Author: Ruthc

Singapore’s financial sector is moving to coordinate its defence against a new generation of cyber threats, as frontier artificial intelligence models begin to change how attacks are planned, scaled and executed.

The Monetary Authority of Singapore (MAS) and the Association of Banks in Singapore (ABS) have established the AI-Driven Cyber and Technology Risk Taskforce, or ACT, an industry-wide group aimed at strengthening the sector’s collective cyber and technology resilience. The taskforce has brought together members since May 2026, MAS and ABS said in a statement.

Also Read: Ransomware in Singapore is becoming a human problem, not just a malware one

ACT includes MAS, ABS, DBS, OCBC, UOB, Singapore Exchange, Network for Electronic Transfers, and Banking Computer Services. Its remit is to help financial institutions understand and respond to AI-enabled threats through shared learning, trials of defensive tools, and new guidance on controls and response measures.

The move reflects a growing concern among regulators and financial institutions globally: AI is no longer just a tool for improving productivity or customer service. In the hands of attackers, it can also lower the cost of cybercrime, speed up reconnaissance, and make phishing, malware development and vulnerability discovery more effective.

“Frontier AI is increasing the severity, scale and sophistication of cyber threats. The financial sector must respond with urgency and through strong collaboration,” said Vincent Loy, Assistant Managing Director for Technology and Chief Technology Officer at MAS.

Why AI changes the cyber equation

Banks and financial market infrastructure providers have long been prime targets for cybercriminals, given the value of the data and transactions they handle. But frontier AI models add a new layer of complexity.

These systems can be used to rapidly scan code, identify weak points in digital infrastructure, draft convincing social engineering messages, and automate parts of an attack chain. A less skilled attacker may now be able to perform tasks that previously required more technical expertise. More capable groups, including state-linked actors, can use AI to accelerate operations that are already sophisticated.

For Singapore, the issue is especially sensitive. The city-state is both a regional financial hub and a major technology node for Southeast Asia. Its banks, exchanges and payment systems serve consumers, corporates and investors across borders. A serious disruption would not remain a local operational incident; it could affect regional confidence in digital banking, payments and capital markets.

This is why MAS and ABS are framing the response as a sector-wide effort rather than a matter for individual institutions alone. In a connected financial ecosystem, one organisation’s weakness can become another’s exposure, particularly when vendors, payment rails, cloud systems and shared infrastructure are involved.

ACT will focus on three areas: industry collaboration, capability uplift, and guidance development.

The first is information sharing. Financial institutions will exchange AI cybersecurity use cases and experiences, and engage with cybersecurity and AI experts. This matters because AI-enabled threats are still developing quickly, and no single institution is likely to have a complete view of the risk landscape.

The second is practical capability building. The taskforce will help uplift cyber defence knowledge and conduct proof-of-concept trials to test advanced AI-enabled defensive tools. This suggests the group will not only discuss risks in principle but also experiment with ways to detect, prevent and respond to them.

Also Read: Cybersecurity in the AI age: How startups can stay ahead

The third is guidance. ACT will work on measures, controls and solutions that financial institutions can adopt to improve their cybersecurity posture against AI-enabled threats.

A regional signal from Singapore

Singapore has often set the tone for financial technology regulation in Southeast Asia. Its approach tends to combine innovation with tight operational and risk-management expectations. The creation of ACT fits that pattern.

Across the region, banks and fintech firms are racing to use AI for customer support, fraud detection, credit assessment, compliance and internal automation. At the same time, regulators are under pressure to ensure that faster adoption does not create hidden weaknesses.

AI risk is not limited to model bias or data privacy. It also includes operational resilience: whether critical systems can withstand attacks, whether staff can identify AI-generated fraud, whether vendors are secure, and whether incident response plans are ready for machine-speed threats.

This is particularly relevant in Southeast Asia, where digital finance has expanded quickly over the past decade. Mobile wallets, instant payments, digital banks and embedded finance platforms have brought millions of users into the formal financial system. That growth also broadens the attack surface. Cybercriminals now have more digital entry points, more user data to exploit, and more interconnected platforms to target.

Singapore’s taskforce could therefore become a reference point for neighbouring markets. While each country has its own regulatory structure, the underlying challenge is shared: financial institutions need to defend against attackers who are adopting the same technologies that banks themselves are using to modernise.

Collaboration over isolated defence

The most notable feature of ACT is its collective structure. It brings together regulators, major banks, exchange infrastructure, payments players and technology service providers.

That matters because cyber resilience in finance is rarely about one organisation alone. A phishing campaign targeting bank employees may use information stolen from a vendor. An attack on payment infrastructure may affect merchants, consumers and banks at once. A flaw in a third-party technology stack can spread risk across multiple institutions.

A coordinated taskforce can help reduce duplication, speed up learning and establish common expectations. It can also create a safer environment for testing defensive tools, especially when AI systems themselves can introduce new risks if poorly implemented.

The proof-of-concept trials will be worth watching. AI can help defenders by analysing large volumes of alerts, detecting anomalies, generating threat intelligence and assisting security teams during incidents. But these tools need careful governance. False positives can overwhelm teams; false negatives can create misplaced confidence. Models can also be manipulated through adversarial inputs or compromised data.

Also Read: AI phishing is turning trust into APAC cybersecurity’s weakest link

Ong-Ang Ai Boon, Director of ABS, said AI is reshaping the cyber threat landscape and that the financial sector must move together to stay resilient. She added that close coordination, governance and continued partnership with regulators and industry stakeholders would be central to strengthening cyber and technology resilience.

Her emphasis on governance is important. The question is not simply whether banks can buy or build more AI tools. It is whether they can deploy them responsibly, monitor them continuously, and ensure human accountability remains clear when automated systems are involved in cyber defence.

The next test: execution

ACT’s creation is timely, but its impact will depend on execution. Information sharing must be specific enough to be useful. Guidance must keep pace with evolving threats. Proof-of-concept trials must lead to practical adoption, not just reports.

The taskforce will also need to account for smaller financial institutions and ecosystem players that may not have the same cyber budgets as major banks. In Southeast Asia’s digital finance landscape, risk often travels through the weakest link. Strengthening only the largest players will not be enough if attackers can exploit smaller vendors, fintech partners or outsourced service providers.

Still, the initiative is a clear sign that Singapore sees AI-enabled cyber risk as a systemic issue. The financial sector’s response cannot be fragmented, slow or purely reactive.

As frontier AI becomes more capable, the line between cyber offence and defence will keep shifting. Singapore’s bet is that the best response is not for each institution to fight alone, but for the sector to build shared muscle before the next wave of attacks arrives.

The post MAS, ABS launch ACT taskforce as AI raises cyber risks for banks appeared first on e27.

The crypto market woke up Wednesday morning with a modest but telling 1.08 per cent gain, pushing total market capitalisation to US$2.19 trillion. On the surface, that number looks unremarkable. Dig a little deeper, though, and you find a market that has tethered itself almost entirely to a single narrative: the belief that Washington is finally about to hand digital assets a coherent regulatory framework. The 85 per cent correlation between crypto and the S&P 500 tells you everything you need to know about where this move originates. This is not a grassroots rally driven by organic demand. This is a macro-driven trade, and it lives or dies on whether the Clarity Act delivers what traders have been pricing in for weeks.

The anticipation around the Clarity Act has consumed social channels and trading desks alike. Analysts have drawn direct lines between Bitcoin forming a falling wedge pattern and what they describe as the legislation entering its final phase. Whether or not you trust technical chart patterns, the psychology here is unmistakable. Traders want a reason to commit capital, and regulatory clarity represents the single biggest unlock for institutional money that has sat on the sidelines for years. Bitcoin dominance dipped slightly as fresh capital entered the broader market, suggesting that participants are not just buying the safe haven. They are spreading risk across the ecosystem because they believe the regulatory umbrella will extend beyond Bitcoin.

That conviction shows up most vividly in the altcoin rotation. I see quite a few of them surging by 30-70 per cent, and some with over 8,000 per cent volume explosion. These are not gentle, measured allocations. These are aggressive, speculative bets from traders who believe the macro and regulatory backdrop has shifted enough to justify chasing leveraged returns in higher-beta assets. The Altcoin Season Index, at 51, confirms that the environment remains balanced rather than euphoric, while the directional flow is clear. Money is rotating out of cash and into risk. That rotation amplifies the headline gain and gives the market a sense of momentum that a 1 per cent move alone would never convey.

Also Read: Malaysia, Singapore investors rebalance portfolios without ditching crypto

Now here is where the crypto story and the equity story become inseparable. US markets closed mixed on Tuesday evening, revealing a powerful undercurrent that crypto traders cannot ignore. The Dow Jones surged 537.24 points, or 1.03 per cent, to close at 52,747.32. The S&P 500 added 15.60 points, or 0.21 per cent, to finish at 7,428.78. But the Nasdaq Composite slipped 55.17 points, or 0.22 per cent, to 24,876.91, as the PHLX Semiconductor Index plummeted 4.5 per cent in a single session. Investors hammered AI and chip names over mounting worries about excessive data centre capital expenditures. Meanwhile, healthcare gained 2.33 per cent and consumer staples rose 1.96 per cent, with seven of 11 primary S&P 500 sectors closing in the green. Sherwin-Williams spiked 8 per cent on a strong Q2 earnings beat, and defensive anchors like Boeing, Coca-Cola, IBM, Salesforce, and Amgen all rallied 5 per cent or more to prop up the Dow. The S&P 500 Equal-Weighted Index hit fresh record highs. This is a market rotating away from concentrated tech risk and into breadth. Crypto, with its 85 per cent correlation to the S&P 500, rides this same wave.

The macro backdrop adds another layer of complexity. Brent Crude collapsed 4.83 per cent to settle at US$84.09 a barrel, while WTI Crude fell 4.06 per cent to US$79.26, marking the worst three-day stretch for global energy benchmarks since April 2020. The trigger was a mutual pause in hostilities and diplomatic talks regarding the Strait of Hormuz between the US and Iran. Early Wednesday Asian trading saw a minor 4 per cent rebound following reported regional skirmishes, but the directional damage was done. Lower oil prices eased inflation fears, pushing the 10-year US Treasury yield down to 4.60 per cent. That declining yield environment supports risk assets, including crypto. The Conference Board Consumer Confidence Index slipped to 90.8 in July from 92.2 in June, missing the consensus projection of 92.0. Households cited inflation fatigue and emerging labour market pessimism. That softening consumer backdrop reminds us that the real economy has not fully caught up to the optimism trading desks are expressing.

The international picture reinforces how interconnected this moment has become. South Korea’s KOSPI index triggered a circuit breaker on Wednesday morning as the unwind in AI chips hammered Asian tech corridors. Samsung suffered one of its worst single-day drops in nearly 20 years amid domestic capital constraints and rising competition from Chinese equipment suppliers. Australia’s ASX 200 pointed toward positive territory, buoyed by relief from lower global oil prices. The contagion from the semiconductor selloff is real, and it reminds crypto participants that their 85 per cent correlation to equities means they cannot escape global risk-off episodes.

Also Read: Regulation crypto is here: The 400-page rule that could kill or save American crypto innovation

Looking ahead, the final days of July carry an extraordinary concentration of catalysts. The Federal Reserve delivers its rate decision on Wednesday afternoon under new Chair Kevin Warsh at his second meeting. Most participants expect a hold, but the market is scanning for hawkish forward guidance given Warsh’s strong stance against inflation. Microsoft and Meta report quarterly results late Wednesday, followed by Apple and Amazon on Thursday. US Q2 GDP and PCE Inflation data both land before the week concludes. Any of these events could shift the risk appetite on which crypto currently depends.

For the crypto market specifically, the technical picture frames the near-term path. The market is testing the 23.6 per cent Fibonacci resistance at US$2.21 trillion. A confirmed break above that level could propel total capitalisation toward the swing high of US$2.26 trillion. Failure at resistance may trigger a retest of the 50 per cent retracement and pivot support at US$2.15 trillion. The Clarity Act outcome sits at the centre of this equation. If it delivers genuine regulatory structure, the breakout scenario gains conviction. If it disappoints or delays, the market loses its primary narrative and faces a painful unwind of speculative positioning.

It’s fragile. The uptick we see today rests on regulatory hopes and rotational buying rather than structural shifts in demand. Conviction remains thin ahead of a definitive policy signal. The 85 per cent equity correlation suggests crypto traders are essentially macro traders right now, and the next 48 hours will test whether this rally has legs or collapses the moment a single catalyst misses expectations. The Clarity Act must deliver. Everything else is noise until it does.

The post The market is pricing in regulatory clarity that does not exist yet. Why crypto is fragile? appeared first on e27.

StepHow tests citation-first AI assistant with Tallinn in govtech push
For many city officials, the hardest part of answering a public query is not the answer itself. It is finding the correct document, checking whether it is still valid, and proving where the answer came from.

StepHow, a B2B AI company led by CEO Jasper Hwang, is now trying to solve that problem in one of the world’s most digitised city governments. The company has been selected for the City of Tallinn’s Test in Tallinn innovation programme and has signed a memorandum of understanding with the Estonian capital to begin a proof of concept for its AI-based data search and chatbot product, Wissly.

Also Read: How to drive business innovation with AI-powered data analytics

The project will test whether Wissly can help Tallinn officials search across multiple administrative systems, manage documents more efficiently, and generate evidence-backed answers from public records. Rather than simply producing a conversational response, the system is designed to show where each claim comes from, with direct links to source documents.

That detail matters. As governments experiment with generative AI, the central question is no longer whether chatbots can produce polished answers. It is whether public agencies can trust them when accuracy, auditability, and citizen rights are at stake.

A test inside a mature digital government

Tallinn is a meaningful testing ground because Estonia has long been viewed as a benchmark for digital government. The country is known for its national digital identity infrastructure, online public services, and a policy culture that treats digital access as part of the state’s operating model rather than an add-on.

StepHow’s PoC will sit inside that environment, connecting Wissly to three Tallinn information systems. The first is Teele, the city’s legal acts information system, used for drafting and processing legal acts, resolutions, and directives from the Tallinn City Council, City Government, and related authorities.

The second is AKIS, the public gatherings information system, which manages public events and gathering permit processes in Tallinn. The third is Postipoiss, the city’s document management system, which stores and processes major administrative documents and correspondence, including the 2026 contracts register.

StepHow delivered a working demo of Wissly to the Tallinn project team on June 23 and launched the testing environment. The assistant works on both desktop and mobile devices. Internal users can ask questions in Estonian or English, after which the system searches connected administrative data in real time and generates answers using what the company describes as a “citation-first” approach.

In practice, that means every claim in an answer is tied to a source link from the original document. This is StepHow’s attempt to address one of the biggest weaknesses of large language models: their tendency to produce plausible-sounding but unsupported answers.

Why citations are the core feature

For consumer chatbots, a vague answer can be irritating. In public administration, it can create legal and operational problems.

Officials handling permits, contracts, legal acts, or public correspondence need to know not just what a system says, but why it says it. If an AI assistant summarises the wrong version of a document, misses a later amendment, or cites an irrelevant source, the cost may be borne by citizens, businesses, or other departments.

Also Read: Can your AI actually read your data?

That is why the Tallinn PoC is limited to designated internal staff and uses only publicly available public data and PDF documents. The restricted scope reduces risk while allowing the city and StepHow to test whether the system can cope with real administrative workflows.

The collaboration is scheduled to run until November 30, 2026. Depending on the results, the two sides may discuss a citizen-facing service expansion, further pilots, or a commercial deployment.

“We are thrilled to undertake this innovative validation agreement with the City of Tallinn, a global benchmark for digital governance,” said Hwang. “Through Wissly, which enables question-answering and rigorous evidence verification for public records, we will maximise administrative efficiency and ultimately demonstrate the welfare benefits of innovating how citizens access public information.”

What Southeast Asia can take from the experiment

Although the project is in Europe, its relevance extends to Southeast Asia, where governments are also pushing digital public services but often face fragmented back-end systems.

Singapore has been early in adopting digital identity, data exchange frameworks, and government technology platforms. Indonesia, the Philippines, Vietnam, Malaysia, and Thailand are also investing in digital government services, though implementation varies widely between national agencies, local governments, and legacy departments.

The problem StepHow is addressing is familiar across the region: information exists, but it is scattered across portals, PDFs, old databases, and internal records. A citizen may want to understand a permit requirement. A civil servant may need to confirm whether a policy is still valid. A business may need clarity on licensing or procurement rules. In many cases, the bottleneck is not the absence of information, but the difficulty of retrieving and verifying it quickly.

That is where AI search could be useful, especially in multilingual societies. Southeast Asia’s public sector operates across languages, dialects, and varying levels of digital literacy. But the region also presents a harder challenge than a controlled internal PoC. Citizen-facing AI in markets such as Indonesia or the Philippines would need to handle local languages, uneven document quality, inconsistent data structures, and politically sensitive public information.

Tallinn’s test therefore offers a useful but limited reference point. It shows how a city with mature digital infrastructure might trial AI safely before public rollout. For Southeast Asian governments, the larger lesson may be procedural: start with bounded use cases, require citations, restrict sensitive data, and test systems with officials before exposing them to the public.

A crowded field for enterprise AI search

StepHow is entering a competitive space. Enterprise AI search and workplace assistants have become a major battleground since the rise of generative AI. Globally, players such as Glean, Microsoft Copilot, Google Vertex AI Search, OpenAI’s enterprise products, and AWS-backed AI services are all trying to help organisations search internal knowledge and automate routine information work.

In the public sector, StepHow may also run into competition from large systems integrators and govtech vendors that already manage government document platforms, identity systems, and cloud infrastructure. Its differentiation, based on the Tallinn project, appears to be a focus on citation-heavy administrative search rather than a general-purpose productivity assistant.

For a smaller AI company, that specialisation can be an advantage if it proves reliable. Public agencies are unlikely to adopt tools that cannot show their sources. But selling into government also means long procurement cycles, security reviews, localisation demands, and accountability requirements that are more demanding than typical enterprise software sales.

The Tallinn PoC will not, by itself, prove that Wissly can scale across governments or markets. It will, however, test the product in a demanding environment where document accuracy and institutional trust are central.

Also Read: Singapore’s data analysts trust AI to work, not to think

If StepHow can show that its assistant reduces the time officials spend searching records without sacrificing reliability, the company may gain a useful reference case for Europe and, potentially, for digital government projects in Asia.

For now, the real story is not that Tallinn is testing another chatbot. It is that the next phase of AI in government may be less about flashy automation and more about something less glamorous but far more important: helping public servants find the right answer, and prove it.

The post Tallinn taps StepHow to test AI assistant for public-sector document search appeared first on e27.

Atome Financial has reported its strongest year yet, with revenue rising 80 per cent year-on-year to US$470 million in 2025, as the Singapore-based digital financial services platform expanded its lending book, merchant network, and card products across Southeast Asia.

The company, which comprises Atome’s buy-now-pay-later business, Atome Card, and Indonesian digital lending platform Kredit Pintar, also said it remained profitable before tax for the second consecutive year. It did not disclose its profit figure.

Also Read: Atome’s US$88M AUB facility tests the next phase of Philippine BNPL

Total operating income reached US$360 million, up 52 per cent from 2024, while gross merchandise volume (GMV) crossed US$4 billion during the year, an increase of more than 60 per cent. GMV refers to the total value of transactions processed on the platform before deductions such as refunds, fees, or other adjustments.

The numbers come at a time when Southeast Asia’s consumer credit market is being reshaped by embedded finance, digital lending, and card-linked instalment products. Traditional banks still dominate formal lending, but fintech platforms have found room to grow by serving younger consumers, online shoppers, small merchants, and underbanked borrowers who may not have easy access to conventional credit cards or personal loans.

Atome’s latest figures suggest that the company is no longer just riding the early wave of BNPL adoption. It is trying to position itself as a broader digital finance platform, one that combines instalment payments, cards, lending, insurance, savings, and merchant financing across multiple markets.

Momentum carries into 2026

Atome said its growth has continued into 2026. As of June, annualised net revenue had reached US$800 million, up 55 per cent year-on-year, while annualised GMV crossed US$6 billion, up 64 per cent.

Annualised figures are not the same as full-year results. They usually take a shorter reporting period and project it over 12 months. Still, they give a useful indication of the pace at which the business is currently running, especially for companies in high-growth lending and payments segments.

One of the company’s key drivers has been product adoption in the Philippines. Atome’s PayLater Anywhere Card crossed three million cards issued as of June 2026. The product allows users to pay later beyond Atome’s merchant network, effectively turning BNPL into a more flexible card-based credit product.

The card was also launched in Malaysia earlier this year, giving Atome another route to deepen engagement in a market where digital banking, e-wallets, and instalment payment products are becoming increasingly competitive.

The company also credited its growth to wider merchant partnerships, new product rollouts, loan book expansion, and the use of artificial intelligence across operations. In fintech, AI is often used to improve credit underwriting, detect fraud, automate customer service, and prioritise collections. The real test is whether these tools can support faster growth without weakening asset quality.

Also Read: Atome lines up US$345M debt as Southeast Asia fintechs shun equity

That question matters because digital lenders and BNPL platforms depend not only on transaction volume, but also on their ability to manage defaults. Rapid loan book expansion can lift revenue in the short term, but poor credit controls can quickly turn growth into losses.

Funding lines become a competitive weapon

Atome Financial has also been strengthening its funding base, which is critical for any lending-led platform. The company recently secured a PHP5 billion, or US$81 million, facility with Asia United Bank in the Philippines. The local currency facility adds to its funding stack and reduces some of the foreign exchange mismatch that can arise when lending in regional markets.

Earlier this year, Atome also announced an upsized US$345 million syndicated facility to support growth across Southeast Asia.

This access to institutional funding is one of Atome’s key advantages. Its funding partners include Standard Chartered, HSBC, Bank Jago, DBS Bank, SMBC, BlackRock, EvolutionX Capital, and InnoVen Capital. The company is part of Advance Intelligence Group, which is backed by investors including SoftBank Vision Fund 2, Warburg Pincus, Northstar, and Singapore-based EDBI.

For digital lenders, funding is not merely balance-sheet plumbing. It determines how much credit they can extend, how competitively they can price products, and how resilient they are when capital markets tighten. In Southeast Asia, where interest rates, currency movements, and consumer credit risk vary widely by country, diversified funding lines can help platforms expand without relying too heavily on a single market or source of capital.

The Philippines facility is particularly notable because the country has become one of the region’s most active fintech markets. It has a large young population, high mobile usage, and still-significant gaps in formal credit access. At the same time, regulators have become more alert to consumer protection, data privacy, and aggressive debt collection practices in digital lending.

BNPL grows up, but scrutiny follows

Atome’s results also land in a more mature phase for BNPL. During the pandemic-era e-commerce boom, BNPL companies benefited from a surge in online shopping and merchant demand for conversion tools. But globally, the sector has since faced pressure from higher funding costs, regulatory scrutiny, and questions over consumer overborrowing.

In Southeast Asia, the picture is more nuanced. BNPL remains attractive because credit card penetration is still uneven, and many consumers are comfortable with mobile-first financial products. Merchants, meanwhile, use instalment options to increase basket sizes and reduce friction at checkout.

Also Read: Atome defies market headwinds with 63 per cent income surge, US$4B GMV run rate

But regulators are watching more closely. Singapore has introduced a BNPL code of conduct, while other Southeast Asian markets have been tightening rules around digital lending, disclosures, debt collection, and consumer affordability. For platforms such as Atome, the next phase of growth will likely depend on whether they can show not just scale, but responsible lending discipline.

This is where profitability before tax becomes important. Many fintechs in the region spent years prioritising user growth over earnings. Atome’s claim of a second consecutive year of pre-tax profitability suggests a shift towards more sustainable expansion, though the absence of detailed profit and credit-loss figures makes it difficult to assess the quality of those earnings from the announcement alone.

Rivals crowd the same opportunity

Atome operates in a crowded and increasingly blurred competitive field. In Southeast Asia, it competes with digital finance and lending players such as Kredivo, Akulaku, SeaMoney’s SPayLater, and Grab’s financial services ecosystem. In specific markets, it also faces banks, e-wallets, digital banks, credit card issuers, and local lending platforms that are adding instalment and pay-later features.

Globally, the broader BNPL category includes names such as Klarna, Affirm, and Block-owned Afterpay, though their market focus and operating models differ from Atome’s Southeast Asian playbook. The competitive pressure is not only about who can sign more merchants or issue more cards. It is about underwriting, funding cost, regulatory trust, and the ability to turn transaction relationships into broader financial services.

Atome’s regional footprint gives it exposure to some of the fastest-growing consumer markets in Asia. But it also means operating across countries with different credit bureaus, payment habits, languages, regulations, and collection environments. Scaling a credit business across Southeast Asia is rarely straightforward.

The company’s 2025 results show that demand for flexible consumer finance remains strong. Its 2026 run-rate figures suggest that momentum has not slowed. The harder task now is to prove that this growth can hold through a full credit cycle.

For Southeast Asia’s fintech sector, Atome’s trajectory reflects a wider shift. The winners in digital finance will not simply be the companies that acquire the most users. They will be the ones that can pair distribution with disciplined lending, stable capital, and products that remain useful after the initial BNPL novelty fades.

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On a hot afternoon in Southeast Asia, a parked car can become almost unbearable within minutes. In some cases, the cabin temperature can climb to 70 to 90 degrees Celsius, turning the first blast of air-conditioning into a survival reflex rather than a comfort choice.

But air-conditioning carries its own contradiction. It cools the inside of a vehicle, home, mall, or factory, while releasing heat outside and drawing heavily on electricity. In cities from Singapore and Bangkok to Manila, Jakarta, and Ho Chi Minh City, this cycle worsens peak power demand and adds to the urban heat island effect, where concrete, asphalt, and glass trap heat long after sunset.

Korean deep-tech startup ZERC believes part of the answer could be as simple as paint.

Also Read: 5 Seoul startups made their Southeast Asia debut at Echelon Singapore 2026 under the SBA pavilion

Founded in November 2022 as a faculty startup from Korea University, ZERC is commercialising a water-based radiative cooling paint that can be applied to roofs, vehicles, ships, industrial equipment, and even safety helmets. The company was founded by Lee Heon, a professor in Korea University’s Department of Materials Science and Engineering, who has been working on materials that can lower surface temperatures without consuming electricity.

“We founded the company and have continued our research in order to create a practical breakthrough for the climate crisis and energy problems through a technology that lowers temperature without using electricity,” Lee said.

How radiative cooling works

Radiative cooling is not a new idea, but it has become more commercially relevant as global temperatures rise and electricity grids come under strain.

The basic principle is straightforward. A material reflects most incoming sunlight, preventing surfaces from absorbing heat. At the same time, it emits thermal radiation through what scientists call the “atmospheric window”, a range of infrared wavelengths that can pass through the atmosphere and escape into outer space.

In practical terms, the surface cools down without fans, compressors, refrigerants, or electricity.

ZERC says its water-based paint reflects 96 per cent of sunlight when applied at a thickness of 150 micrometres, roughly the thickness of a human hair. It also radiates more than 93 per cent of heat into space through the atmospheric window. In tests, the paint recorded a surface temperature about 4 degrees Celsius lower than ordinary water-based paint.

The company says the cooling effect can last for more than five years and that the initial installation cost can be recovered through electricity savings over one summer season. It also says the paint is resistant to rain, wind, and sunlight, an important requirement if it is to move beyond controlled demonstrations and into construction sites, logistics fleets, factories, and public infrastructure.

For hot and humid Southeast Asia, where cooling is one of the largest drivers of energy consumption, this is the kind of technology that could attract attention from building owners and municipalities. The International Energy Agency has warned that demand for space cooling is growing rapidly, especially in emerging economies. In this region, rising incomes, urbanisation, and more frequent heatwaves are making cooling both a public health issue and an energy security challenge.

Why water-based paint matters

The key claim behind ZERC’s technology is not only that it cools surfaces, but that it does so in a water-based paint format.

According to Lee, paint-based solutions are increasingly seen as more practical than films or panels because they can be applied with rollers or sprays. Films can be difficult to install on curved surfaces, irregular structures, or large areas. Paint, by contrast, fits into existing construction and maintenance workflows.

Also Read: Tallinn taps StepHow to test AI assistant for public-sector document search

The problem is that many radiative cooling paints have relied on organic solvents such as toluene. These solvents make thick paint easier to apply and can reduce costs, but they evaporate during application and drying, releasing volatile organic compounds, or VOCs. VOCs are harmful air pollutants, and some are linked to serious health risks.

ZERC says it has avoided this by developing a proprietary formulation that combines polymers, water, and ceramic pigments instead of toluene. A polymer acts like a binder, helping pigment particles adhere firmly to the painted surface. The ceramic pigments help deliver the optical properties needed for sunlight reflection and thermal radiation.

“Field painting companies are highly sensitive to price and ease of application as well as eco-friendliness, so until now they have used toluene even if it was toxic,” Lee said. “We instead eliminated VOC emissions at the source through a technology that combines polymers, water, and ceramic pigments instead of toluene.”

This distinction may become commercially important. Across Southeast Asia, governments are tightening environmental and workplace safety standards, but construction and industrial maintenance remain highly cost-sensitive sectors. A cooling paint that requires specialised handling, releases hazardous fumes, or disrupts normal application methods would face a harder route to adoption.

From roofs to helmets

ZERC sees applications wherever paint can be used: building exteriors, roofs, vehicles, ships, and industrial equipment. In the tropics, the clearest use case may be roofs. Warehouses, factories, schools, bus depots, and low-rise residential buildings often absorb large amounts of solar heat through rooftops, raising indoor temperatures and increasing the need for mechanical cooling.

Vehicles are another target. Delivery vans, buses, passenger cars, and electric vehicles all face heat-management challenges. For EVs in particular, reducing cabin cooling loads can help preserve battery range, a concern in hot markets.

One more immediate and human use case is worker protection. ZERC is exploring the use of radiative cooling paint on safety helmets for outdoor workers, including those in construction, logistics, ports, and public works.

“If radiative cooling paint is applied to workers’ safety helmets in summer, it can greatly improve thermal comfort,” Lee said. “Workers must wear safety helmets for protection, but this paint can solve the problem of sweat and discomfort inside the helmet. I believe this is one way advanced science can help vulnerable people.”

That point is especially relevant in Southeast Asia, where outdoor workers are increasingly exposed to heat stress. As heatwaves become more frequent, employers and regulators are under pressure to reduce risk without slowing down essential work. Passive cooling tools, if affordable and durable, could become part of a broader worker-safety toolkit.

A growing climate-tech race

ZERC is entering a market that is already attracting startups and large industrial players. Market research firm Spherical Insights projects the radiative cooling market will grow from US$35.8 billion in 2023 to US$87.7 billion in 2033, at an average annual growth rate of more than 9 per cent.

In the US, SkyCool Systems has demonstrated electricity savings by applying radiative cooling panels to supermarket HVAC systems. RadiaCool has worked on lowering cooling loads in electric vehicles. Japan’s SpaceCool has installed cooling film on buildings, including for the Osaka Expo.

These companies show that the sector is moving beyond lab research. But they also highlight the different approaches within radiative cooling: panels, films, coatings, and paints. ZERC’s bet is that a water-based paint can win in settings where low-friction installation, worker safety, and compatibility with existing surfaces matter more than highly engineered hardware.

The startup is also looking at industrial circularity. Lee recently worked with POSCO to develop a radiative cooling paint that recycles slag, a byproduct generated when iron ore is smelted to make iron. If commercialised, that could give the technology another sustainability angle by turning industrial waste into a cooling material.

The larger question is whether ZERC can move from scientific performance to commercial reliability at scale. Paint has to survive weather, pollution, abrasion, uneven application, and years of exposure. Customers will also compare it against ordinary reflective coatings, insulation, roof retrofits, and traditional cooling systems.

Also Read: Korea’s startup ecosystem is training founders, not just funding them

Still, the timing is favourable. In much of Asia, heat is no longer a seasonal inconvenience. It is becoming an infrastructure problem, a labour issue, and a cost burden. If ZERC can prove that its water-based radiative cooling paint performs in real-world conditions, it may find demand not only in Korea, but across the hotter, fast-urbanising markets of Southeast Asia.

As Lee put it, the goal is to move university deep-tech research “beyond papers and patents” and towards real-world problems in industry, energy savings, and carbon reduction. In a warming region, that ambition will be tested not in the lab, but under the sun.

The post Korean startup ZERC develops paint that cools roofs, vehicles, and helmets appeared first on e27.

Across Japan, corporations are grappling with a familiar tension: promising innovation initiatives that stall before they scale, not for lack of merit, but because rigid organisational structures move slower than the market opportunities in front of them. For a growing number of Japanese enterprises, the response has been to look outward, toward ecosystems agile enough to move at startup speed while stable enough to be trusted with real business problems.

Singapore has become one of the clearest answers to that need. It combines advanced technological capability with a predictable regulatory environment and an English-language business culture, an unusual combination that lets cross-border collaboration happen without the friction that typically slows first engagements between Japanese corporates and international startups.

This is the backdrop to the Boundary Spanning Service, a structured programme developed by Sony Acceleration Platform will connect Japanese corporations with Singapore-based startups capable of addressing specific innovation challenges. For founders in Singapore, understanding this shift, and how to engage with it, is becoming increasingly relevant.

It is also a shift worth watching closely, because it says something about where Singapore’s startup ecosystem sits in the region’s broader innovation map. Japanese corporates are not simply adding Singapore to a list of markets to monitor; they are treating it as a working partner capable of solving problems their own internal teams cannot move on fast enough. That is a different, and arguably more durable, kind of attention than a scouting trip or a pilot programme with no clear next step.

Why Japan is looking to Singapore

Japanese corporations rarely approach business matching service for passive technology scouting. As Sony Acceleration Platform has described in earlier conversations with e27, they typically arrive with clearly defined operational bottlenecks, seeking practical, market-ready solutions across digital transformation, automation, and niche technical capabilities that can be fast-tracked into commercial deployment.

Singapore’s appeal lies in the specifics: a stable and predictable regulatory environment, strong technological capability, and business conducted seamlessly in English. For Japanese corporates trying to manage risk in cross-border ventures, that combination offers a stable, efficient starting point. Singapore’s tech community, meanwhile, brings a level of global compliance and agility that makes it a natural counterpart for enterprises seeking fast, reliable co-creation. Boundary Spanning Service exists to structure that meeting point.

Rather than functioning as a one-off transactional exercise, it is designed around mutual trust and reciprocal value creation, with the Japanese corporate contributing operational resources, industry expertise, and market access, and the Singapore startup contributing agility, speed, and disruptive technology. The goal is to lower the practical cost of survival for good ideas, and to get them into real-world deployment before the window closes.

What this looks like for a Singapore founder

For founders, engagement begins with a streamlined application process supported by e27, designed to be low-friction rather than bureaucratic. From there, Sony Acceleration Platform shares and recommends qualifying startup profiles to the Japanese corporations it works with, meaning founders can expect a structured introduction rather than a cold pitch. What follows is worth entering with clear eyes. Japanese corporate decision-making tends to involve extensive internal consensus-building, a structural characteristic of how these organisations operate, not a signal of disinterest or a personal hurdle. That front-loaded alignment process takes time, patience, and a willingness to meet exacting standards around quality and operational stability.

The payoff for founders who can meet that bar is a relationship that, once trust is established, tends to be exceptionally stable and deeply committed over the long term, backed by the distribution networks and credibility of a major corporate partner. Founders considering Boundary Spanning Service should honestly assess whether they are ready for this type of long-game partnership, rather than a fast transactional deal.

In practice, that means being candid with yourself about a few things: whether your product is genuinely ready for enterprise-grade scrutiny, whether your team has the bandwidth to sustain a longer sales and alignment cycle, and whether you are prepared to treat quality and operational stability as a foundation rather than a formality. Founders who approach Boundary Spanning Service with that mindset tend to be the ones who get the most out of it.

Why Singapore, and why now

Singapore’s position as the starting point for this corridor is not incidental. It reflects a deliberate choice by Sony Acceleration Platform to begin Japan-Singapore collaboration where the ecosystem conditions- technological, regulatory, and cultural- are most conducive to building the kind of trust these partnerships require.

For Singapore founders, it is a rare opportunity to meet Japanese corporate organisations directly, a meaningful step in a process that, by Sony Acceleration Platform’s own account, rewards founders who invest early in the relationship rather than those looking for a quick win.

Founders who engage with Boundary Spanning Service now are positioning themselves at the front of a collaboration corridor that both governments and leading corporations have signalled a long-term commitment to developing. As that corridor matures, early movers are likely to be the best placed to benefit from it.

Register your interest

Singapore founders curious about what this collaboration could mean for their own business have immediate ways to engage: submit an application through the Boundary Spanning Service at https://tally.so/r/815k1k?source=article . The region’s startup ecosystem is evolving quickly, and this corridor between Japan and Singapore offers a concrete, structured way for founders to be part of what comes next.

The region is evolving quickly, and e27 and this collaboration offer the right place at the right moment to be part of what comes next. Register here to join the conversation.

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The post Why Sony Acceleration Platform is turning to Singapore for innovation, and what it means for your startup appeared first on e27.

For much of the past two years, crypto investors have been forced to separate signal from noise. Token prices recovered, regulators tightened their grip, and the industry’s loudest claims about remaking finance gave way to a quieter question: which parts of blockchain are actually useful?

Singapore-based digital asset firm Psalion is betting that the answer lies less in speculative trading and more in the plumbing beneath everyday business. The firm has launched its third and largest venture vehicle, a US$50 million fund targeting early-stage startups using blockchain infrastructure in real-world markets.

Also Read: Malaysia, Singapore investors rebalance portfolios without ditching crypto

The fund, Psalion VC Fund III, is structured as a Singapore-domiciled Variable Capital Company, or VCC, a flexible investment fund structure widely used by asset managers in the city-state. It is managed by Conduit Asset Management, which is licensed and regulated by the Monetary Authority of Singapore (MAS).

The choice of Singapore is not incidental. Over the past few years, the country has tried to draw a firm line between crypto speculation and regulated digital asset innovation. The MAS has tightened rules around retail crypto promotion while continuing to support institutional experiments in tokenisation, stablecoins and digital money through initiatives such as Project Guardian. For fund managers like Psalion, that regulatory posture offers both credibility and constraints.

“Crypto was the thesis. The traditional financial system was the antithesis. What we’re investing in is the synthesis, where web2 businesses run on web3 rails,” said Tim Enneking, Managing Partner of Psalion.

That framing captures where much of the venture market around blockchain has moved. The first wave of crypto investing was largely about native protocols, tokens and decentralised finance platforms. The next wave, if it materialises, may be less visible to end users: stablecoins for payments, tokenised real-world assets, blockchain-based trade finance, middleware for digital ownership, and consumer products where the underlying rails are decentralised but the interface feels familiar.

Backing builders before the market turns

Psalion said the new fund will focus on pre-seed and seed-stage companies across infrastructure, middleware, trade finance, real-world assets, stablecoins and decentralised finance. It will also look at consumer applications where web3 technology changes how people own, trade or interact with assets without requiring them to behave like crypto-native users.

The timing is notable. Psalion’s previous two funds were also launched during weaker market cycles, and the firm appears to see the current environment as a feature rather than a drawback.

“Some of the best opportunities arise in down markets. Valuations are more reasonable, founders are more focused, and the builders who show up are in it for the long term,” Enneking said.

That view is common among venture investors, but it carries particular weight in crypto, where bull markets often inflate valuations before products have found real users. The collapse of several high-profile crypto businesses in 2022 and the subsequent regulatory clean-up changed the funding landscape. Startups now face harder questions around revenue, compliance and utility.

For Southeast Asia, those questions are especially relevant. The region has a large underbanked population, strong cross-border trade flows, high mobile adoption and fragmented financial infrastructure. These conditions have long made it attractive for fintech founders. Blockchain companies now need to prove they can solve similar problems without adding unnecessary complexity.

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

Stablecoins, for example, have gained attention as a tool for faster and cheaper cross-border settlement. Tokenised real-world assets have attracted banks and asset managers seeking more efficient ways to issue, trade and settle financial products. Trade finance remains a persistent pain point for small businesses across the region, where paperwork, trust gaps and slow settlement can limit access to working capital.

The opportunity is clear. The challenge is distribution, regulation and trust.

Beezie becomes an early test case

Alongside the fund launch, Psalion disclosed that it led a US$4 million round in Beezie, a commerce platform that blends digital ownership, discovery and liquidity into consumer transactions.

Beezie says it has processed more than US$170 million in gross merchandise value since launch and generated more than US$85 million in revenue year-to-date. It also claims to have attracted over 30,000 active users since January 2026. The company’s recent community raise on Echo, initially targeting US$250,000, reportedly sold out in 10 minutes and was capped at US$1 million within 24 hours.

The platform operates across collectibles, luxury and entertainment markets — categories where scarcity, authenticity and resale value matter. These are also areas where blockchain has often been pitched as useful, though consumer adoption has been uneven. Many users care about whether an item is authentic, tradable and liquid; fewer care about whether the backend uses blockchain.

That is precisely the point Psalion is making with the investment.

“Beezie is exactly the kind of company our thesis is built around — a real consumer product, real revenue, and blockchain quietly doing the heavy lifting underneath,” Enneking said. “This is what web2 meeting web3 actually looks like in practice.”

Beezie plans to use the capital for inventory acquisition, geographic expansion and growth across collectibles, luxury and entertainment. Founder and CEO Andrea Miele said the company wants to make transactions feel more engaging by combining ownership, anticipation, discovery and liquidity.

The broader question is whether that emotional layer can translate into durable commerce behaviour. Collectibles and luxury resale markets are already competitive, and user trust is hard won. Beezie will need to show that blockchain improves the experience rather than becoming a technical wrapper around familiar marketplace mechanics.

A crowded field for digital ownership

Beezie is entering a market with several established and adjacent rivals. Globally, platforms such as StockX, Whatnot, eBay, Sotheby’s and Christie’s already serve different parts of the collectibles, luxury and resale economy. In Southeast Asia, Singapore-founded Carousell and sneaker marketplace Novelship have built regional consumer bases around resale and authenticated goods. On the crypto-native side, platforms experimenting with tokenised collectibles and digital ownership have struggled to move beyond early adopters.

Psalion, meanwhile, is competing for deals with a global group of crypto and web3 investors, including Animoca Brands, Spartan Group, Hashed, Dragonfly, Pantera Capital and a16z crypto. The difference will not simply be cheque size, but whether the firm can help portfolio companies navigate compliance-heavy markets and reach users outside the crypto bubble.

Singapore’s role as a base for such funds may strengthen if institutional blockchain adoption continues to move from pilot projects to production systems. The city-state has already positioned itself as a hub for digital asset regulation, tokenisation trials and wealth management. But the region’s startup markets remain uneven. Indonesia, Vietnam, the Philippines, Thailand and Malaysia each present different regulatory and consumer realities.

Also Read: Singapore crypto adoption hits new high as 61 per cent now hold digital assets

For founders, that means a product that works in one market may need significant adaptation elsewhere. Payments, identity, gaming, commerce and financial services all carry local rules and behaviours. A regional web3 startup cannot rely only on the promise of decentralisation; it must solve very specific market problems.

Psalion’s new fund lands at a moment when blockchain has become less fashionable but potentially more useful. The speculative cycle has not disappeared, and neither have the risks. But investors are increasingly looking for companies that can hide technical complexity behind products people actually use.

If Psalion’s thesis proves right, the next major blockchain companies in Southeast Asia may not look like crypto companies at all. They may look like commerce platforms, trade tools, payment networks or financial infrastructure providers, with web3 working quietly in the background.

The post Singapore’s Psalion raises US$50M fund for Web3’s next practical phase appeared first on e27.

Across Southeast Asia, AI is reshaping how workers operate, but not in a uniform way. A new analysis reveals a striking cultural divergence: Filipino professionals are turning to AI primarily as a burnout shield, using it to offload repetitive, draining tasks and protect their mental bandwidth. Singaporean workers, by contrast, are deploying AI as a deep work enabler, a tool to carve out uninterrupted focus time and accelerate high-value cognitive output.

The difference is not merely stylistic. It reflects each country’s distinct labour market pressures and workplace cultures. The Philippines, home to one of the world’s largest business process outsourcing industries, faces chronic worker fatigue at scale. AI is emerging as a structural response to that exhaustion. Singapore, with its knowledge-economy positioning and productivity-first ethos, is using the same tools to raise the ceiling on individual performance.

For founders and operators across the region, the implications are significant. A one-size-fits-all AI adoption strategy will underperform. Localising how AI tools are introduced, framed, and incentivised — by country, by sector, by workforce profile — may determine whether AI delivers measurable gains or simply adds another layer of complexity to an already stretched team.

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REGIONAL

Psalion raises US$50M fund for Web3’s next practical phase: Singapore-based Psalion has closed a US$50M fund targeting what it calls Web3’s practical phase, focusing on real-world utility over speculation, one of the larger crypto-native fund closes in SEA this year.

Sunwah Innovations and Brinc launch Vietnam JV for university spinouts: The joint venture will channel university research in Vietnam into commercialised startups, targeting a gap between academic output and venture-ready companies across the country.

Singapore’s Tikva targets solid cancer barrier with US$8M Series A: Tikva is using its Series A raise to advance therapies that address tumour microenvironments, a persistent obstacle in treating solid cancers, positioning Singapore as a node in precision oncology.

Why investors back Vietnamese startups more aggressively than Thai peers: Structural factors, including Vietnam’s younger demographic, higher risk appetite, and stronger technical talent density, help explain why Vietnam consistently attracts more aggressive VC bets than Thailand.

Malaysia and Singapore investors rebalance portfolios without ditching crypto: Institutional and retail investors across both markets are adjusting allocations amid macro uncertainty, trimming risk exposure while retaining crypto positions — suggesting a maturing, not retreating, digital asset stance.

The 27 SEA biotech firms betting on cells, fermentation, and code: A deep-dive list of 27 Southeast Asian biotech companies working across synthetic biology, cultured meat, and computational biology signals the sector’s growing depth beyond Singapore.

Triple-A says own digital assets hit by unauthorised access: Singapore-based crypto payments firm Triple-A confirmed a security breach affecting its own holdings — a significant incident for a firm that processes crypto transactions for major enterprise clients.

SEA’s regulatory patchwork demands a local-first approach: Fragmented licensing regimes across Southeast Asia’s fintech and tech sectors are forcing companies to build compliance infrastructure country by country rather than regionally — raising costs and slowing expansion.

Vietnam’s tech talent market is broken and hiring habits won’t fix it: Most companies are sourcing Vietnamese tech talent through outdated channels that prioritise credentials over capability, exacerbating a structural mismatch between employer needs and available skills.

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INTERVIEWS & FEATURES

What BEYOND Expo 2026 revealed about Asia’s hardware edge: Observations from BEYOND Expo 2026 point to a regional shift; Asian hardware founders are moving faster from prototype to production than Western counterparts, with supply chain proximity as a structural advantage.

How do you finance a first nuclear reactor for a data centre: A detailed breakdown of emerging deal structures for nuclear-powered data centres shows how project finance, offtake agreements, and government backing are converging to make first-of-kind builds viable.

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INTERNATIONAL

Anthropic’s Dario Amodei flags risk from Chinese AI, not open-weight models: Amodei clarified he does not oppose open-weight AI development but warned that Chinese AI advancement poses a more material geopolitical risk — a framing with direct implications for SEA’s AI policy debates.

Satya Nadella warns against over-reliance on a single AI system: Microsoft’s CEO cautioned that companies trusting one AI for everything risk structural fragility, a message directed at enterprise AI buyers accelerating consolidation of their vendor stacks.

Lyft and Baidu begin robotaxi testing in London: The partnership marks Baidu’s first Western robotaxi deployment, testing Apollo Go technology in a heavily regulated market, a move that signals Baidu’s intent to internationalise its autonomous driving stack beyond China.

Waymo reportedly weighing a break with Uber: A reported split between Waymo and Uber would reshape the autonomous vehicle partnership landscape, with implications for how robotaxi services are distributed globally, including in markets where Uber dominates ride-hailing.

Microchip Technology acquires Israeli AI chipmaker Hailo: The acquisition gives Microchip a dedicated edge AI inference chip portfolio, strengthening its position in embedded AI hardware used in automotive, industrial, and smart device markets across Asia.

DeepSeek pauses fundraising amid viral post scrutiny: DeepSeek’s decision to halt funding discussions follows a wave of social media attention that drew regulatory and investor scrutiny, a rare instance of viral exposure creating friction rather than momentum for a high-profile AI lab.

Apple sued over US$1.8M App Store crypto scam: A lawsuit alleges Apple failed to remove a fraudulent crypto app despite user complaints, raising platform liability questions relevant to SEA’s growing base of mobile-first crypto users.

Swiggy names Nandita Sinha to head Instamart: The appointment puts an experienced consumer leader in charge of Swiggy’s quick-commerce arm as it battles Blinkit and Zepto in India’s intensifying 10-minute delivery war.

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CYBERSECURITY

Microsoft launches its first cyber model and agentic security system: The new agentic cybersecurity system uses AI agents to detect and respond to threats autonomously, a significant product move that could reset enterprise security procurement benchmarks across Asia.

Hugging Face CEO calls for transparency after OpenAI hack: Following what he described as an unprecedented breach at OpenAI, Hugging Face’s CEO argues the AI industry must adopt radical transparency on security practices, or risk systemic trust collapse.

Singapore’s agentic AI ambitions hinge on code trustworthiness: Deploying agentic AI systems at scale in Singapore requires a level of software auditability and verification that current frameworks do not yet adequately address, according to a new analysis.

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SEMICONDUCTOR

Quantum sovereignty in Asia: computing, AI, and emerging ventures: A detailed look at Asia’s quantum computing landscape maps how governments and startups across the region are racing to establish independent quantum capabilities as a strategic national asset.

Are brain waves the next unlock for physical AI?: Researchers exploring brain-computer interfaces as an AI input layer argue that neural signals could give physical AI systems a more precise and low-latency human control mechanism than current interfaces allow.

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AI

AI voice is scaling across APAC, but listening hasn’t kept pace: Voice AI deployment across Asia-Pacific is outrunning the comprehension capabilities of underlying models, particularly in multilingual and dialect-heavy markets — creating accuracy gaps that affect trust and adoption.

Indonesia’s AI hiring gap is real, just not 28x: Claims of a 28-fold AI talent shortage in Indonesiaare overstated, but the underlying deficit is genuine — driven by a mismatch between university output and the practical skills employers need to deploy AI systems.

AI is making SEA’s startups faster not richer, yet: AI tools are compressing execution timelinesfor SEA startups, cutting weeks off product cycles and reducing headcount needs, but revenue impact remains limited as monetisation models lag behind adoption.

Enterprise AI adoption in SEA accelerates despite internal friction: Southeast Asian enterprises are pushing ahead with digital transformation despite unresolved questions around data governance, integration costs, and workforce readiness, a paradox driven by competitive pressure rather than strategic clarity.

Asia’s AI race will be won by whoever keeps the lights on: Energy infrastructure, not capital or talent, is emerging as the decisive constraint in Asia’s AI buildout, with power availability and grid reliability determining which markets can scale compute at speed.

How AI and blockchain could make commerce decisions more accountable: Combining AI decision-making with blockchain audit trails could create verifiable, tamper-resistant records of automated commercial choices, an approach gaining traction among compliance-focused fintechs in SEA.

AI repriced SEA’s marketing agencies; it didn’t replace them: AI tools have fundamentally altered agency pricing models across Southeast Asia — compressing margins on execution work while shifting value toward strategy, creativity, and client relationships.

Philippines use AI to avoid burnout; Singapore for deep work: A comparative study of AI adoption behaviours across the two markets reveals that workforce culture, industry structure, and labour market pressures shape how and why employees actually use AI tools at work.

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THOUGHT LEADERSHIP

How the next-generation neobank should be built for the agentic economy: Agentic AI will fundamentally change banking UX, shifting from app-based interaction to autonomous financial agents that act on behalf of users, requiring neobanks to redesign core infrastructure rather than just the interface.

Bitcoin lost US$65,500 support three times before the Fed spoke: BTC’s repeated failure to hold US$65,500 signals weakening buyer conviction at a key technical level — and the pattern emerged before any Federal Reserve guidance, amplifying concern about near-term price direction.

Volatility is here to stay; here is what founders should do: Persistent market volatility is no longer a cyclical event but a structural condition, and founders who treat it as temporary will be outmanoeuvred by those who build resilience into their operating models from day one.

Is ether quietly stealing Bitcoin’s throne as institutional favourite: On-chain data and institutional flow metrics suggest Ethereum is gaining ground over Bitcoin as the preferred vehicle for sophisticated investors, driven by yield potential, programmability, and growing ETF momentum.

SEA’s fintech apps don’t have a literacy problem — they have a fear problem: Low fintech adoption in underserved SEA markets is less about users not understanding the products and more about a deep-seated distrust of digital financial systems rooted in past fraud and institutional failure.

The 3Cs+1 framework for founders navigating geopolitical fragmentation: A practical strategic framework helps founders map their exposure to geopolitical risk across customers, capital, code, and compliance — and decide where to localise, hedge, or exit.

The real workforce challenge: bridging the credential-capability gap: Credential inflation is masking a widening gap between what workers are certified to do and what employers actually need, a structural problem that AI adoption is making more urgent, not less.

How Singapore SMEs should choose a payment provider: A practical checklist for SME payment provider selection covers fee structures, settlement timelines, FX handling, and integration depth, useful for founders navigating Singapore’s crowded but inconsistent payments landscape.

The future of clinical trials: Decentralised clinical trial models using remote monitoring, real-world data, and AI-driven patient matching are accelerating drug development timelines and expanding access beyond traditional trial sites in Asia.

The evolution of trust: from early adoption to institutional maturity: Digital asset markets are moving through a structural trust transition, from speculative retail participation to regulated institutional frameworks, with SEA markets at varying stages of that journey.

The post How the Philippines and Singapore use AI differently at work appeared first on e27.

A few months ago, I was invited to a private university to deliver a keynote on C-Suite skills for 2026 and beyond. The audience was a room full of MBA students. Smart, ambitious, mid-career. People who had paid real money to think seriously about their next decade.

After the talk, one of them raised his hand and asked the question I knew was coming. The question he probably could not ask his own boss. The question that no senior leader at his company wanted to hear out loud.

“Will AI replace senior leaders too?”

The room went quiet. Not because the question was clever. Because it was honest.

Every executive in the world is privately asking themselves the same thing. Almost none of them say it in public. Saying it would look weak. It would unsettle their teams. It would invite the same question right back at them.

But the student had no such constraint. He had paid to learn. He wanted the truth.

Here is what I told him.

I have been studying AI since 2017. Even back then I was telling people that this technology was going to replace a lot of jobs. Including the roles people assumed were untouchable. Doctors. Lawyers. Consultants. Senior managers. Anyone whose work was mainly about applying expertise was going to feel the wave.

But the question most people ask is the wrong one.

AI is a tool. And a tool only performs at its best when someone behind it takes responsibility for the outcome.

So the real question is not “will AI replace you.”

The real question is “are you the one taking responsibility for what AI produces?”

Also Read: The role of thought leadership in scaling beyond your first market

That single shift changes everything. The moment you stop seeing yourself as the person executing a task that AI can do, and start seeing yourself as the person who owns the outcome AI helps produce, you stop being a candidate for replacement. You become the operator of the tool.

This is the part most senior leaders refuse to confront. They built their careers on being the best executor in the room. The most experienced. The most certified. The most credentialed. AI is taking that ground away. And instead of moving up to the layer AI cannot reach, many of them are doubling down on the layer it is colonising.

The student in front of me understood this immediately. He asked the follow up question that most senior leaders never get around to.

“How do I become that person?”

I told him three things.

First, take ownership of outcomes, not tasks. A task is what you do. An outcome is what your work produces in the world. AI can do tasks. AI cannot want an outcome. The person who owns the outcome cannot be automated out of the loop because the outcome is the reason the loop exists.

Second, build judgement in places AI cannot reach. AI is excellent at pattern recognition. It is much weaker at situations where the patterns are new. Reading a customer who has never bought anything like your product before. Navigating a partnership that has never been structured this way. Making a call when the data is incomplete and the stakes are high. These are the moments where human judgement compounds. Spend your career deliberately collecting these moments.

Third, become responsible for results that involve other humans. AI is improving rapidly at producing content. It is not improving at being trusted by a CFO who needs to make a hard decision. Or being chosen by a customer who has options. Or being followed by a team through a difficult quarter. Trust, choice, and followership are the human-only layer. Senior leaders who operate in that layer remain irreplaceable.

This is what I have been doing personally since 2019. I mentor startups. I invest in founders. I help them accelerate beyond their home country. I connect them with local partners in new markets. I help them generate revenue and lift their valuations toward exits.

Can AI do parts of this work? A lot of it, actually. AI can draft introductions, analyse markets, summarise a business plan, generate first-draft strategy.

But who takes responsibility when the call goes wrong?

Who reads the market that does not show up in any dataset?

Who carries the relationships that took years to build?

That part still belongs to a human. And that human is the one who deserves to be in the senior seat.

Also Read: 7 leadership skills every manager needs in a monitored workplace

This is also why I built Future 500 to operate the way it does. Every founder we back gets direct access to people who have actually built businesses from zero. Not because AI cannot do the analysis. It can. But because the founder needs someone willing to take responsibility for the outcome alongside them. That layer of accountability is what AI cannot replicate. It is the layer where senior leadership lives.

When I evaluate a founder for investment, I am looking for exactly this signal. Does this person take responsibility for outcomes, or do they deflect to circumstances? Do they own the numbers, good or bad? Do they propose the next move before being asked?

The founders who answer those questions clearly are the ones I back. The ones who cannot, get a polite pass. AI did not create this filter. It just made the filter sharper, because the candidates who pass it are now even more rare.

If you are a senior leader reading this and feeling shaky about your future, the question to ask yourself is not “will AI replace me?”

The question is “am I the one taking responsibility for what my work produces?”

If you are, AI will multiply you. It will sharpen your judgement, accelerate your output, and free you to focus on the layer of work that only humans can do.

If you are not, you were already replaceable. AI just sped up the timeline.

The MBA student walked out of that hall with a clearer answer than most senior leaders will ever give themselves.

The question is whether you are willing to ask it now, while you still have time to act on the answer.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of e27.

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The post The future of leadership: Owning outcomes in the age of AI appeared first on e27.

Hyperscalers are preparing to spend roughly US$700 billion in 2026 to make artificial intelligence more capable and cheaper to run. That sounds like a straightforward growth story. More models, more compute, more demand, more data centres.

The risk is that the spending is buying the very forces that weaken part of the demand case.

AI build-outs are usually debated through the depreciation question: will the chips become obsolete too fast to earn back their cost? That is a real issue, but it is not the only one. A more important pressure may come from below. Once a model is good enough to complete a defined task, the buyer no longer needs the newest frontier model for that job. And once the cost of running that level of performance keeps falling, more of the work can move onto hardware the buyer already owns.

The problem is not that AI demand disappears. It probably does not. Cheaper intelligence creates more use. The problem is price. The share of work that can be done by a good-enough model on local hardware sets a ceiling on what a data centre can charge for that work.

That ceiling is falling.

The four largest US technology platforms have guided toward extraordinary capital spending. Amazon has pointed to about US$200 billion, Microsoft to about US$190 billion for the calendar year, Alphabet to US$175 billion to US$185 billion, and Meta to US$115 billion to US$135 billion. McKinsey’s widely cited estimate puts worldwide data-centre capital needs near US$6.7 trillion by 2030, with about US$5.2 trillion AI-specific. Morgan Stanley’s estimate is lower, near US$3 trillion through 2029, but still leaves a financing gap it puts around US$1.5 trillion.

These sums create fixed obligations: debt, power contracts, long-dated capacity deals, and depreciation schedules. Those obligations must be serviced regardless of what price inference commands.

The spending buys two things at once. It buys capability, so models can do more. It also buys efficiency, so a fixed level of AI performance becomes cheaper. Both are desirable. Both also undercut scarcity pricing.

Also Read: How AI and blockchain could make commerce decisions more accountable

Capability has a bound for each task. A tax return, a legal draft, a customer-support exchange, or a code review requires a model good enough to finish the job to a competent standard. Once that threshold is crossed, a better model does not make the completed task more complete. The buyer then moves from “best available model” to “cheapest model that clears the bar.”

Efficiency then moves the same work toward commodity pricing. Epoch AI has found the price of reaching a fixed performance milestone falling between ninefold and several-hundredfold a year in some cases. Andreessen Horowitz has tracked inference at constant capability falling at roughly tenfold a year. Gartner expects inference on a trillion-parameter model to cost more than 90 per cent less in 2030 than in 2025, with on-device and edge inference among the drivers.

That matters because the edge is no longer theoretical. Gartner puts AI PCs near 31 per cent of the market in 2025. Counterpoint puts penetration closer to two-fifths. Canalys expects more than 200 million AI PCs shipped annually by 2028, and IDC expects neural processing units to be near-universal in new PCs by then.

Capability is moving with the hardware. A 120-billion-parameter open model now runs on a single desktop appliance at roughly 32 tokens per second. A 70-billion-parameter model runs on a mini-PC costing about US$1,500 at 12 to 15 tokens per second. Apple’s unified-memory Macs and Nvidia and AMD desktop systems put comparable capability on millions of desks. The best open-weight models now trail the leading closed systems by low single-digit points on neutral capability indexes, with several available under permissive licenses.

This does not mean the edge replaces the frontier. It does not. Frontier training remains capital-bound. The largest facilities have minimum efficient scale that owned devices cannot touch. Workloads needing very long context, low latency at high concurrency, proprietary cloud data, always-on orchestration, or the newest reasoning models still belong in centralised infrastructure.

But that is exactly the distinction. The defensible data-centre market is the work that structurally needs the data centre. The fragile slice is ordinary inference that once lived in the cloud only because a capable model could not run anywhere else.

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For that slice, the buyer has a standing choice: rent compute from a data centre, or run the workload on owned hardware. The amortised cost of the owned option becomes the maximum sustainable cloud price before work defects. A chip can be fully utilised and still earn a thinning margin if the price it commands is set by what the same job costs on a machine the customer already bought.

This is why the depreciation debate misses part of the issue. Obsolescence asks whether a chip’s useful life is shorter than the accounting schedule. Edge substitution asks whether the work the chip serves is still scarce enough to command the assumed price. Those are different risks.

The price signals are already mixed, which is what should make the issue interesting rather than dismissible. Hourly rates for prior-generation accelerators fell sharply from around US$8 in early 2024 into a US$1.50 to US$3.50 band by late 2025, as newer chips arrived and new providers entered the market. That looked like commodity pressure. Then rates reversed: one-year rental contracts rose about 40 per cent from an October 2025 low of US$1.70 to US$2.35 by March 2026, with on-demand capacity sold out. The rebound shows that demand is still strong enough to absorb capacity. It does not prove the ceiling has vanished.

McKinsey’s own estimate captures the uncertainty. It expects roughly 60 per cent to 65 per cent of US and European AI workloads to sit on hyperscaler infrastructure by 2030. That still leaves a third or more elsewhere, and the cloud-versus-edge split is a live swing factor.

The strongest objection is simple: total demand may outrun the whole problem. Agentic workflows can use five to thirty times more tokens than a chatbot exchange. Older chips can flow down into inference rather than strand. One Bernstein estimate says a five-year-old accelerator can still earn about US$0.93 an hour against US$0.28 of cash cost, implying a contribution margin above 70 per cent. If AI-generated productivity gains keep arriving, demand expansion may swamp pricing pressure.

That objection is serious. The likely outcome is not collapse. It is segmentation. Frontier work remains centralised and expensive. Commodity work gets cheaper. Some of that commodity work stays in data centres because management, integration, security, and convenience matter. Some moves to owned hardware because the economics become too obvious to ignore.

The watch points are clear. If open-weight models keep closing the gap, the local option strengthens. If memory shortages keep edge hardware expensive, the ceiling falls more slowly. If frontier capability re-widens, centralised infrastructure keeps more pricing power. If commodity accelerator rental rates soften while AI PC penetration rises, the pressure is binding.

The AI build-out may still work. But the risk is not just that racks sit idle. The sharper risk is that the racks are busy carrying work whose price is being set somewhere else.

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