SBOM has become one of those ideas that sounds obvious in a board presentation and messy the moment it reaches a real plant. In theory, it is simple. Ask every supplier what sits inside the software you run. In practice, OT estates are made up of PLCs with opaque firmware, SCADA stacks that have grown over the years, historians with connectors and plug-ins from different eras, and vendor appliances that were bought for uptime rather than transparency. The modern OT now looks much closer to IT than it once did, yet it still carries unique performance, reliability, safety, and change control constraints. That is why SBOM in OT is possible, but it has to be framed as an operational risk tool, not as a purity exercise.

The stronger question for the energy sector is not whether every OT product can produce a perfect SBOM tomorrow morning. The stronger question is whether operators can get enough component visibility to make faster decisions on patching, isolation, procurement, and incident response before they are forced into blind trust. That is also where policy is heading.

It is becoming common for manufacturers of products with digital elements to identify and document components, including by drawing up an SBOM in a commonly used, machine-readable format covering at least the top-level dependencies, and to provide it to market surveillance authorities where needed for compliance checks. At the same time, explicit focus is put on refining data fields, automation support, and operational practices so that SBOMs are scalable and interoperable rather than theoretical.

Why OT makes SBOM harder

The software world often assumes continuous deployment, short release cycles, and an environment where change is routine. OT does not work like that. Change management is paramount in OT, that software changes must be thoroughly tested and rolled out carefully, that outages may need to be scheduled days or weeks in advance, and that many OT environments still rely on older operating systems and firmware that may no longer be supported by the vendor. That changes the value of SBOM. In enterprise IT, it can be a speed tool. In OT, it is first a decision confidence tool.

Also Read: How to navigate the investment opportunity in climate tech sector

This is why many operators still hesitate. They hear SBOM and imagine a flood of component data that creates work without reducing plant risk. That fear is reasonable if the programme is designed badly. A raw component list that is disconnected from asset criticality, patch windows, vendor support, and engineering ownership is not a control. It is an admin. The answer is not to reject SBOM. The answer is to define what useful visibility looks like in an industrial setting.

What SBOM should really mean

For PLCs, the industry needs to be honest. Most operators are not going to get perfect software transparency for every controller any time soon. But that does not mean nothing can be done. A practical PLC SBOM starts with the firmware image, the communications stack, the engineering workstation software used to configure the controller, and any embedded third-party components that materially affect exposure or patching decisions. In OT terms, that is already meaningful progress because it ties software transparency to the assets that can change physical behaviour. The software and firmware inventory, version numbers, vendor details, and SBOM information belong inside an accurate asset inventory and risk management practice.

Historians and SCADA systems are where SBOM adoption should move faster. These platforms are usually closer to standard operating systems, databases, application servers, remote access layers, and commercial software components. In other words, they are part of OT where component transparency is more achievable and more immediately useful. If operators are serious, this is where they should begin, because the effort is lower and the payoff in vulnerability management is more visible. SBOM data improves the speed and efficiency of vulnerability response, helps identify end-of-support components earlier, and becomes far more powerful when integrated into vulnerability management and asset management tools already in use.

Vendor appliances are the real test. These are the black boxes that every site depends on, and very few teams can fully inspect. They are also where operator frustration is highest. It is suggested that buyers seek manufacturers who include hardware and software bills of materials with product delivery and who commit to timely remediation. That matters because procurement is often the only moment when the operator has real leverage. If an appliance supplier still treats component transparency as optional, that is no longer a technical footnote. It is a signal about how seriously they take lifecycle accountability.

Also Read: What big tech won’t show you about the future of AI

The mistake is treating SBOM as a file rather than a workflow

The market still talks about SBOM as though the job ends once a JSON or XML file has been generated. That is far too narrow, especially in OT. SBOM includes workflows for acquisition, management, and use, while its sharing work distinguishes between authors, consumers, and distributors across the lifecycle. SBOM is only data until it is consumed and converted into insight that can drive action. That is the right way to think about OT. A plant does not need more documents. It needs better decisions.

This is also why SBOM without VEX will disappoint many operators. A component list tells you what is inside. It does not tell you whether a newly disclosed vulnerability is actually exploitable in your deployed configuration, or whether the vendor has already assessed the exposure differently. VEX can be used alongside SBOM to improve prioritisation and effectiveness. In OT, that matters enormously because patching is costly and often disruptive. The real value is not finding every theoretical issue. It is knowing which issues deserve scarce outage time.

Can we actually do SBOM in OT

Yes, but it needs a sequence that respects operational reality.

First, use procurement to shape the future estate. Regulations are moving in that direction, and buyers should use that momentum. New PLC platforms, historians, SCADA systems, remote access products, and industrial appliances should be bought with explicit expectations around SBOM, update support, vulnerability disclosure, and version control. This is the easiest part of the OT estate to improve because it relies more on commercial discipline than plant retrofit heroics.

Also Read: How to unlock possibilities through data privacy enhancing technologies

Second, treat legacy products differently from new builds. Binary decomposition of software installation packages is recommended to generate SBOMs where no vendor-supplied SBOM is available, including for legacy software, where technically and legally feasible. When software already exists, binary analysis tools can use increasingly accurate heuristics and datasets to infer underlying components. That does not solve every appliance or controller, but it creates a realistic middle path for brownfield environments.

Third, connect SBOM to asset inventory and criticality from the start. The accurate inventory of vendor, model, firmware, operating system, and software versions is central to identifying and remediating vulnerabilities. SBOM disclosures should be aligned with asset inventories for risk exposure and criticality calculations. That is the step that turns software transparency into plant relevance. Without it, SBOM remains a software artefact. With it, it becomes part of operational risk management.

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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 post SBOM for OT: Can we actually do it? appeared first on e27.

Consumers across Southeast Asia still experience e-commerce as a bargain-hunting paradise: flash sales, free shipping, vouchers, cashback, livestream discounts, and endless price competition. But behind that cheerful promotional theatre lies a harsher truth. The economics are getting tougher for merchants, and the ecosystem is increasingly built on a tension that may not be sustainable in the long term.

According to Ecommerce in Southeast Asia 2026 by MomentumWorks, platform take rates continue to rise across the region, with Shopee reaching a GAAP take rate of 13.5 per cent in the fourth quarter of 2025.

Yet sellers interviewed by MomentumWorks said their real all-in costs (including commissions, advertising, logistics, payment charges, affiliate fees, and platform services) often exceed 30 per cent of GMV.

Also Read: Shopee, TikTok, Lazada: Three ways to win and no easy way in

That gap between official take rate and lived merchant experience tells the real story of Southeast Asian e-commerce in 2026.

The published number is not the merchant’s number

A 13.5 per cent take rate sounds manageable, especially in a region where e-commerce platforms are still in growth mode. But sellers do not pay only the published commission. They pay for traffic. They pay for conversion. They pay to join campaigns. They subsidise consumers. They pay logistics and fulfilment fees. They pay affiliates. They often absorb operational leakage and returns as well.

MomentumWorks cites seller feedback suggesting that platform fees alone can approach 25 per cent even before a merchant includes its own shipping costs and affiliate spend. In some cases, the total drain on revenue approaches half the sale value before product cost is even counted.

This explains one of the report’s most striking observations: sellers are squeezed, but they cannot leave.

Platform dependence is the real moat

Why do merchants stay when margins are deteriorating? Because in Southeast Asia, platform demand is still overwhelmingly dominant.
MomentumWorks estimates that non-platform ecommerce GMV in the region totalled US$27.8 billion in 2025, against platform GMV of US$157.6 billion. That means roughly 85 per cent of e-commerce in Southeast Asia still flows through the major platforms. Social commerce, brand-owned websites, multi-brand retail sites, and chat-based transactions are growing, but they remain secondary.

For merchants, this creates a painful asymmetry. They dislike rising costs, yet they remain dependent on the platforms’ traffic and conversion machinery. Exiting a platform is not just a channel decision. It can feel like voluntary invisibility.

That dependence gives leading platforms enormous room to keep shifting economics in their favour, at least until behaviour changes at scale.

The paradox of cheap e-commerce

Perhaps the most provocative argument in the report is that Southeast Asia’s e-commerce has not yet reached its “true price floor”. That sounds counterintuitive in a market obsessed with discounts. But the report’s point is sharp: today’s affordability is often artificial. It is driven by subsidies funded by platforms, brands, and sellers—not by structurally lower supply-chain costs.

In plain English, prices look low to shoppers because someone else is carrying the burden.

If merchant economics are deteriorating while platforms still need vouchers and incentives to drive price competitiveness, then Southeast Asia has not yet produced a fully efficient discount retail model. It has only produced a heavily subsidised one.

That matters because the region still contains a large, highly price-sensitive consumer base that remains underpenetrated in e-commerce. If a platform can eventually redesign the supply chain rather than merely subsidise the transaction, the market could open much further.

The Temu question hangs over the region

This is where the report raises a question that should make every incumbent uncomfortable: Can a Pinduoduo or Temu-like model really emerge in Southeast Asia?

Also Read: Why quick commerce is really about frequency, not speed

The answer is not obvious. The region is more fragmented than China, with different languages, customs regimes, payment behaviours, logistics costs, and regulatory environments. But the demand side is compelling. Large parts of Southeast Asia remain highly price-sensitive. If a structural cost advantage can be unlocked through sourcing, inventory, logistics, and product design, the addressable market may be larger than current platform models suggest.

Cross-border flows offer a clue. In the Philippines, cross-border e-commerce GMV surpassed US$0.1 billion, with SHEIN and Temu driving significant parcel volume and freight tonnage. Thailand has tightened import oversight, and Vietnam continues to increase scrutiny. But demand has not disappeared. It is adapting.

The danger for incumbents is that they may be fighting over subsidised middle-income consumers while a deeper value segment remains only partially served.

Sellers are becoming multi-platform by necessity, not ambition

MomentumWorks notes that multi-platform operations are no longer optional for sellers. That is a critical shift. Merchants are not diversifying because it is an elegant strategy. They are doing it because platform dependence is risky, algorithmic visibility is unstable, and any one channel can suddenly become too costly.

This could reshape the e-commerce service landscape. Merchant software, cross-platform inventory tools, ad optimisation platforms, social commerce enablement, and direct customer retention solutions all become more relevant when sellers need to spread risk across channels.

The rise of affiliate-driven commerce compounds this. As platforms push more content-led discovery, brands and sellers have to spend more not just on logistics and platform fees, but on attention itself. Discovery is becoming both more expensive and more fragmented.

Regulators are entering the picture, but not to save sellers

Several Southeast Asian governments are tightening e-commerce rules, especially around imports, competition, and platform accountability. Thailand has abolished its de minimis exemption on imported goods. Vietnam has passed a new e-commerce law that places more responsibility on platforms to regulate sellers. Indonesia remains politically sensitive to the dominance of foreign-linked platforms and Chinese product inflows.

Also Read: SEA’s e-commerce giants hit profitability: What it means for region’s digital future

But regulation may not directly improve merchant margins. In fact, it could further entrench the biggest players by increasing compliance costs and favouring platforms with the scale to manage them.

That means sellers should not expect public policy to restore balance quickly. The structural tension will likely persist.

The next wave of opportunity may sit outside the transaction

For founders and investors, the lesson is clear. The biggest opportunities may no longer be in competing for the transaction itself, but in reducing friction for sellers trapped inside high-cost ecosystems. That includes better analytics, AI-enabled content production, customer retention, financing, embedded software, and tools that help merchants understand true profitability by channel.

Southeast Asia e-commerce still looks like a consumer success story. But underneath, it is becoming a merchant stress test. And when the people funding the discount machine start to crack, the whole system can change very quickly.

Cheap e-commerce, in this region, is getting expensive.

The post Why sellers can’t escape the e-commerce platforms that squeeze them appeared first on e27.

Global financial markets present a fascinating picture of resilience and shifting capital flows as we navigate April 2026. Investors find themselves at a crossroads of geopolitical relief and strong domestic economic indicators. The major United States indices reflect optimism among market participants today. The S&P 500 gained 18.33 points, a 0.26 per cent increase, closing at a record 7,041.28. The Nasdaq Composite rose 86.69 points, or 0.36 per cent, reaching 24,102.70 and hitting a historic all-time high.

This movement marks the 12th consecutive positive session for the Nasdaq. Analysts note this represents the longest winning streak for the technology index since 2009. The Dow Jones Industrial Average added 115.00 points, equivalent to a 0.24 per cent rise, finishing the trading session at 48,578.72.

A significant driver behind this market rally involves impactful developments on the geopolitical front. President Trump announced a 10-day ceasefire between Israel and Lebanon. This agreement became effective at 5 pm Eastern Time on April 16. This diplomatic breakthrough provided relief to investors who spent weeks watching regional instability threaten global trade routes.

Market sentiment improved drastically after new reports indicated that discussions between the United States and Iran were ramping up. These diplomatic conversations bring strong prospects of extending a separate two-week ceasefire. This potential de-escalation allows market participants to actively price a lower risk premium for equities across the board.

The energy sector tells a conflicting story right now. Brent crude climbed 4.7 per cent to US$99.39 a barrel as ongoing disruptions in the Strait of Hormuz push oil prices higher.

The domestic economy shrugs off these severe commodity shocks. Recent economic data signals robust resilience across multiple vital sectors. The Philadelphia Fed business index shattered expectations. It surged to a remarkable 26.7, easily beating the consensus expectation of 10.0. Initial jobless claims fell to a low of 207,000. These figures paint a definitive picture of a hot labour market. This economic heat provides the foundational support for the record stock indices we observe closing today.

The corporate earnings landscape offers a nuanced view of this economic resilience. Technology companies continue leading the charge. TSMC reported a 58 per cent jump in quarterly profit. The semiconductor giant confidently raised its 2026 revenue growth forecast to above 30 per cent. This upward revision validates the capital investments flowing rapidly into artificial intelligence infrastructure.

Not all corporate giants share in this euphoric market rally. Netflix shares plummeted nearly 10 per cent in after-hours trading. Management issued a soft Q2 revenue outlook, disappointing Wall Street. Netflix also announced that co-founder Reed Hastings will step down from the board in June. The financial and consumer staples sectors highlight a complex macroeconomic environment that requires careful navigation.

Also Read: The double-edged sword of AI in crypto trading

Charles Schwab shares fell seven per cent after the firm narrowly missed revenue expectations. The financial firm simultaneously announced plans to launch cryptocurrency trading for its client base. Consumer staples giants face their own unique challenges. PepsiCo successfully beat analyst expectations with an adjusted earnings per share of US$1.61. Management warned investors about a volatile macroeconomic environment lying ahead despite the positive earnings beat.

European markets reacted with enthusiasm to the diplomatic news earlier in the week. Indices like the DAX and the CAC 40 surged 5.1 per cent and 5.0 per cent, respectively, as traders anticipated lower energy costs. Asian markets opened notably lower on April 17. Regional traders weighed warnings that the United States-Iran conflict could persist for months, despite temporary ceasefire agreements dominating Western headlines.

The global financial ecosystem increasingly bridges the gap between traditional equities and digital assets. The cryptocurrency market currently sits at US$2.55T, representing a 1.02 per cent gain over the past 24 hours. This upward trajectory shows a strong 75 per cent correlation with the S&P 500. The global liquidity forces lifting traditional stocks actively drive this shared macroeconomic move. An institutional endorsement serves as the primary catalyst for this crypto market strength.

Citigroup published a landmark study on April 16 endorsing Bitcoin and gold as essential portfolio diversifies. The study definitively shows that adding both Bitcoin and gold to a traditional bond-and-equity portfolio increased returns without increasing risk over the past 10 years. This vital data provides a powerful narrative for institutional capital allocators managing trillions of dollars. Industry experts expect this research report to trigger fresh capital inflows into core digital assets.

Market participants must watch for sustained net inflows into United States spot Bitcoin exchange-traded funds. These investment vehicles recently saw their total assets under management rise to US$97.24B. This capital absorption proves that traditional finance treats digital assets as a permanent fixture.

The underlying technical indicators for the cryptocurrency market scream bullish momentum. The 7-day relative strength index currently sits at 74.76. This metric confirms the aggressive buying pressure dominating the order books. Speculative capital actively chases outsized returns in smaller capitalisation tokens.

Investors rotate capital into high-beta sectors in search of massive gains. Top gainers like SIREN skyrocketed by 125.84 per cent over a short period. ORDI posted an astonishing 133.51 per cent gain during the same timeframe. Investors rotate their profits from Bitcoin into riskier assets. They search for asymmetric upside in digital narratives such as the Binance Ecosystem.

Also Read: The alarming reason crypto now moves like gold but falls like stocks

The broader digital asset market has not yet entered a full-on altcoin frenzy despite these explosive moves. The Altcoin Season Index currently sits at a neutral 37. A sustained rise above 50 would confirm a comprehensive alternative coin rally. The immediate path for the cryptocurrency market hinges on ongoing institutional behaviour and upcoming regulatory catalysts.

Technical analysts identify key overhead resistance at the 127.2 per cent Fibonacci extension level. This technical level aligns with the US$2.63T total market capitalisation mark. Breaking above this ceiling requires sustained buying pressure from major financial institutions.

The overall market must securely hold the 23.6 per cent Fibonacci support level residing at US$2.49T. Losing this support level could trigger a cascade of profit-taking across all digital assets. Fundamental catalysts will determine which direction the market breaks next. The Securities and Exchange Commission scheduled a vital roundtable discussion covering the CLARITY Act for April 16. This regulatory event could provide the directional cue the market needs right now.

My perspective as an active investor suggests that the current market dynamics represent a fundamental shift. We witness traditional finance capitulating to the mathematical reality of digital assets. The Citigroup study and fund inflows clearly evidence this institutional shift.

Traditional equities simultaneously exhibit remarkable resilience to geopolitical shocks and soaring crude oil prices. The strong correlation between cryptocurrency and major stock indices proves modern investors treat all global assets as interconnected vessels of systemic liquidity.

The current bullish case rests heavily on continued economic resilience among American consumers. Market participants must remain vigilant. Prudent investors must carefully balance the excitement of record index highs against the lurking risks of sudden geopolitical deterioration or unexpected regulatory headwinds.

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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 post Crypto at US$2.55T: Bull market confirmation or trap for retail investors? appeared first on e27.

Southeast Asia’s e-commerce story has long been framed as a consumer triumph: cheap prices, endless deals, and frictionless convenience. But this model is beginning to show strain where it matters most: at the merchant level.

What makes the current moment interesting is not just rising platform costs, but the growing disconnect between headline metrics and lived reality. A 13.5 per cent take rate sounds manageable until sellers account for advertising, logistics, and incentives that can push total costs beyond 30 per cent. At that point, scale becomes less about growth and more about survival.

Yet merchants remain locked in. Platforms still control demand, and leaving them often means losing visibility altogether. That dependence is the real moat, and the real risk.

The bigger question is what breaks first: seller margins or the subsidy-driven pricing model. If the ecosystem cannot transition from incentives to structural efficiency, the current equilibrium may not hold.

For founders and investors, the opportunity is shifting. The next wave may not be about owning transactions, but about helping merchants survive them.

Regional

SEA merchants trapped in a high-cost e-commerce squeeze: While Shopee’s GAAP take rate hit 13.5%, sellers report all-in costs exceeding 30% of GMV; yet platform dependence, with 85% of regional commerce flowing through major players, makes exit feel like voluntary invisibility.

Shopee, TikTok Shop, and Lazada now control SEA e-commerce: Platform GMV in Southeast Asia reached US$157.6B in 2025, up 22.8%, but Shopee, TikTok Shop, and Lazada now command 98.8%of regional platform commerce, leaving no room for another large horizontal marketplace.

Quick commerce is a fight for frequency, not just speed: MomentumWorks argues that platforms like Shopee, Grab, and Lazada are using instant delivery not to win a logistics race, but to build habitual urban demand; the platform that wins habit wins far more than any single basket.

Vietnam’s Farmnet secures US$11.75M institutional loan: TechCoop’s trading arm raised a senior secured loan from impact investor Symbiotics, the first offshore institutional borrowing by a Vietnam-incorporated TechCoop entity, to scale agricultural commodity trading across 641 co-operatives nationwide.

Indonesia’s Baskit raises US$9.9M to take supply chain model regional: The profitable AI-enabled distribution startup, backed by Cento Ventures and HSBC Innovation Banking, is expanding into the Philippines after three years mastering Indonesia’s fragmented offline trade channels.

Choco Up launches US$30M private credit facility for APAC SMEs: Partnering with tech-driven credit specialist CHUAN, Singapore’s Choco Up is targeting Asia’s US$2.5T SME funding gap with AI-powered underwriting that promises approvals in hours, not months.

Animoca Brands secures Hong Kong stablecoin licence: Through its joint venture Anchorpoint, with Standard Chartered and HKT, Animoca is one of only two entities out of 36 applicants to receive an HKMA stablecoin issuer licence, gaining a regulated settlement rail for digital assets.

eFishery founder faces 10-year jail term in Indonesia: Prosecutors asked the Bandung District Court to sentence Gibran Huzaifah after he admitted to inflating the aquaculture startup’s revenue, with alleged losses exceeding 69B rupiah and investor confidence severely damaged.

TikTok disables 780,000 underage accounts in Indonesia: TikTok became the first platform to report compliance action under Government Regulation No. 17/2025, disabling accounts held by users under 16, while Roblox failed to fully comply due to lingering stranger-chat features.

Indonesia’s e-commerce child safety rules spark industry confusion: Ministerial Regulation 9 of 2026 requires platform self-assessments to set child access limits, but industry players are questioning whether high-risk classifications were assigned to major marketplaces before those assessments were even completed.

Nadiem questions Chromebook corruption loss calculation: A LinkedIn post by Gojek co-founder Nadiem Makarim argued that trial testimony, including from resellers and procurement officials, challenges the 1.5T rupiah state-loss figure cited by prosecutors, noting two independent audits found no markup.

Singapore businesses hit an AI automation wall: A HubSpot survey of 700+ local business leaders found that while nearly two-thirds use AI daily, only 18% have deployed fully autonomous agents, with data quality and legacy integration gaps becoming more acute, not less, as organisations scale up.

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Interviews & Features

From chatbots to creators: Indonesia’s AI startups to watch: A new wave of Indonesian startups is applying AI across finance, healthcare, content, and commerce, highlighting how local innovation is shaping practical, scalable solutions in Southeast Asia’s evolving digital economy.

Share2Inspire founder: your CV isn’t failing, it’s being misread: Samuel Rolo, a veteran of Deloitte and AstraZeneca, built a career intelligence platform that scores CVs against applicant tracking systems — arguing most rejections stem from formatting and presentation failures rather than lack of capability.

A founder built an AI agent for himself, then turned it into a micro-SaaS: What started as a personal productivity tool called Seraphina, handling content, replies, and community management, grew to 2,000 users and became a layered business model spanning SaaS, education, and consulting.

Southeast Asia’s GameFi markets each play different roles in Web3: A Vietnamese expat living in Manila argues that the Philippines is a consumer-amplifier, Indonesia a scale-user market, and Vietnam a builder hub, with the 2026 gaming market projected at US$14.86B and maturing toward fun-first, stablecoin-integrated models.

Singapore’s AI adoption gap: from tools to real-world impact: Experts from AI Singapore, JJ Innovation, and Knovel Engineering say adoption lags not from reluctance but from poor data readiness, cultural resistance, and a critical need for “plus-skilling” — upskilling existing roles rather than wholesale retraining.

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International

OpenAI to spend over US$20B on Cerebras chips over three years: The deal, which could give OpenAI warrants for up to a 10% stake if spending hits US$30B, reflects surging demand for AI inference computing and a US$1B commitment toward funding new data centres.

Some OpenAI investors question its US$852B valuation: After two product roadmap shifts in six months and a recent US$122B raise, backers worry the enterprise and coding pivot could weaken ChatGPT’s position against Anthropic and a resurgent Google ahead of a potential IPO.

Perplexity’s revenue jumps 5x to US$500M: CEO Aravind Srinivas announced the revenue leap, from US$100M, alongside 34% headcount growth, with the AI search startup targeting a further 2x revenue increase in 2026 using the same lean team and its Computer product.

SoftBank raises US$3.6B in high-yield bonds amid AI debt surge: The sale, comprising US$1.5B in dollar notes and €1.8B in euro bonds, came as its AI investment push drove borrowing costs higher, with its 10-year dollar coupon at a record 8.5% and shares down 35% since November.

Snap cuts 1,000 jobs as AI takes over code generation: With AI now producing over 65% of new code, Snap is laying off 16% of its workforce and closing 300 open roles, expecting annualised savings of more than US$500M by the second half of the year.

Netflix co-founder Reed Hastings to exit in June: Following a failed Warner Bros Discovery merger and a stock drop of about 9%, Hastings will not stand for re-election as Netflix posts Q1 revenue of US$12.25B, up 16%, while forecasting its slowest growth in a year.

Saudi PIF raises Lucid investment with US$550M in convertible stock: The funding accompanies Uber’s additional US$200M commitment and a purchase commitment of at least 35,000 Lucid vehicles, as the EV maker expands its robotaxi fleet ambitions.

Nas Daily creator raises US$27M for AI business builder: Nuseir Yassin’s Nas.com secured the Series A round led by Khosla Ventures, with 500 Global, V Ventures, and Factorial Capital also participating, though valuation and use of funds were not disclosed.

Naver plans IPO for Naver Financial after Dunamu share swap: The deal would give Naver Financial full ownership of Upbit operator Dunamu, targeting a listing within five years, though Korea’s proposed Digital Asset Basic Act and an ongoing antitrust review could affect structure and timing.

Robotaxi market projected to reach US$168B by 2035: Counterpoint Research links the forecast to AI advances, larger fleets, and wider commercial rollouts, with the US and China accounting for most deployments, led by Waymo, Tesla, Baidu’s Apollo Go, WeRide, and Pony.ai.

India’s AI firms pursue acquisitions to build full-stack capabilities: As enterprise clients consolidate vendors and shift from trials to larger deployments, Tracxn recorded five deals in four months, including C5i’s US$45M-US$50M acquisition of UK-based Datavid.

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Cybersecurity

DeFi faces twin blows from falling yields and a US$285M hack: Lending rates on Aave have dropped below the US Federal Reserve’s benchmark, while a North Korean-linked group’s theft from Drift has shaken confidence in the US$97B sector as firms pivot toward tokenised traditional assets.

AML compliance is becoming PropTech’s biggest opportunity: With Australia’s Tranche 2 reforms bringing 80,000 real estate professionals under AML obligations from July 2026, and Singapore, Hong Kong, and Japan tightening rules, founders who build identity verification and beneficial ownership tools are entering a mandated, rapidly growing market.

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Semiconductor

TSMC expands 3nm production across Taiwan, Arizona, and Japan: The chipmaker is building new 3nm lines in Taiwan for H1 2027 mass production, with its second Arizona fab set for H2 2027 and a second Japan plant using the 3nm process targeting 2028 — all driven by AI, automotive, and IoT demand.

Nvidia CEO warns US AI export limits are backfiring: Jensen Huang argues that restricting advanced hardware forces rivals to build independent systems, framing the real technology race as a contest over energy grids and software ecosystems rather than chip speed alone.

China’s semiconductor and robotics sectors lead AI-driven hiring: Data from 51job and Zhaopin shows electronics and semiconductors drew 1.5x more applications than other sectors, robotics recruitment rose 36.6% year-on-year, and demand for AI engineers is running three times supply, pushing salaries to US$95,000 for generative AI roles.

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AI

The next AI race is being fought in the physical world: As AI expands into connected devices, wearables, and industrial systems, trust — not model quality — becomes the decisive factor for enterprise adoption, with reliability, latency, privacy, and resilience under imperfect conditions determining which companies scale.

Why founders cannot afford to outsource judgment to AI: Drawing on Gojek’s and Grab’s founding stories, this essay argues that Southeast Asia’s regulatory fragmentation and cultural complexitymean contextual judgment, which AI cannot replicate, remains a founder’s deepest moat and most durable competitive advantage.

The agentic economy needs a new management discipline: As AI agents take over entry-level tasks and hybrid workforces emerge, the author coins “H-AgR”, Human and Agent Resources, arguing that Singapore’s January 2026 AI Governance Framework sets a regulatory floor, but enterprises must build governance structures well above it.

AI adoption in APAC is a customer acquisition problem, not just an ethics one: Western-trained AI marketing tools systematically deprioritise underserved segments, which are often less saturated and more loyal once reached, making bias correction a growth strategy, not a compliance exercise, for APAC startups.

Inclusive AI isn’t optional; it’s Asia’s competitive edge: With Asia holding 60% of the world’s population across linguistically diverse and economically varied communities, AI built without inclusion baked in will not just replicate bias — it will scale it — making DEI-AI literacy a leadership imperative, not an HR function.

NTU researchers build AI-powered biochip for 20-minute disease detection: The Singapore team’s platform combines nanophotonic structures with AI image analysis to simultaneously detect three disease-linked microRNAs, achieving over 99% accuracy in lab tests without requiring PCR amplification.

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Thought Leadership

Why Southeast Asian startup founders should flow, not force: Drawing on psychology, Daoism, and physics, this column argues that the most durable startups align with structural macro trends rather than force outcomes, and that founder mindset coherence is not soft advice, but operational infrastructure.

Narrative clarity is a strategic advantage in SEA’s tough market: As investors tighten scrutiny and customers compare across borders, the companies that scale in Southeast Asia will be those that articulate a clear, consistent story, not just those with the strongest technology.

The advice trap: true stories missing their conditions: Most business advice shared on conference stages is accurate, but stripped of the market timing, team dynamics, and sequencing that made it work, meaning founders who follow maps drawn for different terrain often fail not from bad judgment, but from misapplied wisdom.

Digital growth in Asia: how startups can avoid costly pitfalls: From overlooking mobile-first design to ignoring local payment methods, neglecting data analytics, and treating PR as an afterthought, nine common digital marketing mistakes are quietly killing startups across Asia’s fast-growing but fragmented digital economies.

AI is redefining software development and CEOs must lead: Generative AI tools are accelerating development cycles and creating new roles like prompt engineers and AI workflow architects, but organisations clinging to outdated delivery models risk being outpaced by leaner competitors who have aligned leadership, talent, and process around AI.

The missing rung: how automation is quietly breaking the career pipeline: AI has not just replaced repetitive jobs; it has eliminated the entry-level roles that once served as informal training grounds, creating a generation of workers entering management without the foundational decision-making experience grunt work once provided.

Asia’s logistics startups are turning to AI to solve the last-mile puzzle: With 253M online shoppers projected by 2030 and a 15% failed delivery rate in COD markets, AI-powered route planning, demand forecasting, and dispatch automation are cutting fuel costs by 20% and improving delivery times by 30% across the region.

In the age of AI, people matter more than ever: Vietnam, Singapore, and Thailand are all investing heavily in AI literacy programmes, but the real edge for organisations lies in creating psychological safety, rewarding results over hours, and actively funding employee upskilling — not just deploying better tools.

Why founders should stop hustling and start automating: Manual workflows are a growth ceiling, not a badge of honour, and using tools already at hand like Excel, Google Sheets, and Airtable to build systems that run without the founder is what separates sustainable scaling from perpetual firefighting.

APAC’s esports broadcast innovation is rewriting the global playbook: Driven by mobile-first audiences in Indonesia and the Philippines, data-hungry viewers in Korea, and creator-led communities in India, Southeast Asia’s demand for multi-angle streams, real-time analytics overlays, and localised production is redefining what fans expect from live competition globally.

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Over the past two years, a flood of startups and incumbents have raced to build “AI copilots” for finance. Almost every demo shows a chatbot answering analyst questions or summarising a report. Yet despite billions in investment, adoption across financial institutions remains slow, and productivity gains are modest.

The reason is not a lack of ambition or data. It’s that most companies, founders, and technologists fundamentally misunderstand what it takes to turn AI into business value, particularly in a domain that prizes trust, precision, and accountability above all else.

The missing equation: Value and feasibility

Successful technology adoption depends on finding where business value meets real-world feasibility. Feasibility does not stop at algorithms; it lives in people, processes, and governance.

In banking and asset management, that balance is especially delicate. According to the Evident AI Index 2025, banks with the highest AI maturity, such as JPMorgan Chase, Capital One, and RBC, share one key trait. They invest as much in organisational enablement as they do in model development. These leaders report more use cases because employees trust and use their systems.

Contrast that with the many failed pilots elsewhere, where a 2025 MIT study found that over 95 per cent of generative AI pilots fail to scale because teams “avoid friction.” They chase flashy prototypes that collapse in production. Much of this friction comes from the lack of user trust and limited control over outputs.

Why finance resists the hype

Finance’s slower adoption of AI stems not from conservatism but from accountability. Every output, whether a risk score or a research summary, must be explainable, auditable, and defensible. That accountability clashes with the automation-first mindset many startups adopt. Replacing an analyst or risk officer with an opaque model erodes trust and invites regulatory risk.

As Evident Insights notes, only a few major banks, such as BNP Paribas, DBS, and JPMorgan, report both realised and projected ROI from AI projects. They succeed because they have governance and transparency frameworks that others lack. Oversight is not a bottleneck but the foundation of adoption, where the goal is not to replace human decision-making but to reinforce it through systems that enhance judgment and accountability.

Also Read: The psychology of AI adoption: How familiarity bias is quietly slowing finance down

Automation is easy, augmentation is hard

The default format of GenAI applications, the chatbot, reflects this misunderstanding. It promises frictionless automation but often creates new friction because users do not trust the answers, cannot audit the reasoning, and find the interface detached from their actual workflow.

Real progress lies in workflow-aware systems that amplify human expertise rather than replicate it — JPMorgan’s internal LLM Suite illustrates this well. It did not begin as a single grand platform but as a collection of focused, high-value tools for developers, researchers, and compliance officers. Each tool demonstrated its worth before being integrated into a secure workbench that now serves more than 200,000 employees and saves analysts and developers several hours each week.

The lesson is simple: the future belongs to systems that scale human insight, not those that try to substitute it.

The false promise of platforms

When startups pitch “AI platforms” for finance, they often repeat the same mistake that weakened earlier enterprise software. Platforms may look scalable and visionary, but they often turn into complex, cumbersome systems that users tolerate rather than appreciate.

History makes this clear. In the 2010s, tools such as Salesforce and Workday succeeded by solving one pressing problem deeply before expanding outward. Yet as they evolved into sprawling platforms, usability declined. Layers of plugins and integrations turned once-simple workflows into endless clicking and reconciliation, making them less effective the more they tried to do.

The same fatigue is now emerging in financial AI. Many products start and remain generic, from document summarisers to universal copilots and so-called AI operating systems that claim to serve every department but serve none well. The next generation of leaders will move in the opposite direction, building deep, vertical, and trust-focused systems that create real value in areas such as investment research, credit adjudication, and financial crime detection.

Why startups keep missing the mark

Many so-called finance AI startups are led by former bankers, but most come from back-office or auxiliary roles rather than the front lines of research, trading, or client-facing decision-making. That gap in operational empathy shows, as they build tools that over-automate processes, undermine trust, and overlook the reasoning that drives real decision conviction.

Each time an AI system produces an unexplainable result, it erodes credibility. In finance, credibility is currency; once it is lost, adoption disappears. Human-in-the-loop design is not philosophical but commercial. Systems that allow users to trace reasoning, correct mistakes, and feed improvements back into models create feedback loops that build trust and long-term data advantages grounded in real use, not scraped content.

Also Read: The psychology of AI adoption: How familiarity bias is quietly slowing finance down

Augmenting judgement: The middle ground

Between full automation and manual work lies a wide, unexplored space where AI can enhance human judgement and creativity. In investment research, this means helping analysts link cause and effect, such as how a policy change in Washington might influence earnings in Shenzhen, rather than merely summarising data. In portfolio construction, it means simulating alternative narratives, while in risk management, it means contextualising anomalies instead of simply flagging them.

These are challenges of reasoning and workflow, not of chatbots. Solving them requires systems that understand how analysts think and how hypotheses, evidence, and implications interrelate. That is the true frontier of progress: AI as collaborator rather than correspondent.

The way forward

The next wave of financial AI will not emerge from chatbots or generic copilots. It will come from innovators who build workflow-specific products that respect trust, auditability, and regulation. These systems will turn analysts into super-analysts, not by automating their judgment but by strengthening it.

For innovators, the challenge is to design for credibility rather than convenience. For established institutions, it is to invest in what is feasible today rather than chase distant visions. Finance will be reshaped not by replacing people but by changing how good decisions are made and scaled. Those who recognise this will define the next decade of innovation. Those who do not will continue building tools for problems that never mattered.

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