Singapore’s rapid AI adoption is no longer a question of ambition. It is now a reality shaping enterprise strategy across industries. Nearly every business leader surveyed in Hitachi Vantara’s latest State of Data Infrastructure 2025 Report reported some level of AI use, signalling that AI has moved firmly beyond experimentation.

But the report also delivers a clear warning: while adoption is widespread, long-term value is far less certain. As Singapore enterprises accelerate AI deployment, growing data complexity and cybersecurity risks are emerging as the next defining challenges.

Over the past two years, many organisations have embraced AI through pilots and early-stage deployments. Quick wins have come from automating routine processes, improving analytics, and supporting decision-making with machine learning tools. Hitachi Vantara’s research shows that 66 per cent of Singapore respondents say their organisation has already been successful using AI. However, confidence drops sharply when it comes to sustained returns. Only 23 per cent believe their organisation has industry-leading readiness to achieve long-term ROI from AI.

This gap highlights a critical turning point: AI adoption is no longer about whether companies can deploy AI tools, but whether they can support them at scale over time. The next phase of adoption will be defined not by innovation alone, but by operational resilience.

Data complexity becomes a strategic constraint

AI systems are only as effective as the data they rely on. As enterprises expand AI workloads, many are discovering that their data environments are fragmented across cloud services, legacy systems, and siloed business units.

Also Read: Singapore’s AI adoption surges, but data complexity raises security risks: Report

What once appeared as a technical issue is now becoming a strategic risk.

More than half of Singapore respondents (52 per cent) said data complexity makes it more difficult to detect a security breach. This finding underscores how sprawling infrastructure reduces visibility and increases vulnerability.

Instead of accelerating progress, unmanaged complexity can slow AI adoption by forcing organisations to spend more time cleaning data, integrating systems, and strengthening governance frameworks before AI can deliver meaningful outcomes.

In practice, the ability to simplify and modernise data infrastructure may become the true differentiator between enterprises that scale AI successfully and those that stall after early pilots.

AI adoption is also expanding the enterprise attack surface. As AI tools connect to sensitive datasets, internal applications, and privileged workflows, weak infrastructure can introduce new pathways for cyber threats.

The report found that 64 per cent of Singapore leaders agree that if executives fully understood how fragile their data infrastructure is, it would “keep them up at night.” This reflects a growing awareness that AI is not only an innovation driver but also a source of operational risk.

Moving forward, enterprises are likely to adopt a more security-first approach. AI investment decisions will increasingly depend on questions of trust, compliance, governance, and resilience — not just capability.

Organisations may demand stronger controls around credentials, access management, model usage, and vendor accountability. AI adoption will continue, but with higher expectations for security maturity.

Also Read: Low liquidity, high stakes: Why this crypto pullback feels different

ROI expectations will reset

The next chapter of AI adoption will also require a shift in mindset. Early success often comes from quick automation wins, but sustained ROI depends on discipline: monitoring, performance optimisation, governance, and cost control.

As AI becomes embedded in mission-critical operations, enterprises will become more selective, prioritising use cases with measurable business impact rather than broad experimentation.

The organisations that succeed will be those that treat AI as a long-term capability supported by strong infrastructure, not a standalone technology layer.

Singapore’s enterprises are already demonstrating a more risk-aware approach compared with earlier phases of AI expansion. Governance, reliability, and trust are becoming central themes, particularly as AI systems influence high-stakes business decisions.

This positions Singapore to set the tone for mature AI adoption across APAC, one that balances speed with security and innovation with resilience.

Ultimately, AI adoption will not slow down. But it is entering a more demanding phase, where success depends less on deploying models and more on building trusted, scalable foundations.

The companies that close the gap between adoption and readiness will define the next wave of AI-driven growth in the region.

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The lead image of this article was generated by AI.

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Kopi Kenangan, the Indonesia-founded coffee chain, reported its first full year of profitability for fiscal 2025 while continuing rapid international expansion and tightening governance in preparation for an eventual public listing.

CEO Edward Tirtanata claimed in a LinkedIn post that net revenue for FY2025 reached US$184 million, a 45 per cent increase year-on-year. Net profit was US$17 million, and EBITDA climbed to US$37 million.

Sequoia Capital-backed Kopi Kenangan ended the year with 1,324 stores across six countries and added 347 net-new outlets during the year. The chain’s digital ecosystem brought in 4.47 million new customers in 2025, and the firm reported a same-store sales growth (SSSG) of 15 per cent for the year.

Also Read: From a single brew to unicorn: Kopi Kenangan’s journey of coffee and creativity

The firm employs more than 8,000 people and plans roughly 550 new store openings in 2026.

A shift from growth-at-all-costs

The CEO framed the results as a shift from early-stage expansion toward disciplined, sustainable scaling. He described the company’s focus moving to fundamentals (revenue, profitability and capital allocation) and said the business is building processes and controls typical of companies preparing for an IPO.

Kopi Kenangan highlighted that it has maintained unqualified audit opinions from Big Four auditors over eight financial years and is accelerating its financial close and reporting cadence. The company is also investing in internal controls, tax and legal compliance, and data analytics to strengthen governance and due diligence readiness.

Performance across markets

In its largest market, Indonesia, Kopi Kenangan reported 40 per cent year-on-year revenue growth driven by solid same-store sales. In Malaysia, the company said revenue nearly doubled and that the business delivered positive EBITDA as unit economics improved with scale.

Kopi Kenangan also reported expansion into markets beyond Southeast Asia, naming India and Australia among its newer markets.

Technology and unit economics

The management attributed the fiscal-year performance to “technology-led customer acquisition,” pointing to the 4.47 million new customers acquired through its digital channels. It emphasised that increased scale improved unit economics — a point it presented as evidence that its model can be profitable rather than reliant on market-funded subsidies.

The firm’s stated goal is to “compound responsibly through cycles” rather than pursue top-line growth without regard for margins.

Context in Southeast Asia’s startup cycle

Tirtanata placed Kopi Kenangan’s results in the broader context of a regional reset. After a funding cycle driven by low interest rates, investor sentiment shifted, and many startups reoriented toward profitability.

He argued that the reset, while painful, was healthy for the region and that Southeast Asia still offers structural opportunities — demographic growth and economic expansion — for companies that prioritise unit economics and execution.

Outlook

Kopi Kenangan plans an aggressive rollout in 2026 (about 550 store openings globally) alongside continued efforts to tighten governance, speed up financial reporting and prepare documentation for potential public markets. The company presents its recent profitability and improved EBITDA as markers that it is transitioning from a rapid-growth startup to a more mature, investment-grade consumer business.

Also Read: Brewing success: A comparative analysis of Kopi Kenangan and Kopi Janji Jiwa coffee chains in Indonesia

By focusing on unit economics and “compounding responsibly,” Kopi Kenangan is positioning itself to be a resilient, long-term player in the global coffee market rather than a subsidised startup.

In 2026, one can expect the company to prioritise operational maturity alongside its aggressive physical expansion.

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Off the coast of Ireland, beneath the Atlantic Ocean, lies a vast nervous system of cables. These strands of fibre-optic wiring form the invisible infrastructure of our globalised world. These aren’t just conduits for internet traffic; they’re arteries of modern civilisation, carrying everything from financial transactions to state secrets.

And now, they’re under siege. This seabed has been making headlines as it is not just an ocean that connects us but underwater cables that ar the lifeline of our virtual connections. In todays world we are seeing daily threats to the very infrastructure that allows us the freedom to connect, explore and trade with the rest of the world.

The hyper-sensitivity to globalisation has inserted fear where there was opportunity. Instead of viewing these connections as extremely valuable points of cultural intersections we are seeing them as threats to the viability of local industries. 

It is not just the fibre-optic wiring stretching thousands of miles across the seabed that is threatened, but rather the ability to operate, trade and communicate globally. Stability in geopolitics is crucial for doing business in all shapes and forms today. 

As recent global tensions rise, cybersecurity threats multiply, and there is an increasing risk of disruption. 

The new frontline is digital

The world is teetering on the edge of a new era, one where firewalls matter more than fences, and zero-day exploits can be as devastating as missile strikes. “I look at the current political landscape and see a world under strain,” says Rhythm Jain, a Marketing Development Manager at Resonance Security.

This battleground is vast and largely invisible, stretching from the inboxes of public officials to the seabeds off Ireland’s coast. In 2024, NATO released a bold new strategy to secure undersea infrastructure, citing increased Russian submarine activity near British waters. The message is clear: cables are now targets, and data is a strategic asset.

The cables are just one piece. From the 2020 SolarWinds breach to daily ransomware attacks on hospitals and water systems, it’s clear that the digital realm is now where the most consequential battles are fought.

“If you’re building anything that holds value, you’re a target,” says Jain. In a world where physical borders blur and kinetic warfare feels like an artifact of the 20th century, the real battles are happening in code. The firewalls of corporations and nations alike are now the new frontlines, and the stakes have never been higher.

“Geopolitical rivalries, economic uncertainty, and fractured alliances are fuelling a surge in cyber threats. Tensions between major powers like the US, China, and Russia, alongside regional flashpoints like Iran or North Korea, have turned cyberspace into a battleground.”

The past decade has seen an explosion in digital espionage, ransomware, and infrastructure sabotage. From hospitals being locked down by ransomware during a pandemic to energy pipelines halted by keystrokes, it’s clear, cybersecurity is now a necessity.

Also Read: AI power shift: How geopolitics and innovation are rewriting global rules

Vital infrastructure is exposed and vulnerable

Modern critical infrastructure including power grids, healthcare networks, financial systems were never designed with state-sponsored hackers in mind. “I believe ransomware attacks on critical infrastructure are a growing threat, often fueled by geopolitical tensions,” says Jain. “They exploit weak identity and access controls, letting hackers lock up vital systems.”

The situation demands a radical rethink. Blockchain-based decentralised identity (DID) systems are being explored as a solution, offering cryptographic verification instead of passwords and making impersonation significantly harder.

“Blockchain’s strength is its decentralised, tamper-proof ledger,” says Jain. “Imagine a power plant where every technician’s access is verified on a blockchain; hackers couldn’t easily impersonate someone to gain entry.”

Early implementations are promising, with companies experimenting with blockchain to verify machine identities and reduce unauthorised access to vital infrastructure. But this tech isn’t 100 per cent secure.

“Blockchain doesn’t stop phishing or social engineering. It’s also resource-heavy. And if private keys are mismanaged, then the whole system becomes vulnerable.”

In other words, there is no silver bullet but there is a smarter way forward. And it starts with layered, adaptive defenses built on a deep understanding of threat evolution.

Regulation is a hot topic

As cyber threats escalate, so too does the conversation around regulation. But not all regulation is created equal.

“Regulations create a baseline,” says Jain. “They force companies and institutions to adopt minimum standards: multi-factor authentication, encryption, incident response plans. Without that push, many organisations wouldn’t prioritise security until it’s too late.”

However, regulation can backfire when reduced to checklists and certifications. “Compliance is not security,” he warns. “I’ve seen companies with all the right certifications still fall victim to ransomware because no one was monitoring their logs.”

The solution? Thoughtful oversight that prioritises real-world resilience over audit-readiness. “The goal of regulation should be to raise the floor, not define the ceiling. It should encourage companies to build a real security culture and not just tick boxes once a year.”

Also Read: Asia’s trade turning point: How tariffs and geopolitics are redrawing supply chains

Security experts are a voice of reason in the storm

This fragmentation of global digital infrastructure has global implications. If countries begin developing separate, competing networks, the internet as we know it could become increasingly divided, where national security priorities override the free flow of information. 

For businesses, this could mean increased costs and inefficiencies as they navigate multiple regulatory and security frameworks. For individuals, it could mean a future where access to information is dictated by geopolitics rather than technological progress. 

Addressing these risks requires a multi-pronged approach. First, international cooperation must be strengthened to safeguard all infrastructure. The US and its allies are also working on developing quantum encryption technologies to prevent cyber intrusions on data transmitted through undersea cables. Secondly, offering public and private partnerships where security experts can provide case studies, evidence, and education with regards to vulnerable areas of work.

Welcome to the era of cyber geopolitics where the interconnected world is adding layers of new security challenges. By safeguarding the infrastructures that unite us and thoughtfully navigating the currents of globalisation, we can transform challenges into avenues for cooperation and mutual growth. How nations respond in the coming years will determine whether the internet remains a tool for progress or a source of conflict.

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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.”

The post Building SEA climate tech ecosystem: Why urgency, policy, and alignment matter appeared first on e27.

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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