These are challenging times for startups and small businesses, especially those committed to long-term sustainability goals. Geopolitical uncertainties — including fluctuating tariffs, ongoing conflicts, and disrupted global supply chains — continue to cast a shadow over already volatile markets.

While it’s encouraging that Singapore is emerging as a global leader in sustainability, building a green business remains a complex endeavour. Government initiatives like the Enterprise Sustainability Programme, which provides training and consultancy support, and the recently launched Carbon Development Grant offer crucial help.

However, these efforts often fall short of fully bridging the financial and operational gaps that sustainability-driven startups face.

Balancing profit and purpose

Sustainability is undeniably vital for the environment and future generations. But at the end of the day, businesses are primarily driven by the need to achieve profitability. The adoption of sustainable practices often involves significant upfront investment, and without clear, near-term returns, many companies view them as cost centres rather than value drivers.

That said, the landscape is shifting. More financial incentives are becoming available, such as green loans offering preferential interest rates, provided companies meet ESG reporting requirements. This creates a tangible business case for embedding ESG not just as a compliance checkbox, but as a tool for unlocking new capital and strategic growth opportunities.

In Singapore, all listed companies will be required to provide climate-related disclosures aligned with international standards starting from FY2025. However, most of these firms prefer to work with established providers — such as the Big Four accounting firms — for sustainability and reporting services. This makes it harder for newer, smaller sustainability consultancies to gain market share.

Meanwhile, SMEs are unlikely to face the same reporting requirements in the near future, due to concerns about added financial strain. Consequently, the market for sustainability services remains concentrated among larger enterprises. Startups that want to break in must offer specialised, enterprise-grade solutions — and that requires both capital and talent.

Also Read: Investing in a better future: Why sustainable investment matters

Funding challenges and emerging alternatives

Perhaps the biggest roadblock is funding. Traditional venture capital models emphasise high and fast returns, which often don’t align with the long timelines and capital-intensive nature of carbon and sustainability projects.

A promising but still-evolving alternative is tokenisation — a blockchain-based model that allows startups to raise capital from a broad investor base, somewhat akin to crowdfunding. Supported in part by Singapore’s Monetary Authority (MAS), this method offers greater access to funds but still inherits the same investor expectation for rapid ROI.

Reality, however, rarely matches these timelines. Take a reforestation project in Mongolia, for instance. Due to the harsh climate, tree saplings are first cultivated in greenhouses — a process that can take two to three years before planting even begins. Such projects require patient capital and mission-aligned investors.

Surviving and thriving through collaboration

In this environment, startups must be prudent and resourceful. One of the most effective ways to extend runway and accelerate progress is through strategic partnerships. By teaming up with like-minded businesses and leveraging shared services, startups can reduce costs while gaining access to complementary networks, technologies, and markets.

Collaboration can be a force multiplier. Whether through formal consortiums, incubators, or informal partnerships, collective action allows sustainability-minded businesses to scale impact faster and more efficiently.

But perhaps most importantly, green startups must cultivate endurance. Building a truly impactful, sustainable business isn’t a sprint — it’s a marathon. It demands flexibility, commitment, and a long-term mindset.

A long-term commitment to impact

Despite the many obstacles, the mission remains deeply worthwhile. Building a sustainable business is not just about regulatory compliance or generating carbon credits — it’s about creating lasting impact in the fight against climate change and improving the lives of communities around the world.

The journey is tough, especially in today’s financial climate. But by staying committed to our purpose, embracing innovation, and building strategic partnerships, we can not only survive the current challenges — we can emerge as resilient, future-ready leaders in the green economy.

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As someone who works closely with entrepreneurs and business leaders across Singapore and the ASEAN region, I’ve been watching with growing interest the convergence of two powerful forces: artificial intelligence and sustainability.

At first glance, these might seem like distinct domains—one rooted in algorithms and automation, the other in environmental and social responsibility. But at their intersection lies a wealth of opportunity, especially for small businesses willing to look beyond the obvious.

We’re living in a time when governments, corporations, and consumers are all rethinking what growth looks like. Singapore’s Green Plan 2030, ASEAN’s push toward decarbonisation, and rising investor focus on ESG metrics are reshaping how business is done. At the same time, AI tools are no longer locked behind corporate firewalls—open-source models, cloud-based platforms, and no-code tools have dramatically lowered the barriers to entry.

I see this convergence as the centre from which great untapped or little-tapped opportunities emerge. Let me share four such directions where I see strong potential for SMEs in our region to lead the way.

AI for sustainable agriculture

It’s easy to think of farming as old-world, but in Southeast Asia, agriculture remains vital—and ripe for transformation. In Singapore, I’ve seen how vertical farms are using AI and IoT to manage light, nutrients, and watering schedules, boosting yields while saving space and resources. These systems, while sophisticated, are increasingly affordable—basic setups are now built with open-source software and off-the-shelf sensors.

What’s exciting is how this same approach is reaching rural farms. In Vietnam, a company called MimosaTEK offers smart irrigation solutions that use AI to help farmers reduce water usage by up to 30 per cent. Imagine that impact at scale.

Entrepreneurs who understand data analytics and have even a modest grasp of agronomy can create platforms or consulting services to help traditional farmers modernise. Precision farming doesn’t require high-end robotics—it often begins with dashboards, SMS alerts, and remote monitoring linked to simple AI models.

Also Read: Unlocking agritech’s potential: Can Southeast Asia rise to the challenge?

Localised smart city solutions

The term “smart city” can sound like it belongs to governments and multinational tech firms, but there are practical ways SMEs are already playing a role. I’ve been following Vebits AI, a Singapore-based startup that built smart parking systems for private property owners—not the city government. That’s a great example of how small businesses can contribute to AI-driven urban improvements without trying to overhaul entire cities.

Opportunities lie in micro-mobility management, building-level sustainability dashboards, or last-mile delivery optimisation tools. Imagine working with university campuses, business parks, or condo developers to manage scooter-sharing, track utility use, or reduce delivery congestion.

In Manila, a local company partnered with a residential developer to use AI for predictive waste collection—cutting unnecessary trips and improving recycling rates. Projects like these don’t need deep capital reserves; they need a bit of data savvy, IoT integration skills, and strong B2B relationships with property owners or facility managers.

AI for renewable energy optimisation

Energy is a massive space—but there are smaller niches opening up where entrepreneurs can make a real difference. Sembcorp, for instance, uses AI to manage its renewable energy assets across Singapore. But what about all the smaller solar farms, community grids, or off-grid setups across ASEAN?

The International Renewable Energy Agency projects that Southeast Asia will double its solar capacity by 2030, yet much of it will be in smaller-scale installations. That’s where startups can step in—offering AI-powered forecasting, grid balancing, or battery usage optimisation.

A small team with knowledge of energy systems and predictive modelling could build cloud-based tools to help industrial parks in Johor or off-grid resorts in Bali manage fluctuating supply and demand. These tools don’t need to be complex—they need to be reliable, cost-effective, and region-aware. 

Also Read: How the upcycling movement can help build a true circular food economy

AI-enabled circular economy models

One of the most overlooked intersections between AI and sustainability is in the circular economy—rethinking how products are used, reused, and tracked across their lifecycle. Startups here in Singapore are already using AI to monitor waste streams and help manufacturers close the loop.

For instance, a local startup developed an AI-powered dashboard that alerts packaging producers when certain materials are underutilised or overstocked, helping them reduce waste by 15 per cent. That’s real impact—and real savings.

This space is wide open for SMEs with supply chain knowledge and a working grasp of operations or sustainability frameworks. You could build tools that track material flow, optimise end-of-life processes, or even help retailers match surplus with demand in real time. With regulatory pressure growing across ASEAN for extended producer responsibility, tools that support circular thinking will only become more relevant.

ASEAN market opportunities at the intersection of AI and sustainability

Entrepreneurs exploring the convergence of artificial intelligence and sustainability in ASEAN can tap into high-growth sectors backed by both policy momentum and investor interest. Here’s a quick snapshot of where the biggest opportunities lie:

Final reflections

What strikes me across all these areas is that you don’t need to invent new technologies—you need to apply what’s already out there in thoughtful, grounded ways. The convergence of AI and sustainability isn’t only about clean energy or climate models. It’s about building smarter farms, more liveable communities, resilient energy systems, and resource-efficient businesses—all of which are deeply relevant to ASEAN’s future.

So if you’re an entrepreneur wondering where the next wave of growth will come from, consider pointing your compass toward the spaces where technology meets stewardship. These aren’t just opportunities for profit—they’re opportunities for purpose. And in today’s world, that might just be the most enduring edge you can have.

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As Southeast Asia (SEA) rapidly rises as the world’s fourth-largest economy, the region faces a defining question: can its climate tech ecosystem mature quickly enough to meet net-zero goals by 2030? Optimism abounds with climate investment in the area, growing 15 per cent year-on-year from 2015 to 2023. Yet a staggering US$2.5 trillion investment gap remains.

At Echelon Singapore 2025, a panel of leading voices in climate innovation unpacked the opportunities and gaps that must be addressed to unlock a thriving climate tech ecosystem in SEA. It is widely known that the climate crisis is worsening, and SEA is highly vulnerable.

Rebecca Sharpe, Director of Better Earth Ventures, noted, “SDG 13, climate action, is actively regressing,” citing UN ESCAP’s 2023 findings. Yet she remains confident: “Innovation can and should play a critical role. We just need urgency and alignment.”

That urgency stems not just from deteriorating environmental metrics but also from Southeast Asia’s unique potential. With 34 per cent of the region’s population aged between 15 and 24, it is primed to lead in digital innovation, including climate tech. But potential alone is not enough.

Policy, regulation, and mindset in climate tech

A recurring theme among the panellists was the regulatory vacuum in the region. Sharpe pointed to Europe’s robust climate legislation, noting that such frameworks compel action.

“Without regulations, climate solutions are seen as ‘nice to have’, not must-haves,” she said. Singapore, often viewed as a regional leader, has a carbon tax but lacks enforceable climate mandates.

Also Read: Amasia introduces impact assessment framework for climate tech companies

Equally important is cultural context. Arka Irfani, CEO of Bell Living Lab, highlighted the irony of Asia’s historic sustainability practices giving way to growth-at-all-costs models. “The traditional mindset of being inclusive and mindful of future generations has been lost. We need to bring it back.”

Nicole Ngeow, Executive Director of the Prudence Foundation, offered a perspective from the philanthropic front lines. Her foundation supports community resilience in climate and health. But she stressed that innovation must be viable. “Philanthropy can fund early-stage pilots to derisk models, but there must be a pathway to sustainable business,” she explained.

This view aligns with emerging blended finance models, where philanthropic capital helps prove concepts, and commercial investors scale them. “It’s not an excuse to ignore market signals,” she added. “Startups must still demonstrate viable unit economics.”

Several speakers agreed that alignment across sectors—government, corporates, researchers, and startups—is key to scale. Irfani shared a powerful example: a three-month government-backed programme in Indonesia helped Bell Living Lab partner with over 100 farmers to convert coffee waste into sustainable materials.

“Alignment allowed us to scale from idea to impact,” he said. “But for long-term success, proximity to market demand is essential.”

Hyperlocalisation also emerged as a critical success factor. Sharpe noted that effective climate solutions often address specific local challenges—from mangrove restoration in Indonesia to nutrient-rich farming in India.

“Localisation doesn’t mean small scale. Often, these solutions are replicable across borders,” she said.

Developing transformative climate tech is one thing; communicating its value is another. Jatin Kumar, CTO of Xinterra, offered a masterclass in bridging the technical-to-practical divide. His AI-powered material innovation allows textiles to capture carbon dioxide, an idea that could sound esoteric.

Also Read: Why these startups focus on informal plastic waste workers in the fight against climate crisis

“Communication is everything,” Kumar said. “You must explain your technology in a way your audience understands—whether it’s a five-year-old or a textile manufacturer.” By translating emissions metrics into relatable impacts (“20 of these t-shirts equals the emissions offset of a tree”), Xinterra helps partners grasp both the science and the benefit.

Regarding funding, climate tech faces a structural challenge: its returns take time. “Investors don’t always get it,” Kumar said candidly. “Climate solutions aren’t instant wins. We need a shift from fast to slow money, like in biotech.”

Sharpe echoed this, noting that many generalist VCs exited the climate space post-pandemic due to longer timeframes and higher perceived risk. “We need new financial models that match the climate reality,” she said. Tools like the Asia Climate Lab, which maps active climate investors, are helping founders navigate this new terrain.

The panel concluded with a consensus: climate tech must move from fringe to front stage. “This isn’t just about branding,” Irfani noted. “For us, converting waste is the business model. For climate tech to thrive, authenticity matters.”

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A new whitepaper from Singapore-based Device-as-a-Service (DaaS) startup Cinch aimed to bring attention to a largely invisible but mounting problem: 2.9 million unused smartphones are sitting idle in Singaporean households, exacerbating the country’s e-waste challenges.

Titled Rethinking E-Waste: How Singapore’s Consumer Tech Ecosystem is Building a Blueprint for a Circular Economy in Southeast Asia, the report draws from a national survey and offers fresh data on consumer habits while proposing practical solutions rooted in collective action.

It reveals that Singaporeans replace their smartphones every 2.7 years, considerably faster than the global average of 3.5 years. However, rather than being recycled or resold, many older devices end up forgotten in drawers. Concerns around data privacy and a lack of convenient recycling or trade-in options were cited as key barriers to responsible disposal.

Despite these challenges, the appetite for sustainable solutions remains high: 90 per cent of surveyed consumers indicated they would be open to reusing, recycling, or returning devices if safer and easier processes were available.

Cinch’s whitepaper emphasises that the most effective long-term solution lies in adopting circular technology models, which extend the lifespan of devices through reuse, refurbishment, redeployment, and recycling.

This approach not only reduces e-waste but also lessens the environmental footprint associated with raw material extraction and carbon emissions.

Also Read: AI shopping adoption surges 39 per cent in APAC, fueling retail tech investments

The startup’s DaaS model exemplifies how circularity can be embedded into business operations. Through partnerships with organisations such as ALBA and CompAsia, Cinch aims to develop scalable systems that align with Singapore’s Green Plan 2030 and the National Environment Agency’s Producer Responsibility Scheme.

“No single company can solve e-waste alone. What’s needed is a national framework that rewards sustainable behaviour and embeds circularity into the tech ecosystem,” said Mahir Hamid, CEO of Cinch.

Emissions and cost benefits at scale

The environmental stakes are significant. According to the report, adopting circular models at scale could cut Singapore’s e-waste volume by 50 per cent and reduce tech-sector CO₂ emissions by 40 per cent. Each refurbished smartphone saves approximately 25 kilograms of CO₂ emissions, prevents 77 kilograms of raw material extraction, and avoids generating 56 grams of electronic waste.

Beyond environmental gains, consumers also benefit financially. Subscription-based DaaS models can lower upfront costs for devices by up to 96 per cent compared to outright purchases.

While Singapore’s government has implemented regulations and established collection infrastructure to address e-waste, Cinch’s report underscores the importance of multi-stakeholder collaboration. Businesses, policymakers, and consumers all play critical roles in driving circular economy adoption.

“Circularity isn’t an add-on to business. It is becoming the core of how tech consumption needs to evolve,” Hamid concluded.

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Most conversations about AI focus on tools. What model to use? What agent to deploy? What workflow to automate?

But after spending the past few months building AI-first systems inside real communities, I’ve realised something far more important than tooling choices: AI rarely breaks first. Trust does.

And once trust erodes, scale doesn’t save you. It accelerates the damage.

From products to communities

I didn’t set out to build “another AI product”.

What we’ve been building instead are AI-first, custom systems designed for existing communities — founders, creators, speakers, operators. These are not anonymous users on a landing page. These are people with shared history, shared context, and ongoing relationships.

That distinction matters.

When AI is embedded inside a community, it stops being neutral software. It becomes part of how people:

• Ask questions
• Make decisions
• Interpret authority
• Relate to each other

This is why I keep returning to a simple framing: Communities are the currency. AI is the engine. Human relationships are the result.

Founders who design AI without understanding the relationship triangle tend to break things they didn’t realise they were touching.

Vibe coding changed the speed — not the responsibility

AI-assisted development has radically compressed time.

What once took months can now take days. What used to be a “test landing page” is now a working MVP.

We are no longer validating ideas with email opt-ins. We are validating them with real products, in public, with real people.

This is powerful, and it’s also where misuse begins.

Because when building becomes easy, clarity becomes the true bottleneck.

Founders often rush to ship without answering:

• What is the outcome this AI is optimised for?
• What decisions are allowed to influence?
• Where must a human always intervene?
• What does “done” actually mean?

When those questions are unanswered, AI doesn’t fail loudly. It fails quietly — through misalignment.

Also Read: The great stabilisation: Why 2026 will be the year AI “grows up”

What actually breaks when AI scales

The assumption is that AI will fail technically. In reality, what breaks first is almost always human.

Trust breaks before tech does.

AI sounds confident by default. Communities assume intent by default.

When founders test AI systems inside communities without transparency — without clearly saying this is early, this is experimental, this is evolving — people don’t feel included. They feel misled.

In practice, I’ve seen two very different outcomes:

• In communities where experimentation was explicit, members gave better feedback, tolerated rough edges, and stayed engaged.
• In communities where AI changes appeared suddenly and opaquely, engagement dropped — not dramatically, but quietly.

And quiet disengagement is the hardest to recover from.

User experience breaks when expectations aren’t designed

Speed creates a dangerous illusion.

Fast answers feel like accurate answers. A confident tone feels like authority.

Without clear boundaries, AI begins to:

• Answer beyond its scope
• Sounds definitive when it should be conditional
• Close loops that should remain open

One principle has consistently prevented damage: Analyse, guide, recommend — but do not instruct.

In systems where this boundary was respected, users treated AI as support. Where it wasn’t, users outsourced judgment too quickly and blamed the system when things went wrong.

The difference wasn’t the model. It was the design decision.

Founders automate responsibility away — unintentionally

This is the most subtle failure mode.

As AI handles more replies, routes more conversations, and “keeps things moving”, founders begin to disengage — not out of laziness, but out of misplaced trust in the system.

Silence gets filled by automation. Judgment gets deferred.

In one case, a system functioned perfectly from a technical standpoint, but users grew confused about who was actually accountable. The AI had become the voice of the product.

That confusion didn’t create errors. It created hesitation.

The issue wasn’t hallucination. It was abdication.

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

The hidden variable: Founder operating style

Working closely with multiple founders across different AI-first builds surfaced a pattern I didn’t expect to be so stark:

AI doesn’t neutralise founder behaviour. It amplifies it.

Three archetypes consistently emerge.

• The co-founder of the builder

This founder treats AI as a collaborator, not a replacement.

Communication is two-way. Roles and responsibilities are explicit. Good questions are asked early. Cashflow and constraints are respected.

In these environments, AI performs exceptionally well — not because it’s more advanced, but because decision ownership remains human.

Observable outcomes:

• Faster iteration with less resistance.
• Higher-quality feedback from the community.
• Fewer rollbacks, fewer trust repairs.
• Users feel invited into the build, not managed by it.

Here, AI scales clarity — not chaos.

• The builder-by-habit founder

This founder is capable, competent, and often technically strong, but less collaborative in exploration.

They build because they can. They optimise execution more than alignment.

In these cases, AI reveals something uncomfortable: The founder might be better served by configuring an existing system instead of inventing a new one.

Observable outcomes:

• More features, less coherence
• Slower momentum despite higher build velocity
• Eventual consolidation back into off-the-shelf tools

AI doesn’t fail here. It exposes opportunity cost.

• The reactive founder

This is the most fragile archetype.

The founder responds only when asked. Avoids proactive decision-making. Delegates judgment without context.

AI fills the gaps, and the system drifts.

Observable outcomes:

• Accountability becomes unclear.
• The AI becomes the de facto authority.
• Community confidence erodes.
• Founder ends up firefighting instead of leading.

AI doesn’t fix leadership gaps. It scales them.

The real misuse of AI

Most founders believe they are scaling:

• Speed
• Efficiency
• Support

What they are actually scaling is:

• Unclear intent
• Weak boundaries
• Unfinished thinking

AI does not create these problems. It accelerates whatever already exists. That’s why copying AI stacks without copying operating discipline fails so often.

What this looks like in practice

Founders who scale AI responsibly tend to decide a few things early — not as rules, but as design principles:

• What decisions AI can support, but never make.
• Where human override is mandatory.
• How experimentation is communicated to users.
• When not to build, even if they can.

They understand constraints:

• Not everything integrates.
• Not all data is extractable.
• Not all workflows should be automated.

They build MVPs first — not because they’re careless, but because no system is complete at launch. What matters is whether it evolves with its community.

The real takeaway

AI-first isn’t about replacing humans.

It’s about revealing how founders think, decide, and lead — faster than ever before.

When AI is embedded inside communities, those truths surface immediately.

Communities are the currency. AI is the engine. Founder behaviour determines whether trust compounds or collapses.

—

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Indonesia’s Davos push was less about headline-grabbing meetings and more about signalling intent in a world where semiconductors have become geopolitical currency. By courting Nvidia, AWS, and leading US cybersecurity firms, Jakarta is making it clear that it no longer sees chips as a peripheral manufacturing play, but as foundational infrastructure for its digital and economic ambitions.

What stands out is timing. As AI accelerators, data centre GPUs, and advanced packaging emerge as global bottlenecks, Indonesia is positioning itself precisely where supply chains are under strain. Its recent progress — from the Batam assembly facility to advanced packaging investments in East Java — gives the pitch credibility. This is no longer a greenfield dream; it is an ecosystem under construction.

Yet ambition alone will not secure a place in the upper tiers of the semiconductor value chain. Assembly and testing are important entry points, but they are also crowded and margin-thin. The harder work lies in talent depth, sustained capital flows, and policy consistency over decades, not election cycles. Fast permits and generous incentives buy attention, not loyalty.

For Nvidia, AWS, and others, Indonesia offers optionality: cost advantages, geopolitical neutrality, and scale. Whether that optionality turns into long-term commitment will depend on execution. Davos opens doors; factories, engineers, and stable rules decide who walks through them.

REGIONAL

Indonesia courts Nvidia and AWS as it eyes a bigger role in global chip supply chains: Over the past three years, Indonesia has moved aggressively to establish a foothold in the semiconductor industry, transitioning from a near-absent player to a credible assembly and testing destination.

Singapore places a US$786M bet on AI sovereignty: A large public fund creates room to expand national compute capacity, subsidise cloud access, and build shared research infrastructure that universities, labs, and startups can tap.

Juspay raises US$50M, makes secondaries mainstream in Indian fintech: WestBridge-backed round underscores how employee liquidity, cleaner cap tables, and price discovery are reshaping Asia’s private funding playbook. The company claims its annualised TPV now exceeds US$1T and that it processes 300M+ transactions daily.

Singapore’s AI startup Level3AI raises US$13M: Investors include Lightspeed, Beenext, and 500 Global. Level3AI builds customer support and sales agents for enterprises. It deploys its engineers to co-design the AI agents with the client. The agents are then integrated into the client’s text and voice support channels.

Singapore’s data centre firm DayOne eyes IPO at US$20B valuation: The firm considers hiring banks for a share sale that could occur as early as this year, and is also evaluating a dual listing in the US and Singapore. Earlier this month, DayOne completed a US$2B+ Series C round, which was expected to value the company at around US$10B.

Malaysia reopens Grok AI access after temporary ban: This follows the social media platform’s introduction of additional safety measures. The country temporarily blocked Grok earlier this month following concerns over a feature that allowed users to generate and share sexualised images.

FEATURES & INTERVIEWS

How SPUN uses agentic AI to untangle Southeast Asia’s visa mess: SPUN is a plug-and-play platform blending AI document checks with human savvy, boasting a 99% approval rate across thousands of applications. No blind automation here. AI flags dodgy docs or regulatory quirks, escalating to specialists.

How SMEs can vet and choose AI partners that truly deliver: AI is becoming a great equaliser for SMEs, lowering barriers through generative tools that boost agility, automate testing, improve software quality, and help smaller firms compete with enterprise giants globally.

INTERNATIONAL

UAE’s K2, WeRide to launch autonomous bus service in Abu Dhabi: K2, a local mobility solutions provider, will leverage its experience in fleet management and real-world mobility deployments, while WeRide will contribute its autonomous vehicle technology and deployment expertise.

South Korea launches US$186M AI manufacturing fund: This marks the largest allocation to date and an 11.5% increase from last year. The funding aims to support AI-powered manufacturing. The programme will fund shared equipment and facilities for testing, evaluation, and pilot projects.

BYD targets 1.3M overseas EV deliveries in 2026: The Chinese company plans to double its European showrooms to 2,000, and establish a local supply chain for European production. BYD also operates factories in Thailand and Brazil to support rising demand.

South Korea’s robotics industry faces supply chain risk: Korea ranked fourth globally in installed robotic equipment in 2024, with a high robot density of 1,012 robots per 10,000 employees. Despite this, nearly 89% of Korea’s imports of permanent magnets and 60% of raw materials like rare earth elements depend on China.

TikTok US uninstalls jump 150% after joint venture announcement: The deal was announced last January 22. Some users reacted skeptically after being asked to accept an updated privacy policy that mentions collecting sensitive data, though similar language already appeared in a version from August 2024.

Zoom’s Anthropic stake may be worth up to US$4B, analysts say: In May 2023, Anthropic announced a partnership with Zoom and said Zoom Ventures had invested, though the amount was not disclosed. Zoom reported US$51M in strategic investments that quarter, with analysts estimating most of it went to Anthropic.

EU tightens rules on WhatsApp to tackle harmful content: The move follows the platform’s reported 51.7M average MAUs in the EU during the HI 2025, surpassing the 45M-user threshold set by the DSA. The designation aims to strengthen oversight and accountability for platforms with significant user bases within the EU.

Antler Japan invests US$1.5M in 10 early-stage startups: The firm announced a new six-week Inception Residency for 2026, increasing initial funding to US$150,000 per startup. Selected companies operate in fields such as robotics, AI, logistics, legal tech, and biotech.

SEMICONDUCTOR

Taiwan electronics output hits record high on AI chip demand: The overall industrial production index rose to 112.2, with the manufacturing subindex climbing 17.9 percent to 113.1. The electronics component industry saw a 24.7% rise. In December, the industrial production index increased by 21.6% to 131.8.

Nvidia launches AI weather forecasting tools: The new models are designed to improve forecast accuracy and speed across different timescales. These open-source tools aim to make weather AI accessible for scientists, startups, and government agencies globally, reducing reliance on traditional supercomputers.

Microsoft, Tsinghua use Nvidia chip to train AI without real data: Using only synthetic data, the team trained a 7B-parameter coding model that outperformed larger 14B-parameter models on benchmarks. The experiment used 128 Nvidia H20 chips for 220 hrs during supervised fine-tuning and 32 H200 chips for 7 days during reinforcement learning.

Microsoft unveils new AI chip to cut reliance on Nvidia: The new Maia 200, an AI inference accelerator chip fabricated on TSMC’s 3nm process, is designed to improve the efficiency of large-scale AI workloads. The chip features native FP8/FP4 tensor cores, a redesigned memory system with 216GB HBM3e memory at 7TB/s.

AI

AI to add about US$607B to India’s economy by 2035: PwC: AI may add up to 15% to global GDP by that year, driven by productivity gains in sectors such as manufacturing, healthcare, agriculture, energy, and education. In agri, the sector’s gross value addition is projected to increase from US$637B in FY25 to US$2.4T in FY47.

Human-centric skills in the age of AI: How to never lose touch with humanity in the workplace: AI lacks the nuanced understanding and ethical reasoning that define human interactions. This is why human-centric skills remain relevant.

AI data centres vs climate: How can business leaders find a workable balance? AI adoption in Southeast Asia strains water and power resources, forcing businesses to confront ESG impacts and use AI more responsibly.

The US$1M per person revolution: How AI is reshaping Southeast Asia’s startup landscape: Southeast Asian startups are adopting AI to drive US$1 million revenue per employee through smart automation across research, content, and sales.

THOUGHT LEADERSHIP

Building the ASEAN AI archipelago: How SEA can secure its place in the global AI value chain: ASEAN’s AI future depends on regional interoperability, deep localisation for SMEs, and an integrated semiconductor backbone—moving Southeast Asia from fragmented adoption to a resilient, collaborative force in the global AI value chain.

The surprising economics of orbital data centres — and the real solution: Falling launch costs make space-based solar viable for AI energy, but orbital data centres fail economically; the numbers favour beaming clean, firm power from space to Earth-based compute in future.

Hiring for human skills in a tech-heavy world: Southeast Asia must shift from tech-first thinking to human-centric problem-solving, using AI as a tool guided by empathy, critical thinking, and purpose-driven skills to ensure technology serves societies and governments.

Commercialisation ≠ sales: Understanding the difference early matters more than it seems: Early startups confuse sales with commercialisation, mistaking deals for validation. Without a clear commercialisation system, early revenue creates false traction, premature scaling, and fragile growth instead of repeatable businesses models.

The strategy trap: Why your best plan is failing to launch: Most SME strategies fail not from poor vision but weak execution, misaligned metrics and incentives, vague priorities, and unchanged behaviours, where leaders avoid decisions needed to turn intent into action.

Gold hits US$5K and crypto bleeds: What comes next? Markets opened amid geopolitical tensions, gold surged past US$5,000, equities diverged, Asia hedged dollar risk, while crypto slid on hacks and liquidations, exposing trust across traditional and digital financial systems.

The resume is dead: Why 80% of companies fail to hire based on real skills: Resumes dominate hiring despite being unreliable, leaving skills untested. As companies gamble on credentials, AI-driven, skills-based hiring is emerging to prioritise real ability, potential, and proof over polish.

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This was a day of stark contrasts and palpable anticipation, as traditional equities climbed higher, gold achieved a historic milestone, the US dollar retreated significantly, and the crypto sphere staged a notable comeback.

The narrative is complex, with investors juggling the immediate bullish sentiment fueled by technical rebounds and institutional plays against a backdrop of looming macroeconomic risks, including US tariff threats, an upcoming Federal Reserve decision, and large tech earnings reports. My view is one of cautious observation: while the short-term bounces in both equities and digital assets offer a glimmer of optimism, the underlying instability suggests a market holding its breath, keenly aware that a single headline could trigger a rapid reversal.

The US stock market delivered solid gains on Monday, pushing major indices closer to record territory. The S&P 500, a key benchmark, advanced a respectable 0.50 per cent to close at 6,950.23 points, placing it within a mere 0.4 per cent of establishing a new all-time high. This performance was mirrored by the Dow Jones Industrial Average, which saw a healthy 0.64 per cent increase, adding over 300 points to finish the session at 49,412.40 points. The tech-heavy Nasdaq Composite also participated in the rally, rising 0.43 per cent to reach 23,601.36 points. These moves suggest a market largely driven by optimism and positioning ahead of crucial economic events scheduled for the week.

The safe haven asset, gold, provided one of the day’s most dramatic headlines, soaring past the US$5,000 per ounce threshold for the first time in history. The precious metal was trading near a record high of US$5,100 per ounce early Tuesday morning. This incredible surge is a direct consequence of strong safe-haven demand, with investors flocking to stability amidst heightened global uncertainty.

Also Read: Gold hits US$5K and crypto bleeds: What comes next?

Paradoxically, the US dollar, another traditional safe haven, moved in the opposite direction. It weakened to its lowest level since 2022, with the euro exchange rate sitting near EUR0.84125 per US$1 on Tuesday morning. This divergence highlights the specific nature of current investor fears, which seem more attuned to geopolitical tremors than domestic US economic factors.

Simultaneously, the crude oil market saw modest fluctuations. Brent crude futures, the international benchmark, slipped slightly by 0.4 per cent to settle at US$65.59 a barrel on Monday. The market action here seems a delicate balance between potential supply disruptions caused by a US winter storm and the possibility of progress in ongoing peace talks, dampening fears of an immediate crisis impact on oil flows.

A significant driver of this volatility, and the corresponding boost for gold, was US President Donald Trump’s announcement. He signalled a potential tariff hike on South Korean goods, including autos and pharmaceuticals, to a flat 25 per cent. This sort of protectionist rhetoric inevitably fuels global market jitters, pushing capital toward perceived safety and away from riskier assets.

In Asia, markets displayed a modest recovery. The MSCI Asia Pacific Index initially showed weakness but found some footing, while the South Korean Kospi index, despite the potential tariff threat looming over its economy, reversed early losses to climb by 0.8 per cent. This resilience indicates that while investors are concerned, they remain reactive to immediate market dynamics and technical trading patterns.

The cryptocurrency market, often marching to its own drum but increasingly correlated with mainstream finance, experienced its own compelling rebound. The total crypto market cap rose 1.34 per cent over the last 24 hours, shaking off deeply oversold conditions. This recovery was not accidental; it was a response to specific market catalysts. A primary factor was a technical rebound, with the RSI14 hitting 26.98, a classic indicator of oversold territory signalling exhaustion in selling pressure. Bitcoin, the market leader, reclaimed the US$88K support level after briefly testing US$86K, offering a measure of relief to anxious holders.

Also Read: Crypto in the danger zone: Technical weakness, low volume, and a critical support test

Institutional conviction also played a crucial role in the crypto resurgence. News that BitMine had acquired 40,302 ETH, valued at an impressive US$120 million, and had staked over 2 million ETH in total, provided a significant boost to market confidence. This followed on the heels of BlackRock’s Bitcoin Premium Income ETF filing, indicating that major players see long-term value despite short-term headwinds.

Even as gold touched an all-time high of US$5,069, social media chatter indicated a palpable shift of focus towards higher beta assets like Bitcoin and Ethereum. This rotation is evident in the rising crypto-Nasdaq correlation, which climbed to 0.52, amplifying equity-linked moves within the digital asset space.

Ultimately, today’s market dynamics, spanning traditional stocks, commodities, and the volatile crypto realm, reflect a complex interplay of technical factors, institutional moves, and overarching macro concerns. My perspective suggests the gains seen across the board represent a temporary reprieve, a technical healing process if you will, rather than a definitive shift in market direction.

Major risks such as potential US government shutdown fears and persistent ETF outflows in the crypto sector remain significant headwinds. The market is positioned at a crucial juncture, watching key levels like Bitcoin’s US$88K support and Ethereum’s US$2,960 level, waiting to see if institutional accumulation can truly counter the prevailing retail caution in the days ahead.

The true test for global markets will arrive later this week, as the world awaits the Federal Reserve’s pronouncements and the highly anticipated wave of technology company earnings reports, events that will undoubtedly shape the near-term financial landscape.

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The lead image in this article was generated by AI.

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Cybersecurity has moved far beyond the server room. According to Penta’s report, Cyber risk is stakeholder risk: What leaders need to know now, cyber incidents are now as much about trust, reputation and leadership as they are about firewalls and patches. Drawing on data from January 2024 to August 2025, the report makes one thing clear: how an organisation responds to a cyber incident now defines its standing with stakeholders more than the breach itself.

For business leaders, this marks a decisive shift. Cybersecurity is no longer a purely technical challenge managed by chief information security officers behind the scenes. It has become a board-level and executive issue, with implications for brand equity, regulatory scrutiny and investor confidence.

One of the most striking cybersecurity trends highlighted in the report is the collapse of stakeholder trust following cyber incidents. Sentiment around data security and incident response remains strongly negative, particularly among regulators and investors. In an era of heightened transparency, silence or slow reactions are interpreted as incompetence or indifference.

This erosion of trust cuts across geographies and sectors. Cyber incidents now generate negative sentiment globally, regardless of where the breach occurs. However, industries with direct consumer interfaces suffer the sharpest declines, reflecting public sensitivity around personal data and service disruption.

Cybersecurity meets geopolitics

The report also underscores how cybersecurity has become entangled with geopolitical risk. State-linked attacks, such as those attributed to the group known as “Salt Typhoon,” have reframed cyber threats as matters of national security and diplomacy. Attacks on major telecom providers have raised concerns not only about corporate resilience but also about critical infrastructure and espionage.

Also Read: The great rotation: Why investors are balancing record gold with high risk crypto

For leaders, this adds another layer of complexity. Cybersecurity decisions are no longer judged solely on commercial outcomes but also on their broader societal and political implications. But perhaps the most important insight from the report is the emergence of what it calls the “response” narrative. In today’s environment, the defining story is not how a breach occurred but how it was handled.

Penta points to the CrowdStrike outage as a telling example. While the incident itself drew intense scrutiny, visible executive accountability and clear communication helped stabilise sentiment within 30 days. The lesson for leaders is stark: rapid transparency and visible leadership can materially shape stakeholder perception, even in the wake of significant disruption.

Technical containment remains essential, but it is no longer sufficient on its own. Cybersecurity resilience is now measured by an organisation’s ability to communicate, reassure and demonstrate control in real time.

The report’s sector analysis shows how cybersecurity risk manifests differently across industries. Technology companies face the highest visibility, accounting for 74 per cent of mentions, and are increasingly seen as sources of systemic risk. High-profile incidents involving cloud and security providers amplify concerns across the wider digital ecosystem.

Retail emerges as the most sentiment-sensitive sector, with negative sentiment reaching minus 77. Legal action and breaches at well-known brands highlight how exposed consumer-facing businesses are when customer data is compromised.

Telecommunications sits at the intersection of cybersecurity and national security, while financial services continues to battle scepticism around digital asset security and crypto resilience. Healthcare sentiment has collapsed amid fears over patient safety and systemic disruption, and the automotive sector is under growing strain as connected vehicles expand the attack surface, with cyber attacks rising 50 per cent year-on-year.

The report’s overarching message is that cybersecurity is now inseparable from stakeholder management. Leaders must treat cyber risk as a reputational and governance issue, not just a technical one. This means preparing not only incident response plans but also communication strategies, leadership visibility and regulatory engagement.

In a world where trust can evaporate overnight, cybersecurity has become a defining test of leadership. Those who recognise this shift — and act accordingly — will be better positioned to recover when, not if, a breach occurs.

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Antler is scaling up its bet on Japan’s early-stage startup ecosystem, investing ¥240 million (US$1.55 million) across 10 Japanese startups in 2025 and committing to significantly larger pre-seed cheques for founders entering its Japan programme in 2026.

The move signals growing conviction that Japan — long viewed as a challenging environment for venture-backed startups — is becoming a viable launchpad for globally competitive technology companies, particularly in deeptech, AI, robotics, and applied enterprise software.

Also Read: OpenAI calls for ‘AI infrastructure revolution’ to reboot Japan’s growth

Under its updated model, Antler Japan will run a streamlined six-week Inception Residency in 2026, offering US$150,000 net upfront per company, nearly doubling its previous initial investment. Founders can also access up to US$250,000 in matching follow-on capital within six to nine months, bringing total capital at inception to as much as US$400,000.

“We are deliberately doubling down on Japan as a source of globally competitive companies,” said Jussi Salovaara, co-founder and managing partner at Antler. “The local talent pool is highly skilled, technically rigorous, and already comfortable building at the frontier of modern technology.”

A highly selective funnel

Antler’s Japan operation remains sharply selective. Since entering the market in 2022, the firm has funded 20 companies out of more than 2,100 applications — an acceptance rate of roughly 0.5 per cent. The 2025 cohort reflects a clear strategic tilt: founders building for international markets from day one, often combining Japanese technical depth with global operating experience.

Each of the 10 startups received ¥24 million in pre-seed funding through Antler’s Inception Residency model, which supports founders from company formation through early validation and investor readiness.

The portfolio spans sectors where Japan’s strengths in engineering, manufacturing, and compliance-heavy industries create defensible advantages. These include Refined Robotics, which is developing wheel-legged delivery robots claimed to be up to 25 times more energy-efficient; Logistical, which uses AI to reduce empty freight runs in transport networks; and Rubi Labs, whose “Lapis” platform targets AML and counter-terrorism financing risks by detecting anomalies across fragmented KYC and transaction systems.

Also Read: Forget China and the US–Japan is the true powerhouse of mobile game spending

Other companies include KanjuTech, working on brain-inspired AI for autonomous systems that requires significantly less data and energy; Smart Tissues, which is developing biomaterials for chronic wound healing; and Snappy Compliance, an AI-driven regulatory automation platform for robotics firms.

Why Japan, and why now

Japan’s startup ecosystem has historically lagged peers in Southeast Asia and the US due to risk-averse corporate culture, limited early-stage capital, and founders content with domestic scale. That calculus is beginning to change.

Venture capital deployment in Japan reached roughly US$7 billion in 2025, up 20 per cent year-on-year, driven largely by AI, robotics, biotech, and enterprise technology. Labour shortages, supply chain reconfiguration, and demographic pressures are accelerating enterprise demand for automation and applied AI.

Government intervention has also played a role. Startup visas, large public funds, and renewed industrial policy have lowered barriers for both domestic and foreign founders. Notably, every Japanese company Antler added to its portfolio in 2025 included at least one international founder.

“The Japan market offers access to world-leading customers across multiple verticals, strong and resilient supply chains, a highly skilled and affordable talent pool, and increasingly positive signals around startup support and capital availability,” said Florian Geier, senior director at Antler Japan.

A regional strategy, not a local one

Antler’s Japan strategy is closely tied to its broader Asia footprint, including Singapore and Southeast Asia. Japanese startups in its portfolio are testing expansion, partnerships, and customer acquisition across ASEAN markets earlier in their lifecycle, while founders from the region increasingly view Japan as a base for R&D and enterprise access.

The firm sees Japan as a long-term core hub within its 27-location global platform, rather than a standalone market. Investor Demo Day for the 2025 cohort is scheduled for February 13, targeting downstream investors across Asia.

The next Inception Residency will begin on May 11, 2026, aimed at technically strong founders with global ambitions.

Also Read: “SEA + Japan is a long game”: MUIP’s Gerrard Lai on cross-border startup collaboration

For Antler, the strategy is clear: deploy more capital earlier, raise the bar on founder quality, and lean into Japan’s underutilised strengths. In an early-stage market often dismissed as slow-moving, the firm is betting that disciplined aggression — not incrementalism — will produce the next generation of globally relevant companies.

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Most people think only big corporations can be “learning organisations.” They imagine expensive HR departments, internal academies, and endless workshops.

But the truth is the opposite: SMEs actually have the best conditions for continuous learning.  No bureaucracy. No silos. No political layers. Just the need to move fast, solve problems, and adapt.

The tragedy is that most small businesses never convert their hard-earned experience into reusable knowledge because they just lack the structure.

Every time someone resigns… Every time a project ends… Every time a mistake repeats…

They lose time, money, and momentum. Not because they lack talent, but because they lack retention.

This is the hidden threat every SME faces: Knowledge leakage.

Big corporations talk about “knowledge management.” Small businesses live or die by it.

Where SMEs bleed knowledge

Unlike corporates, SMEs rely on:

• A handful of key operators
• Undocumented processes
• Tribal knowledge held in people’s heads
• Informal “verbal SOPs” that change daily

So when one employee leaves, an entire workflow evaporates. When one client asks a recurring question, someone rebuilds the answer from scratch. And when training is needed, everyone is too busy “doing” to teach.

This isn’t incompetence. It’s the reality of survival-mode environments where execution outruns organisation.

But in 2025 and beyond, SMEs that fail to build learning systems will fall behind:

Not because they can’t work hard, but because they can’t scale wisdom.

Also Read: Gaming in SEA: Understanding the growing opportunity for SMEs and payment providers

Why learning organisations beat big corporations

A large company needs endless meetings, frameworks, and departments just to update a process.

An SME can change course in a single afternoon if it has internal clarity.

Learning organisations inside SMEs move faster because they:

• Shorten onboarding
• Reduce repeated mistakes
• Scale consistent quality
• Unlock multi-role capability
• Build internal leadership early
• Adapt to market signals quickly

SMEs don’t need bureaucracy to grow. They need structure without stagnation.

The truth is: Small businesses that systematise learning, not just hire talent, will outgrow bigger, slower firms.

How SMEs can become learning organisations (without red tape)

Document as you go — not “at the end”

Most SMEs fail because documentation is treated like homework. Instead, bake it into the workflow:

• After finishing a task, take five minutes to record how it was done.
• Use Loom, Notion, Google Docs, or even WhatsApp voice notes.
• Store every win, mistake, and shortcut in a central, searchable place.

Every successful project hides a repeatable blueprint. Capture it before it disappears.

Build a micro-learning culture

Forget two-hour seminars or quarterly training sessions — SMEs don’t have that luxury.

Instead:

• Run 10-minute weekly learning huddles.
• Share a quick win, a mistake, or a tip from a real client project.
• Let junior staff present what they learned that week.

Small, frequent learning beats big, infrequent training.

Make mentorship operational, not theoretical

Mentorship programs fail because they’re abstract. But SMEs can embed mentorship inside the work itself:

• Pair juniors with seniors on live tasks.
• Let juniors own 10–20 per cent of a project with supervision.
• Rotate roles weekly so everyone touches different functions.

This builds multi-skilled talent faster than any classroom.

Also Read: AI adoption is an area of maturity for SMEs, but they have advantage over big corporations: Aicadium’s Robert Young

Use AI as the “second brain” of the company

AI transforms SMEs into learning organisations by:

• Recording institutional knowledge
• Generating SOPs from your past projects
• Turning conversations into playbooks
• Storing templates, workflows, and client responses
• Assisting new hires with context and memory

The SME that uses AI as a knowledge repository becomes more resilient than one reliant on individual memory.

Reward knowledge contribution

Most SMEs reward “output.” Learning organisations reward “transfer.”

Incentivise staff for:

• Writing SOPs
• Recording tutorials
• Teaching juniors
• Improving old processes
• Sharing insights after client projects

When people are rewarded for teaching, the company stops losing knowledge.

The future belongs to SMEs that learn faster than they grow

Being a learning organisation isn’t about:

• Hiring more managers
• Creating more slides
• Building more departments

It’s about building systems of retention so that experience compounds instead of evaporates.

Big companies talk about “knowledge management.” Small companies don’t need the jargon; they need to build the habit and process.

Because the real competitive advantage isn’t the talent you hire — it’s the knowledge you keep.

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