

At the Korea-Singapore AI Connect Summit, Lee positioned artificial intelligence not merely as a technology trend but as a national competitiveness imperative. His announcement of a US$300M global fund to be established in Singapore by 2030 marks Korea’s first offshore master fund dedicated to AI and deeptech startups, underscoring Seoul’s intent to anchor itself deeper within Southeast Asia’s innovation ecosystem.

The proposed Korea-Singapore AI Alliance adds institutional weight to that ambition, linking policymakers, researchers, and industry leaders in what Lee described as an open innovation framework. The emphasis on joint research to address global challenges suggests a bid to move beyond capital flows toward co-development and shared intellectual leadership.

For two resource-scarce but talent-rich economies, collaboration in AI is both pragmatic and symbolic. As the sector remains dominated by the US and China, Seoul and Singapore appear to be betting that middle powers can still shape emerging technologies — not alone, but together.

REGIONAL

S Korea to launch US$300M AI startup fund in Singapore by 2030: The fund will invest in promising AI and deep‑tech startups from both countries. The fund would be Seoul’s first offshore global master fund and proposed a Korea‑Singapore AI Alliance.

myFirst bags US$8M to build a safer first internet for kids: Vertex Ventures is the lead investor. myFirst’s technology stack is designed around a simple idea: children should be able to communicate and create without being exposed to the open social web.

Dyna.Ai lands eight-figure Series A to move banks beyond AI pilots: Investors include Lion X Ventures and ADATA. Singapore-based Dyna.Ai aims to deploy agentic AI inside banks, betting enterprises are shifting from pilots to governed, results-driven systems built for measurable operational execution.

Toku emerges stronger from IPO year with AI suite driving monetisation: Toku grew FY2025 revenue 9.3% to US$34.8M, with usage revenue up 21%, improved EBITDA, reduced debt, and strengthened finances post-IPO, positioning its AI platform for margin expansion and global growth.

Indonesia launches platform to combat rising gaming addiction: DARA is a multiplatform private counselling service designed to help children and families manage gaming addiction. Studies show about 33% to 39% of high school students in some samples fall into moderate to severe gaming addiction.

FEATURES & INTERVIEWS

‘Profitability is an inflexion point, not the finish line’: PolicyStreet CEO: Khazanah-backed PolicyStreet posted over US$1 million in profit after 2.5x revenue growth, with CEO Yen Ming Lee outlining disciplined capital management and a sustainable embedded insurance model.

Strait of Hormuz closure: A potential chokepoint for the Southeast Asian tech startup ecosystem: Skyrocketing energy prices might erode profit margins for startups in SEA hubs, where data centres guzzle electricity for AI training and cloud computing.

From bridge rounds to global awards: Startups across Asia keep building: Asian startups are securing funding, partnerships, awards, and leadership hires — but visibility drives credibility. On e27, dynamic profiles turn milestones into lasting signals of traction, momentum, and growth.

INTERNATIONAL

Amazon to invest US$50B in OpenAI, expands cloud deal: They’re expanding their multi-year contract from US$38B to US$100B over eight years, and OpenAI will secure about 2 gigawatts of Trainium capacity on AWS. They’ll work to customise OpenAI models specifically for Amazon developers to integrate more deeply with AWS infrastructure.

Amazon to invest US$9B in Korea, eyes public sector AI push: As part of the deal, it plans to invest over US$5 billion by 2031 in data centres. Ham Kee-ho, AWS Korea’s managing director, predicts that AI-native models could allow Korean startups with fewer than 12 employees to generate US$100B in annual revenue by 2029.

China unveils first national standards for humanoid robots: The system is built on six pillars – foundational and common standards, neuromorphic and intelligent computing, limbs and components, full-system integration, application, and safety and ethics.

ChatGPT uninstalls surged by 295% after the deal with the US gov: CEO Last week, the AI giant reached an agreement allowing the Department of Defense to use its AI models in the department’s classified network. This follows a high-profile standoff between the DoD and OpenAI’s rival Anthropic.

Pine Labs to launch stablecoin prepaid cards in 9 countries: The prepaid card will be funded from consumers’ digital wallets with stablecoins and will convert them into local currencies at the point of sale in real time. It does not plan to launch the product in India or China.

CYBERSECURITY

‘Cybersecurity must move at the speed of AI development’: ArmourZero CEO: Tho Kit Hoong warns AI-driven development is accelerating application and supply chain risks, urging enterprises to adopt real-time, contextual risk intelligence to secure modern software ecosystems across Southeast Asia and beyond.

Beyond the audit: Why risk management is the secret engine of 2026 growth: In a permacrisis economy, risk management is no longer compliance theatre but a growth engine. Founders must tackle non-linear scaling, correlated expansion risks, and AI obsolescence to build resilient, sustainable startups.

Cyber risk is moving upstream but we’re still defending downstream: Cyber defence once focused on firewalls and incident response. Today, risk forms upstream—in architecture, code, identity, and supply chains—long before attacks occur, demanding security by design, not detection alone.

Cybersecurity is not an IT problem: It is a trust architecture crisis: Southeast Asia’s digital economy risks fragility as cybersecurity remains siloed. Trust depends on empowered people, coordinated governance, and resilient infrastructure — not perimeter defence — to sustain confidence at scale.

SEMICONDUCTOR

China chip firms post big 2025 gains as Nvidia H200 blocked: Cambricon, Moore Threads, and MetaX posted large revenue rises for 2025 as domestic demand for semiconductors climbed amid Beijing’s tech-sufficiency push. Cambricon posted its first full-year profit of US$306.02M in 2025, while revenue jumped 450% to US$947.23M.

India chip market to hit US$103B as AI, EV drive demand: Domestic semiconductor market could nearly double to US$103B by 2030 from US$52B in 2024. The next 18 months are key as the ecosystem transitions from policy announcements to operational readiness.

US may cap Nvidia H200 exports to Chinese firms at 75,000 units: Bloomberg reported that Alibaba and ByteDance privately sought orders larger than 75,000 units, which per-customer limits would restrict. The US rules would restrict Chinese companies from using H200s to build data centres overseas.

AI

71% of APAC firms see AI as top data security risk: report: Only 35% of Asia Pacific firms know where all their data resides, 40% can fully classify it, and 47% of sensitive cloud data remains unencrypted. Credential theft leads attacks on cloud management infrastructure in Asia Pacific at 69%, compared to 67% globally.

Singapore targets 100K workers in AI upskilling programme: The city-state last month unveiled a US$122B budget to help it navigate a “more dangerous world,” marked by technological challenges and trade fractures. The PM has made AI a key plank in his economic strategy and pledged there’ll be “no jobless growth” amid this push.

When AI stops being a feature and starts being infrastructure: As AI quietly shifts from experiment to infrastructure, reliability, governance, and accountability matter more than novelty. Once embedded in workflows, AI demands ownership, maintenance, and resilience — because business-critical systems cannot afford failure.

Nvidia, telecom firms partner to develop AI-powered 6G networks: Nvidia said the members will commit to building 6G networks using software-controlled radios running on general-purpose computers that use AI to help direct radio traffic safely and efficiently.

THOUGHT LEADERSHIP

Extreme fear grips crypto: What 15 Fear Index reading means for your portfolio: US–Israel strikes on Iran triggered a global risk-off selloff, with crypto plunging alongside equities as correlation hit 78%, extreme fear spiked, leverage unwound, and oil-driven inflation fears clouded near-term recovery prospects.

How to use Bayesian thinking to pick a winning startups investment: Startup investing isn’t about bold vision, but Bayesian humility—updating beliefs with evidence, not hype. In a game of frequent failure, disciplined probability beats conviction, protecting investors from bias, overconfidence, and self-deception.

Why I’m trading bytes for atoms: The 65-year-old investor breaking the climate tech silos: After 33 years building and backing startups, this founder is “refiring” into FOAK climate-tech and nature-based solutions, launching Sherpa Alpha to back asset-heavy ventures bridging innovation, capital, and infrastructure gaps.

The investor data room: The final battlefield for trust: Startup deals often stall at due diligence: investors scrutinise data rooms, governance, and documentation. Institutional capital flows to ventures proving operational discipline, transparency, and readiness — not just compelling growth narratives.

The hidden risk most Founders don’t plan for: When everything looks “fine”: Success can mask structural risk. Overreliance on key people and weak systems stay invisible until disruption hits — and by then, damage is costly. Founders must diversify keyman risk early, while calm prevails.

Why perfect carbon audits could cripple climate finance — and what to fix instead: Blaming auditors for junk carbon credits misses the real problem: bloated methodologies. Lean baselines, satellite MRV, and smarter oversight can protect integrity without pricing developing-country climate projects out.

Transition climate risk: Navigating the future of sustainable real estate: As economies decarbonise, real estate faces rising transition risks from regulation, market repricing, technology shifts, and reputational pressure, demanding proactive decarbonisation, green financing, and data-driven resilience strategies.

Throwaway gold: How data can tap into the unrealised potential in plastic waste: Amid a worsening plastic crisis, poor data blocks a US$120B recycling opportunity. Better insights, inclusive systems, and circular innovation could transform waste into economic and environmental value.

The shifting geopolitics of sustainability, energy, and climate: Policy shifts in the EU, UK, and Canada reveal sustainability, energy security, and geopolitics converging — reshaping ESG standards, supply chains, Indigenous governance, and strategic business decision-making worldwide.

Can Bitcoin help us in the fight against climate change?: Bitcoin’s energy use draws criticism, but experts argue it consumes less than traditional banking and increasingly relies on renewables, potentially incentivising clean energy adoption while reshaping ESG and institutional investment conversations.

Revolutionise your business operations: A smarter alternative to lengthy paper processes: Paper-based processes slow businesses and cost up to US$36 per agreement. E-signatures boost productivity, enhance security, reduce costs, and cut environmental impact.

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There is a quiet assumption in the tech ecosystem that artificial intelligence makes systems smarter simply by being added to them. Smarter credit underwriting. Smarter hiring. Smarter insurance pricing. Smarter healthcare routing.

In practice, most AI does something much more specific.

It makes existing decisions more consistent.

And consistency, while valuable, is not the same thing as intelligence.

Modern institutions were not designed to misunderstand people. They were designed to scale. As companies grew, human discretion became difficult to standardise and defend. So we replaced judgment with rules, and rules with statistical models. When machine learning matured, we replaced static scorecards with dynamic prediction engines.

Each step improved efficiency. Default rates fell. Time-to-hire shortened. Fraud detection sharpened. Operational variance narrowed.

But in the process, decision-making quietly shifted from something revisable to something conclusive.

A credit score stopped being a signal and became a gate.

A résumé filter stopped being a screen and became a ceiling.

A risk model stopped being advisory and became authoritative.

AI did not create this structure. It inherited it.

Prediction is not learning

And when predictive models are layered onto rigid systems, they don’t automatically make them more humane or more inclusive. They make them more precise.

The real question is not whether AI predicts accurately. It’s whether the system it sits inside is designed to learn over time.

Prediction looks backward. Learning moves forward.

Most AI deployed today is exceptionally good at learning patterns from historical data. But historical data reflects past institutional decisions as much as it reflects human potential. When we train models on who defaulted, who churned, who succeeded, or who stayed, we are teaching systems to recognise patterns of past behaviour within past constraints.

That can be commercially effective.

It is not the same as recognising human change.

The thin-file reality in emerging markets

This distinction becomes particularly important in Southeast Asia and other emerging markets, where large segments of the population are “thin-file” not because they are risky, but because they are under-documented. Informal income streams, non-linear career paths, gig-based work, and evolving digital footprints do not fit neatly into static classification systems.

When AI is applied purely to optimise gatekeeping, thin-file individuals are processed faster—but not necessarily understood better.

So perhaps the next evolution of AI isn’t about better prediction at the moment of decision. It’s about redesigning when decisions become final.

Keeping decisions revisable

Human-Centric AI is less about replacing humans and more about structuring systems so that early judgments remain provisional. Instead of collapsing uncertainty into a single score, these systems make uncertainty visible. Instead of asking “approve or reject,” they ask “what trajectory is emerging?”

In credit, that means observing volatility and recovery patterns before default rather than reacting after missed payments. In hiring, it means recognising learning velocity and adaptability rather than screening purely for static experience similarity. In insurance, it means detecting mitigation behaviour before loss severity increases. In healthcare, it means integrating longitudinal signals before thresholds are breached.

None of this requires lowering standards. It requires raising resolution.

The commercial implications are significant. Broad segmentation caps growth. Static thresholds protect against loss but limit expansion. When systems can safely interpret individual trajectories, hyper-personalisation becomes operationally viable rather than marketing rhetoric. Previously “unscorable” customers become observable. Early stress becomes manageable. Risk becomes dynamic rather than binary.

This is not an ethical pivot. It’s a structural one.

The design choice that defines AI

At InsightGenie, this philosophy shapes how we design behavioural AI across financial services, HR, and health use cases. Rather than building sharper filters, we focus on modelling behavioural trajectories — how patterns evolve, stabilise, or deteriorate over time. Voice analytics, engagement signals, and behavioural micro-variations are not used to freeze identity. They are used to detect movement.

Because intelligence in institutional systems should not be measured only by how accurately it predicts an outcome.

It should be measured by how early it recognises change.

We are still early in the AI adoption curve across the region. Many systems are being built now that will define how opportunity, access, and risk are allocated for decades. The decisions made at the design level — whether models close decisions quickly or keep them revisable — will shape whether AI becomes a tool for rigid optimisation or adaptive growth.

The debate is often framed as humans versus machines. That framing is already outdated.

The more relevant question is simpler: when new information appears, is the system allowed to change its interpretation?

If the answer is yes, AI becomes an engine for responsiveness.

If the answer is no, AI becomes a very efficient way of preserving the past.

The technology is not the constraint.

Design is.

If this resonates and you’re rethinking how your systems make — and revise — decisions at scale, let’s talk. Reach me directly at vincent@insightgenie.ai.

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This article was sponsored by InsightGenie

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Startups across Asia continue to push forward with new funding, leadership hires, global competition wins, and enterprise partnerships. Yet many of these milestones remain scattered across social feeds, press releases, or private investor updates. In a market where visibility influences credibility, distribution matters as much as execution.

On e27, company profiles are increasingly becoming living records of startup progress. They are not static directory listings, but dynamic pages that document a company’s evolution over time: funding rounds, product launches, regulatory approvals, leadership changes, partnerships, and awards. For investors, corporates, and ecosystem players browsing the platform, these milestones provide real-time signals of traction and momentum.

If you are building, your milestones deserve more than a single post that disappears in 24 hours. Create your startup profile and share your updates. Visibility compounds, and the startups that consistently document progress are often the ones that stay top of mind.

Below is a look at some of the latest milestones shared by startups on the platform.

MUI-Robotics — Bridge Round with Akai Wagon Partners
MUI-Robotics has secured a bridge round of funding from Akai Wagon Partners, a Japan-based investor. The funding adds to the robotics startup’s runway as it continues to develop and scale its offerings, with the backing of a Japanese investment partner signalling confidence in the company’s direction and regional relevance.

BrndIQ — Public and Agency Plans Launch
BrndIQ has rolled out public plans starting at US$28 per month, with additional discounts of 10–25 per cent available for quarterly or annual commitments. The company has also introduced agency plans featuring whitelabel capabilities. New users can sign up with 30 free credits to explore the platform.

Also Read: As Asia’s startup ecosystem moves forward, these milestones show what founders are building

TAG MY BOX — Go Green Go Global Hackathon 2025 Consolation Award Winner
TAG MY BOX was selected as a Consolation Winner at the Go Green Go Global Hackathon 2025. The recognition came from GS1 Singapore, Singapore Manufacturing Federation, and APGA, highlighting the startup’s work at the intersection of innovation and real-world sustainability challenges.

UIB Holdings — UIB names former WhatsApp Director Deepesh Trivedi as CEO
API AI company UIB.ai has appointed Deepesh Trivedi, former Director and Board Member at WhatsApp, as its new CEO. Based in Singapore, Trivedi will lead UIB’s growth strategy in the expanding white-label omnichannel conversational and generative AI market.

M3TRIQ — First Place at Evolved Technology 2025 Global Sprint
M3TRIQ has taken first place in the Agentic Automation and Workflow Optimisation track at Evolved Technology 2025, a global AIxBio hackathon backed by NVIDIA, Nebius, and Lux Capital. The win was powered by AMPSA, the company’s multi-agent system designed for cross-species antibody adaptation.

ClinSync — Partnership with Genira for AI Drug Safety Reporting
ClinSync has partnered with Genira to integrate its AI-powered pharmacovigilance application into early-stage oncology trials. The integration supports ICHE2B (R3), MedDRA, and WHODrug compliance, aiming to ease clinicians’ documentation burden while ensuring data security and faster adverse drug reaction reporting.

Good Bards — Selected for HP Garage 2.0 Cohort 2
Good Bards has been selected to join HP Garage 2.0, a curated accelerator programme designed as a launchpad for startups building alongside HP. As part of the cohort, Good Bards will co-create, validate real-world AI use cases, and accelerate its go-to-market strategy.

Tisane Labs — Partnership with AccelByte
Tisane Labs has announced a new partnership with AccelByte, integrating its advanced AI-powered moderation capabilities directly into the AccelByte platform. The collaboration aims to strengthen content moderation for gaming and interactive entertainment platforms.

Also Read: Big Wins and Bold Moves: 10 SEA Companies Sharing Their Latest Milestones

Synscribe — Joins Iterative W26 Batch
Synscribe has joined Iterative’s W26 batch to scale its hybrid SEO and GEO agency powered by AI. The startup is building an AI-operated agency framework to automate the human-heavy parts of account management, helping B2B SaaS startups win visibility on both Google and ChatGPT.

Staple — GovTech Innovation Challenge Award
Staple AI has been selected as one of six award recipients in the World Bank GovTech Innovation Challenge, supported by SECO Economic Cooperation and Development and Trust Valley. The recognition positions Staple among a select group of companies advancing innovation in government technology.

Why this matters

Milestones are more than announcements. They are signals.

For investors, they indicate execution velocity, capital efficiency, and market validation. For corporates, they highlight potential partnership readiness. For media and ecosystem players, they surface emerging categories and breakout companies.

Startups that consistently document their progress build a visible track record over time. A funding round is stronger when it follows documented product launches. A partnership carries more weight when supported by prior awards or pilot wins. Publicly archived milestones create narrative continuity and institutional memory.

Create your startup profile here.
Post your next milestone here.

If you are building, document it. If you are scaling, amplify it. Visibility is part of growth.

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

Looking ahead: Echelon Singapore 2026

Echelon Singapore 2026 brings together 300+ investors, 500+ corporates, and 100+ media over two days, focused on real deal-making. Founders leave with term sheets, pilot projects, and partnerships, not just business cards.

Secure your startup a booth now at 40 per cent OFF here.

Unsure if you’re the right fit? Reach us at events@e27.co.

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The post From bridge rounds to global awards: Startups across Asia keep building appeared first on e27.

The recent closure of the Strait of Hormuz can potentially unleash a cascade of negative impacts on the Southeast Asian tech startup ecosystem. Skyrocketing energy prices might erode profit margins for startups in hubs such as Singapore, Jakarta, and Hanoi, where data centres guzzle electricity for AI training and cloud computing. Operational costs have surged as oil disruptions inflate fuel prices for logistics and server cooling systems. Hardware imports face delays and premiums, crippling prototyping timelines for semiconductor-dependent ventures that rely on Malaysia and Vietnam.

Supply chain snarls compound the crisis. Rare earths, chips, and helium—critical for tech manufacturing—route through Hormuz-linked routes, sparking shortages that stall scaling efforts. Petrochemical hikes hit packaging and plastics, squeezing gadget makers. As one LinkedIn analysis notes: “Semiconductors and oil & gas sectors in Southeast Asia face immediate volatility from Hormuz closure”. Investors, spooked by geopolitical chaos, are pulling back. Venture capital flows, already cautious following the post-2025 slowdown, now prioritise resilient sectors, delaying funding rounds for energy-vulnerable startups.

This perfect storm threatens innovation pipelines. AI firms, burning cash on power-hungry models, confront slashed budgets mirroring broader tech spending slowdowns. A Nikkei Asia report confirms: “Strait of Hormuz closed to energy, other traffic,” amplifying regional refining strains. Southeast Asian tech startup ecosystem players, from fintech in the Philippines to e-commerce in Thailand, risk stunted growth amid 20-30 per cent cost spikes. With this, layoffs loom as founders slash teams to survive.

Broader economic ripples deepen the pain. Inflationary pressures curb consumer spending on apps and services, hitting ad revenues for digital natives. Regional governments, juggling energy imports, may hike taxes or subsidies, diverting focus from startup incentives.

Also Read: AI is not about automation. It’s about when systems are allowed to learn.

Yet, amid turmoil lies opportunity for the nimble. Startups can pivot to resilience strategies, fortifying the Southeast Asian tech startup ecosystem against future shocks.

Localisation tops the list. Firms should onshore critical components, tapping Vietnam’s chip assembly boom or Indonesia’s rare earth potential. Partnerships with Australian or US suppliers bypass Gulf chokepoints, stabilising costs.

Renewables offer a lifeline. Solar-powered data centres in sunny Singapore cut oil dependence, slashing bills by up to 40 per cent. Indonesian startups could lead with their climate tech edge, attracting green VCs wary of fossil risks.

Diversified funding models emerge. UAE crowdfunding platforms and sovereign funds fill VC gaps. Bootstrapped successes, such as Vietnam’s budget AI tools, prove lean ops thrive in crises.

Policy advocacy matters. Collective lobbying for tax breaks on renewables and supply chain insurance bolsters ecosystems. Governments in Malaysia and Thailand have already signalled support by fast-tracking visas for green tech talent.

Finally, agility defines winners. Southeast Asian tech startup ecosystem pioneers embracing AI for predictive logistics or blockchain for transparent sourcing turn liabilities into leads. As Hormuz tensions persist, pivots today ensure dominance tomorrow. Bold founders will not just survive—they will redefine regional tech supremacy.

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Image Credit: Venti Views on Unsplash

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