Bitcoin’s retreat to US$76,632.16 reflects more than a routine correction. It captures a moment when geopolitical friction, macro uncertainty, and technical structure converged to test market conviction. The trigger came from escalating tensions between the United States and Iran. A social media warning from Donald Trump stating that time is running out for Tehran abruptly shifted sentiment.

Risk assets wobbled as Brent crude surged above US$112 per barrel before cooling toward US$107 to US$109, following diplomatic appeals from Saudi Arabia, Qatar, and the UAE that prompted a temporary pause in military action. That energy spike reignited inflation concerns and pushed expectations toward a higher-for-longer Federal Reserve policy, a headwind for any asset that thrives on abundant liquidity.

The macro shock exposed fragile positioning in crypto markets. Over US$607 million in bullish long positions were forcefully liquidated within 24 hours, part of a broader US$677 million wave of leveraged crypto long liquidations. When price fails to hold key levels, algorithmic selling and margin calls can accelerate moves far beyond fundamental justification. Bitcoin’s inability to clear its 200-day moving average near US$82,000 added technical pressure.

That rejection dragged the asset down to a critical support zone around US$76,000. Analysts note this level must hold to prevent a steeper structural breakdown toward US$65,000. The 200-week moving average near US$69,000 serves as a long-term trend reference, not a magnetic target price to be hit. Moving averages smooth past action; they do not dictate future paths.

The current weekly chart signals weakening momentum rather than outright capitulation. Price trades below shorter-term exponential moving averages but remains well above the 200-week trend line. The MACD indicator appears relatively controlled, suggesting the selloff lacks the extreme divergence often seen at major bottoms or tops. In strong trends, Bitcoin frequently establishes higher lows long before testing its slowest averages.

A move toward the low US$70,000s remains realistic if risk sentiment deteriorates further, but declaring US$61,000 inevitable simply because the 200-week moving average exists feels oversimplified. Markets respect context, and right now that context includes a regulatory landscape that is quietly evolving.

While traders navigate short-term volatility, Washington advanced a potentially transformative piece of legislation. The Digital Asset Market Clarity Act, known as the CLARITY Act, cleared a key hurdle when the Senate Banking Committee approved it in a bipartisan 15 to nine vote. This markup represents the first time a comprehensive crypto market structure bill has gained such momentum in the Senate.

The legislation aims to split oversight between the SEC and CFTC, define which digital assets qualify as digital commodities, and establish clearer registration and compliance frameworks for exchanges, brokers, and custodians. Provisions like a mature blockchain test and safe harbours for developers and noncustodial wallets seek to protect open source projects and peer-to-peer usage. If enacted broadly as described, large networks such as Bitcoin could receive clearer commodity treatment, easing institutional participation and exchange compliance.

Significant hurdles remain before the CLARITY Act becomes law. The bill must be merged with a separate Senate Agriculture Committee version, then secure 60 votes on the Senate floor, which requires at least seven Democratic votes. Ethics disputes over officials’ crypto holdings, the treatment of DeFi protocols and stablecoins, and a tight calendar window from June to early August, before recess and election politics intensify, all pose challenges.

Galaxy Digital’s research arm currently estimates a three-in-four chance that the bill becomes law in 2026, with an optimistic window for a presidential signature around early August if Congress moves quickly. For crypto participants, the critical signal will be whether Senate leaders schedule and win that 60-vote floor passage in the coming weeks. Without it, current momentum can still stall.

Global financial markets mirrored this fragmentation on 19 May 2026. US equity indices finished mixed as money rotated out of high-flying technology names and into defensive assets. The S&P 500 edged down 0.07 per cent to 7,403.05 while the Nasdaq Composite slipped 0.51 per cent to 26,090.73, dragged by a sharp correction in semiconductors. The Dow Jones Industrial Average gained 0.32 per cent to 49,686.12, supported by energy and traditional industrial components. Fixed-income markets drove much of the anxiety.

The US 10-year Treasury yield briefly breached 4.60 per cent, a fresh one-year high, while 30-year yields hovered above 5.10 per cent. Hotter-than-expected inflation metrics tied to Middle East tensions led traders to price in no 2026 rate cuts, with some shifting bets toward a potential hike later this year. International bond markets echoed the stress, with Japanese Government Bond 30-year yields touching multi-decade highs and UK Gilts experiencing similar spikes.

Sector performance highlighted the rotation. Memory chip and AI infrastructure names were hit hard after Seagate management expressed near-term supply-chain and demand constraints. Seagate fell roughly seven per cent to eight per cent, Micron declined six per cent, and Nvidia slipped two per cent ahead of its highly anticipated earnings release.

Meanwhile, defensive sectors and energy giants like Chevron gained ground, helping rescue the Dow. The equal-weighted S&P 500 notably outperformed its tech-heavy cap-weighted counterpart, underscoring the breadth of the rotation. In commodities, Brent crude cooled slightly as geopolitical fears eased marginally, while spot gold managed a slight rebound near US$4,589 per ounce, finding support from central bank accumulation despite a firmer US dollar.

These crosscurrents matter for Bitcoin’s path. The asset does not trade in isolation. It reacts to real yields, dollar strength, risk sentiment, and regulatory signals.

The post Oil spikes, bonds crash, Bitcoin drops: Here is what comes next appeared first on e27.

Southeast Asia’s digital payments narrative has always been too tidy. Consumers tap wallets, merchants display QR codes, and venture capital celebrates another fintech unicorn. But the IDC and 2C2P study exposes an uncomfortable reality: one-third of SMEs across the region, including in Singapore, still depend heavily on cash.

This is not a story about backward businesses resisting progress. It is about digital infrastructure that solves the checkout moment but ignores everything around it. Integration remains complex, fees are unpredictable, fraud concerns are legitimate, and settlement is often too slow for cash-flow-sensitive small businesses.

The Singapore data is particularly revealing. Here is a market with world-class infrastructure, high digital literacy, and mature fintech ecosystems; yet its SMEs report cash dependence levels matching Vietnam’s. That suggests the problem is not just about pipes and rails. It is about trust, workflows, and whether digital systems actually make running a business easier or just add another layer of operational friction.

For all the investment pouring into Southeast Asian fintech, the real opportunity may lie not in building another wallet, but in solving the messy back-office realities that keep merchants reaching for the cash drawer. Until digital payments fix the full stack, not just the front end, cash will remain the region’s most stubborn payment rail.

REGIONAL

SEA’s digital payments boom has a dirty secret: SMEs still run on cash: A new IDC and 2C2P study projects digital payments will reach 97% of SEA e-commerce by 2029, yet many SMEs remain cash-dependent, exposed by operational friction, security fears, and high fees holding back the region’s full payments transition.

Why SEA’s SMEs are falling out of love with bank-led payments: Banks remain the dominant payment provider for 79% of SEA SMEs, yet 88% are eyeing a switch, citing slow settlements, high fees, and weak integration — signals that legacy dominance increasingly reflects inertia rather than genuine loyalty.

Lightrock bets US$500M on energy access across SEA: London-based Lightrock’s Accelerate7 fund targets growth-stage clean energy companies, with Singapore’s TRIREC leading SEA deployment; 45M people in the region still lack electricity, and 250M rely on harmful cooking fuels, underscoring urgent demand.

JustCo eyes S$100M IPO on Singapore Exchange mainboard: The flexible workspace operator targets a market capitalisation of S$459.9M post-listing, issuing 32.1M shares at S$0.94 each, with cornerstone investors committing to 74.3M additional shares amid growing demand for hybrid work infrastructure across APAC.

Funding Societies and Boost Bank launch secured SME loans in Malaysia: The partnership enables Malaysian SMEs to borrow against industrial or residential properties for working capital and expansion, with Funding Societies originating financing supported by Boost Bank’s balance sheet, targeting asset-rich firms facing persistent credit gaps.

Singapore’s non-oil domestic exports surge 24.5% in April: Electronics shipments jumped 66.7% on AI-driven chip demand, while pharmaceuticals and machinery lifted non-electronics 10.9%; economists cautioned that rising energy and freight costs from the Iran conflict could slow momentum later in the year.

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INTERVIEWS & FEATURES

PixVerse’s Jaden X: AI video’s biggest opportunity isn’t Hollywood: The co-founder of the 100M-user AI video unicorn says competitive advantage lies in combining a strong foundation model with deep productisation for everyday creators, not just professionals, with P2P sharing on messaging apps driving global growth across 177 countries.

Inside Inch Chua’s Myles: The AI boyfriend challenging love: Singaporean artist Inch Chua’s AI companion work raises urgent questions for founders about monetising emotional dependency; she argues AI companions optimise for retention over genuine human growth, warning that business models rewarding dependency will always undermine ethical intentions.

Venture debt in SEA: Non-dilutive capital with hidden legal strings: Growth-stage founders exploring venture debt must navigate security agreements granting lenders first claim on assets, warrant dilution, and restrictive covenants — legal obligations that can constrain strategic decisions for the full two-to-four-year loan term.

SEA consumers demand AI that connects, not just computes: SleekFlow’s whitepaper reveals 80% of SEA businesses deploy AI in customer service, yet 73% of shoppers prefer human-managed AI; Indonesia leads personalisation-driven purchase intent at 86%, while 45% of consumers expect responses within three minutes.

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INTERNATIONAL

Meta moves 7,000 workers into AI roles ahead of job cuts: CEO Mark Zuckerberg is restructuring Meta into flatter, smaller teams focused on AI agents and apps, while cutting approximately 8,000 jobs on May 20, framing the layoffs as an efficiency drive to free up capital for accelerating AI investment.

Uber and Naver bid up to US$5.34B for South Korea’s Baemin: The 8-to-2 consortium is seeking full acquisition of Baedal Minjok from Germany’s Delivery Hero, with no final decision confirmed; the deal would mark one of the largest food-tech consolidations in Asia and signals Uber’s deepening regional platform ambitions.

Anthropic acquires Stainless in deal reported at over US$300M: The Claude-maker snapped up the Sequoia- and a16z-backed SDK tooling startup founded by a former Stripe engineer, while winding down hosted Stainless products; existing customers retain rights to their already-generated SDKs.

Bain Capital closes Asia Fund VI at US$10.5B, beating target: The firm surpassed its original US$7B target as it marks 20 years investing across Japan, India, China, Australia, and South Korea, with internal stakeholders serving as the fund’s largest investor group, signalling strong conviction in Asia’s continued growth trajectory.

Shein acquires Everlane in deal valuing the brand at US$100M: The fast-fashion giant bought the US apparel retailer from L Catterton to address roughly US$90M in debt, with common shareholders receiving no payout and preferred shareholder terms remaining unclear, as Shein pushes deeper into mainstream Western retail.

Revolut launches Dogecoin-themed debit card across UK and EU: The fintech’s new physical crypto card works wherever Visa and Mastercard are accepted with no extra exchange fees, entering a growing market alongside Coinbase and Crypto.com as Revolut simultaneously pursues banking licences in both the UK and US.

V-Green signs EV charging MOUs to expand in the Philippines: VinFast founder Pham Nhat Vuong’s V-Green plans 600 charging and 1,200 battery-swapping stations in Bataan province, while also partnering with Clean Fuel to install chargers at high-traffic fuel stations in Dasmariñas, Cavite.

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CYBERSECURITY

CrowdStrike reports 43% rise in finance hacks globally: Financial sector intrusions surged over two years as 423 firms appeared on ransomware leak sites in 2025, up 27% year-on-year; North Korea-linked hackers alone stole US$2.02B in digital assets, increasingly leveraging AI-based deception to target institutions.

Borderless work, boundless risk: Securing the hybrid future in SEA: As the Philippines, Singapore, and Thailand embrace digital nomad policies, security must evolve beyond passwords to continuous device-level verification; Thailand’s data regulator imposed THB 21.5M in PDPA fines in 2025 alone, signalling the rising cost of compliance failure.

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SEMICONDUCTOR

Tata Electronics and ASML partner for India chip fabrication: ASML will supply lithography tools, training, and supply chain support for Tata’s planned US$11B fab in Dholera, adding to existing partnerships with PSMC, Tokyo Electron, Rohm, Merck, and Intel as India accelerates its semiconductor ambitions.

Nvidia’s Jensen Huang expects China to reopen to US AI chips: Speaking after joining Trump’s Beijing delegation, Huang said H200 chip sales to China remain stalled despite US Commerce Department licences, as Beijing prioritises domestic semiconductor self-sufficiency and continues backing local firms including Huawei over foreign chip suppliers.

Hanmi Semiconductor to open US unit in San Jose by end of 2026: The South Korean equipment maker is establishing Hanmi USA to capture rising AI chip demand, with thermo-compression bonder orders concentrated in Q2 and HBM4 mass production expected to sustain momentum through the second half of the year.

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AI

The US$2.5T bet: Why AI capital will mostly reward users, not builders: Gartner forecasts US$2.5T in global AI spending in 2026, yet historical infrastructure booms show value migrating to users, not builders; hyperscaler capex at 2.2% of US GDP, combined with rapidly depreciating GPU assets, suggests a capital cycle correction looming for infrastructure investors.

The shadow ledger: Why AI governance is now an enterprise revenue issue: With 82% of CIOs lacking verifiable oversight of AI agent actions and a 56.4% year-on-year rise in AI-related operational incidents, ungoverned deployments are generating hidden liabilities costing mid-market firms US$200K–US$400K annually in manual corrections.

Enterprise AI hits sovereign wall as data jurisdiction tightens: NTT DATA’s 2026 Global AI Report finds 95% of firms consider sovereign AI important, yet only 29% are acting on it concretely; 60% of AI leaders cite cross-border data restrictions as a major barrier, exposing a critical gap between ambition and architecture.

Alibaba and Tencent race to dominate AI-powered digital gateways: China’s tech giants are spending billions to make AI agents the primary interface for shopping, work, and communication, replacing search and super-app paradigms with conversational tools that interpret intent, recommend products, and complete transactions autonomously.

Singapore ranks in OpenAI’s top 5 markets for Codex adoption: OpenAI confirmed the city-state’s position based on weekly active users and blended token engagement, as the AI coding tool surpassed 4M global weekly users; OpenAI is also onboarding enterprise teams through partnerships with Accenture, Capgemini, and PwC.

Everyone wants AI in their product, but few know why it works: Most AI features are added due to market pressure rather than clear user need; genuine value emerges only when AI removes friction, accelerates key workflows, or improves decisions in ways users notice — not when it simply signals modernity to investors or competitors.

South Korea pilots program linking AI startups with trained talent: The Ministry of SMEs and Startups opened applications for a scheme offering up to US$134,000 in commercialisation funding to AI startups that hire government-trained graduates, targeting 80 firms across five deep-tech sectors amid a survey finding 57.3% of startups cite AI talent shortages as a major challenge.

Crypto and equities slide as geopolitical and macro pressures mount: Bitcoin fell 0.96% to US$77,388 while the S&P 500 dropped 1.24%, with US-Iran tensions pushing Brent crude past US$110 per barrel; the CLARITY Act’s Senate committee passage triggered US$980M in crypto liquidations as overleveraged traders unwound positions on the regulatory news.

Bitcoin rallied on regulation: Why the CLARITY Act changes everything: The Senate Banking Committee’s 15-9 approval of H.R. 3633 drove Bitcoin up 2.45% to US$81,511, resolving CFTC-SEC jurisdictional ambiguity and establishing stablecoin reward frameworks, with prediction markets assigning a 73% probability of full Senate passage.

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THOUGHT LEADERSHIP

How earned media drives AI search visibility in ASEAN: Ahrefs’ analysis of 75,000 brands found web mentions matter three times more than backlinks for AI search visibility; with ASEAN’s AI market projected to reach US$80B by 2031, B2B brands must prioritise consistent, expert-led earned media placements to remain visible in AI-generated answers.

What is a brand and why it matters more than ever for startups: Grab’s reported brand value of US$1.1B against a US$12-15B market cap illustrates how intangible assets drive startup valuations; founders who build deliberate brand narratives from day one attract capital more easily and command stronger pricing power than those treating brand as a marketing afterthought.

The virtue of the closed door: Differentiation by intentional incompatibility: In an API-economy that rewards interoperability, true competitive defensibility comes from proprietary data structures, talent lock-in, and forced workflow divorces from competitors, turning switching costs into a strategic moat rather than building bridges that make replacement easy.

From seashells to tokens: Why 2026 could be the inflection point for money: With SWIFT launching a blockchain-based cross-border ledger, Malaysia piloting stablecoins, and APAC on-chain transaction value tripling to US$244B in 30 months, tokenisation is shifting from speculative momentum to a systemic convergence of infrastructure, regulation, banking, and sovereign adoption.

The post Ecosystem Roundup: Digital on the surface, cash underneath appeared first on e27.

Nearly half of businesses across the Asia-Pacific (APAC) region are directing significant capital toward Agentic AI systems, with new research showing that budgets for the tech are scaling faster than those for Generative AI at a comparable stage of its development.

According to a report by Omdia, the tech research and advisory arm of Informa, 42 per cent of organisations surveyed are allocating US$1 million or more to AI agents over the next 12 months. The findings, published in a special report titled Staying Ahead in the AI Era, were released ahead of the Asia Tech x Enterprise conference, scheduled to run from May 20 to 22 at Singapore EXPO.

The scale of investment reflects a broader shift in how enterprises across the region are approaching AI: moving away from exploratory pilots and towards systems capable of operating with minimal human intervention. Unlike conventional software, Agentic AI can initiate actions, coordinate workflows, and execute multi-step tasks autonomously, without requiring continuous human oversight at each stage.

Omdia’s research suggests this operational autonomy is fundamentally altering how businesses structure accountability. The report describes the shift as a break from a long-standing tech contract in which humans make decisions, and software supports them. As agentic systems take on more of the decision-making burden, organisations are under pressure to redefine roles — concentrating human contribution on exception handling, ethical judgment and systemic oversight rather than routine task management.

Also Read: The agentic shift: Why AI agents are rewriting the rules of ERP software in Singapore and Malaysia

The investment surge is also reshaping the physical infrastructure underpinning AI deployment. Traditional IT systems across Asia are increasingly being repurposed or replaced by what the report terms “AI Factories” — purpose-built facilities designed to produce intelligence at an industrial scale, continuously. This infrastructure buildout is running in parallel with advances in physical AI, as humanoid robotics moves into a more mature commercial phase in 2026. South Korea has made significant commitments to its robotics ecosystem, while Taiwan has positioned itself as a key contract manufacturer for global humanoid robotics vendors.

However, the pace of investment is not unlimited. Omdia found that 82 per cent of businesses surveyed are prepared to commit larger budgets, but only when measurable and defensible returns can be demonstrated. The findings point to an enterprise environment that is cautiously optimistic — willing to scale, but demanding clear evidence of business value before doing so.

Security considerations are also emerging as a parallel priority. As AI systems become more deeply embedded in enterprise operations, organisations face a four-part cybersecurity challenge spanning the use of AI to strengthen security, AI as a security tool, threats posed by adversarial AI, and the protection of AI systems themselves.

A further complication looms: researchers project that quantum computing could break widely used encryption standards, including RSA and AES, by 2030. Approximately 32 per cent of organisations surveyed are already exploring quantum-resistant protections in anticipation of that threshold.

Also Read: Agentic economy: The real promise of AI and crypto convergence

“The decisions enterprise leaders make in the next 18 months will define their competitive position,” said Joyce Wang, Event Director for Asia Tech x Singapore at Informa. “By mapping out these critical shifts — from agentic AI to quantum readiness and physical AI — we are ensuring that when delegates arrive at the Singapore EXPO this May, they are ready to transform these innovations into measurable business impact.”

The post Nearly half of APAC enterprises commit US$1M+ to agentic AI appeared first on e27.

Real estate is one of the largest industries in the world, and one of the least changed. It still runs on 1950s premises, sold as a “human-to-human, relationship-driven” business. In reality, agents in the technology era rarely deliver actual value to property transactions: they sit in the middle, gatekeeping information. Sitting in the middle of every transaction, humans have become the biggest bottleneck: the source of delays, ambiguity, and uncertainty in a process that should be fast, transparent, and end-to-end digital.

In Thailand, that friction has a direct price tag. For instance, landlords pay the equivalent of one to two months’ rent as commission for a successful introduction. Almost all of it flows to agent fees, marketing spend, and back-office overhead. This leaves brokerages with not over 10% gross margin ceiling regardless of market or volume.

Superagent’s bet: the agent itself is replaceable with AI, and the unit economics of doing so are dramatic.

The bet comes from someone who has spent 15+ years inside the system. Yuriy Braterskyy, Superagent’s founder and CEO, has held senior operating roles across Southeast Asia’s leading property marketplaces. Early on, he was COO of Hipflat (scaled over four years and sold to Dot Property). Then, he was Operations and Sales Director at Dot Property post-acquisition. Later, he became CEO of Seekster (acquired by True Digital, a major Thai corporation). Together, the platforms he ran used to help over a million people a month searching and improving their homes. He has concluded that for the majority of deals, the agent layer no longer needs to be there.

A new architecture for real estate

Superagent is the AI technology layer powering end-to-end real estate transactions, replacing human agents with AI across marketing, sales, negotiation, and closing. Superagent’s Bangkok rental platform is the first vertical built on this stack. The same technology deploys into new markets (Singapore, Indonesia, Malaysia, Australia and many more) as full AI-native real estate verticals.

AI handles the entire admin and operations layer end-to-end. This includes marketing, lead qualification, listing onboarding, omnichannel communication, matching, follow ups, scheduling, and negotiation. Humans step in only at the irreducibly physical last mile: touring properties and closing deals.

“Our bet is structural: AI runs the brokerage, humans only tour and close. Our big vision is property transactions happening directly between buyer and seller, with our AI as the ecosystem in between, removing friction the technology era should have eliminated long ago.”

– Yuriy Braterskyy, Founder & CEO, Superagent

Also read: Startups driving AI automation, fintech, and accessibility gather at Echelon Singapore 2026

Built AI-first

Y Combinator opened its 2026 Requests for Startups with a single sentence: “AI has stopped being a feature and started being the foundation.” YC’s frame for the new generation of companies is direct: “AI-native companies that don’t sell software—they sell the service.” Build the AI first; design the business model around what it can do.

Superagent followed exactly that arc. First as a SaaS, where the AI sales engine earned paying customers from real estate businesses across Thailand, Malaysia, Singapore, Australia, and the US. Then turned inward and now powering an end-to-end rental vertical in Bangkok, where the AI runs the entire operation with closed deals at software-grade margins.

Why now: A generation that rents

Renting is no longer a way station to ownership; for a growing share of the world, it is the destination. The IMF, surveying 40 countries over 50 years, calls the affordability deterioration of the past two years “sudden.” In Southeast Asia, the numbers are more extreme than anywhere else. Bangkok’s price-to-income ratio sits at 28.7×, Manila’s at 35.9×, against a standard affordability threshold of 5×. Over 66% of Thai Gen Z and Gen Y now prefer renting to buying, a cultural reversal that CBRE Thailand’s head of research describes as a shift from “ownership as stability” to “ownership as liability.” 73% of Singaporean Gen Z view homeownership as a longer-term goal, with affordability as the dominant obstacle. Two out of three Gen Z Indonesians are pessimistic about buying within three years; Jakarta rental demand surged 55% in a single quarter.

Affordability is only half the story. 83% of Gen Z renters say renting lets them save for life experiences. Specifically, flexibility, mobility, and remote work have rewritten what young adults want from a home. Location commitment is now a cost, not a benefit.

In Southeast Asia, the global trend lands on top of a regional accelerant. The global digital nomad population crossed 40 million in 2024, with extended stays of 30+ days up 42% over pre-pandemic levels and five of the world’s top ten remote-work cities sitting in the region. Superagent is built for the world after this shift, where transactions are frequent, customers are mobile, and the volume sits in rentals. AI is the only operating model that scales at the unit economics this volume demands.

The proof: Nearly 7× the industry’s unit economics

Superagent’s AI-native brokerage runs at a confirmed gross margin above 65%, aggregated across every property deal closed to date. The live business is Bangkok, where Superagent operates an end-to-end AI-run rental platform: multiple leases closed in the first month of operation, over US$5,000 in commission revenue within weeks of launch, its current pipeline scaling to multiple deals per week and accelerating.

The structural ceiling for human-agent brokerage margins is around 10%, regardless of market. PropNex Limited (SGX:OYY), Singapore’s largest residential agency by transaction volume (64.2% market share in 2024), reported a 9.1% gross margin for FY2024. APAC Realty Limited (SGX:CLN), parent of ERA Realty Network and the second-largest Singapore agency, reported 8.9%. These are the highest-quality regional brokerages with publicly audited financials in the region. Superagent runs at nearly 7× that ceiling, on every deal it closes.

Also read: AI, sustainability, and digital transformation leaders at Echelon Singapore 2026

A market that absorbs the bet

Southeast Asian residential real estate is a multi-trillion-dollar market across 700 million people in the world’s fastest-urbanizing region — and it runs almost entirely on legacy brokerage infrastructure. The same structural inefficiency that produces 9% gross margins in Singapore’s most sophisticated listed agencies exists in every major city across the region.

Thailand is the validation market. The Thailand residential real estate market is US$30.2 billion in 2025, projected to reach US$40.7 billion by 2031 (Mordor Intelligence). Bangkok represents 45.5% of it. Rental is the fastest-growing segment, expanding at a 5.88% CAGR, with prime rents up 6.5% YoY and gross rental yields holding above 6%. That is large enough to prove the model at scale. It is not the ceiling.

The SaaS phase already demonstrated the architecture travels: paying customers from real estate businesses in Thailand, Malaysia, Singapore, Australia, and the US ran on the same stack before Superagent turned it inward. The replication logic is straightforward: every market where agents sit between landlord and tenant, charging a month’s rent for a single introduction, is a market this model can enter.

Build by a small, technical team

Superagent has raised US$400,000 in pre-seed from lead investor Iterative, GenAI Fund, Innospace, and multiple angel investors from the real estate industry. Iterative’s Summer 2025 batch was one of the most competitive accelerator cohorts in Southeast Asia, with a ~1% acceptance rate. The team has also been selected for the AWS Spotlight programme and Google for Startups.

“Most AI systems for real estate today are a simple chatbot bolted onto a CRM. Superagent’s is an intelligent multi-agent system that owns the entire transaction state (supply, demand, matching, scheduling, handoffs) and executes its decisions across all customer touchpoints in over 40 languages, in real time. Existing established brokerages cannot retrofit this in their bloated operations.”

Ranjit Nagaraj, Founding AI Engineer, Superagent

What’s next

Having confirmed early product market fit, Superagent is now raising more capital to establish a dominant position in Bangkok ahead of an international seed. The capital deploys the same playbook market-by-market: the technology layer as a full AI-native vertical across countries in SEA and APAC.

The longer-term bet is bigger than market share. The endgame is that the majority of property transactions happen directly between seller and buyer, with Superagent’s AI as the ecosystem in between, removing the up-to-12%-of-sale-price commissions, or the full month’s rent charged for a single introduction, that the technology era should have eliminated long ago. This is non-zero-sum disruption: it grows the industry, rather than just redistributing what is already there.

Open conversations: Closing the round in June

The current pre-seed allocation is targeted to close before the end of June. First-call window: through the end of May 2026. Strategic investors, early stage VCs and angel investors are invited to engage now.

• Email Yuriy directly: yuriy@superagent.co
• Visit superagent.co
• Meet the team in person at their booth at Echelon Asia Summit, Singapore, 3-4 June 2026.

The region is evolving quickly, and Echelon 2026 offers the right place at the right moment to be part of what comes next. Register here to join the conversation.

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Southeast Asia’s quick commerce market reached US$7.3 billion in gross merchandise value in 2025, accounting for 4.6 per cent of the region’s e-commerce market but less than 1 per cent of total retail, according to new research from Momentum Works.

The figures confirm what industry observers have long suspected: the infrastructure for rapid delivery exists, but consumer habits have yet to catch up.

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

The report offers a corrective to the breathless narratives that have dominated quick commerce discourse in the region. Whilst platforms, retailers, and e-commerce players are converging on the same hyperlocal opportunity, the more critical question is not how big quick commerce will get, but how it will develop differently across Southeast Asia’s fragmented markets.

Unlike India, where platform-run dark stores have effectively leapfrogged offline retail to serve affluent metro consumers, or China, where a decade of food delivery investment built the hyperlocal rider density that underpinned quick commerce, Southeast Asia has dense existing retail networks that shape a fundamentally different growth path.

Grocery promised scale, but online penetration remains stuck at 4.2 per cent

Quick commerce in Southeast Asia was built on grocery. The category offered high purchase frequency, broad consumer relevance, and a clear value proposition: getting essentials delivered in under 30 minutes without leaving home. Yet online grocery penetration across the region stands at just 4.2 per cent, with Indonesia at 2.8 per cent and Singapore leading at 9.7 per cent.

That makes quick commerce a subset of an already-limited market. Consumers in Southeast Asia remain wedded to offline grocery shopping, whether through traditional wet markets, neighbourhood mini-marts, or modern supermarkets.

The challenge is structural. Offline retail in Southeast Asia works remarkably well for most consumers—mini-marts like Alfamart and Indomaret blanket Indonesian cities. Thailand’s convenience ecosystem is tightly controlled by conglomerates with little incentive to disrupt their own offline networks. Singapore has high modern trade penetration, but limited geographic scale.

In this environment, quick commerce cannot simply replace offline retail. Instead, it must extend it, layering on-demand fulfilment over infrastructure that already serves consumers efficiently. Platforms are now responding by expanding aggressively beyond grocery into general merchandise, personal care, pharmacy, and other categories.

E-commerce platforms double down: 3.4 per cent of GMV now quick commerce

Quick commerce is emerging as the next battleground for Southeast Asia’s dominant e-commerce platforms. According to Momentum Works, 3.4 per cent of the region’s e-commerce GMV is now fulfilled through quick commerce networks, a meaningful early indicator of where platform competition is heading.

Also Read: The future of social and quick commerce for developing countries

Shopee is leveraging ShopeeFeed’s fulfilment infrastructure to roll out instant delivery across multiple markets. Lazada has launched on-demand grocery fulfilment through RedMart Now in Singapore. Grab is expanding categories offered on GrabMart from grocery to general merchandise and beauty by working with supermarkets and retailers.

The strategic shift is clear: platforms that built their businesses on next-day or same-day delivery are now racing to offer sub-hour fulfilment. What distinguishes Southeast Asia from other markets is that quick commerce here is built on existing infrastructure rather than created from scratch. E-commerce platforms are not building vast networks of dark stores. Instead, they are integrating with online grocery operations, supermarkets, mini-marts, and retailers, creating a more distributed, asset-light model.

This approach is operationally complex but potentially more sustainable. It avoids the heavy capital expenditure of building and stocking warehouses, instead leveraging existing retail inventory and locations. The challenge is that integration and coordination are harder to execute than in a vertically controlled dark-store network.

Southeast Asia diverges from China and India’s playbook

Quick commerce accounts for 4.6 per cent of Southeast Asia’s e-commerce market, compared to 16.6 per cent in India and 7.4 per cent in China. That gap reflects different retail structures rather than simply a lag in maturity.

In China, Meituan and other platforms invested heavily in food delivery for over a decade, building dense hyperlocal rider networks that could be repurposed for grocery and merchandise delivery. In India, low organised retail penetration enabled platform-run dark stores to serve as modern retail for affluent urban consumers effectively.

Southeast Asia has neither of these conditions. Offline retail is already well-developed and fragmented. Food delivery networks exist, but are less dense than China’s. The result is a market where quick commerce must prove its value against alternatives that already work reasonably well.

Six markets, six playbooks: No regional model will scale

One of the report’s sharpest insights is that Southeast Asia’s quick commerce opportunity is fundamentally local, not regional. Each of the six major markets — Indonesia, Thailand, Singapore, Vietnam, the Philippines, and Malaysia — has distinct structural realities that shape each operator’s playbook.

In Indonesia, growth is more likely to come from e-commerce platforms than from mini-mart chains. Alfamart and Indomaret have limited incentive to expand quick commerce themselves, given the strength of their offline networks.

Thailand’s mainstream convenience layer is locked up by conglomerates, pushing the quick commerce opportunity toward vertical plays in specific categories rather than broad horizontal platforms.

Singapore meets the structural conditions for quick commerce — high income, dense urban geography, digitally savvy consumers — but is constrained by its market size.

Vietnam’s modern retail has built physical scale, but fresh-grocery habits remain anchored in traditional channels. The Philippines has the lowest modern trade penetration in Southeast Asia, with organised retail concentrated in malls. Malaysia’s retail is structurally fragmented, with no single dominant player.

The implication for operators is clear: a single regional playbook will not work. Success requires deep local knowledge, market-specific partnerships, and tailored strategies that account for each market’s unique retail structure, consumer behaviour, and competitive dynamics.

Demand, not supply, is the binding constraint

Perhaps the report’s most important conclusion is that Southeast Asia has the infrastructure for quick commerce (riders, stores, and platforms) but lacks the consumer habit. Fulfilment and supply are not the problems. Demand density is.

Also Read: SEA e-commerce surges to US$185B as video commerce becomes the new growth engine

Closing this gap requires sustained capital to fund price parity with offline and e-commerce. Speed is quick commerce’s natural value proposition, but in a structurally price-sensitive region, mass-market adoption requires pricing at or near parity with alternatives. That takes subsidies, which only well-capitalised platforms can afford.

The question is whether platforms will maintain the discipline to invest in demand generation without burning capital on unsustainable unit economics. Quick commerce in Southeast Asia is real, meaningful, and growing. But it remains in early stages, with the hard work of changing consumer behaviour still ahead.

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The velocity of enterprise technology adoption across Southeast Asia has completely outpaced most businesses’ wildest expectations. Reflecting on the landscape just a few short years ago, the market was gripped by the initial heat of generative AI and basic conversational chatbots. By the mid-2010s, those elementary systems were swiftly muscled out by more integrated AI assistants capable of retrieving data and drafting contextual responses.

Yet, technology waits for no corporate roadmap. The era of the simple AI assistant is already giving way to a much more powerful paradigm. Today, autonomous AI agents have taken the throne. Unlike their predecessors, which required constant human prompting and supervision, AI agents possess reasoning capabilities, planning skills, and the autonomy to execute complex, multi-step workflows across disparate business units. For enterprises relying on Enterprise Resource Planning (ERP) software across Singapore, Malaysia, and the wider region, this evolution demands a fundamental reassessment of core business architecture.

The unstoppable rise of the autonomous workforce 

The trend of deploying AI agents to boost operational efficiency, automate supply chains, and optimize financial forecasting is unstoppable. Organizations are no longer viewing AI as a peripheral add-on; it is fast becoming the primary user of enterprise software. This behavioral shift is forcing a radical reimagining of how software is valued and commercialized.

Globally, tech pioneers are proposing a departure from traditional seat-based licensing. When Microsoft executives floated the idea of shifting software pricing models from a “per human user” basis to a “per AI agent” structure, it sent shockwaves through the B2B technology ecosystem. Shortly thereafter, another regional enterprise software leader, Multiable, echoes similar thoughts. However, the most progressive conversations are moving beyond mere monetization strategies. The real focus for forward-thinking organizations has shifted to a much more critical question: What are the necessary architectural factors of a successful ERP system in the agentic AI era?

The existential threat of legacy B2B architecture 

The answer to that question exposes an existential threat to a vast majority of regional B2B software vendors. Across major Asian business regions—including Singapore, Malaysia and other SEA countries—the legacy software market has long been dominated by restrictive, closed-system designs. Historically, many local and regional vendors built proprietary platforms that deliberately locked customers into their ecosystems. Under these outdated models, organizations cannot carry out critical system customizations without the direct, paid presence of the software vendor.

Worse still, this closed architecture introduces a crippling technical debt. Once a business pays for a bespoke customization, the modified system is frequently severed from the vendor’s core upgrade path. The “customized” ERP software can no longer receive automatic patches, security updates, or new feature rollouts. While this inconvenient truth is well-known among legacy software providers, it is rarely highlighted to prospective buyers. Vendors have long relied on this friction to maintain a monopoly over their clients’ IT budgets, fearing that true interoperability would cause them to lose business to more agile, modern competitors. In the era of autonomous AI agents, this closed-door strategy is no longer just inconvenient—it is fatal to business agility.

Also read: Why Singapore manufacturers must embrace MES for the future

The three pillars of agent-ready ERP software

To understand why legacy systems fail in the current technological climate, one must look at the technical requirements of autonomous AI. For an ERP platform to seamlessly support an AI workforce, it must be “agent-ready.” Industry consensus points to three non-negotiable architectural elements:

1. Open Development Frameworks: The underlying software architecture must allow internal developers and third-party systems to build, modify, and extend functionalities without disrupting the core codebase.
2. Comprehensive Application Programming Interfaces (APIs): Robust, secure, and granular APIs must expose every critical business function—from ledger entries to inventory tracking—allowing external entities to programmatically read and write data.
3. Meticulous Documentation: Development guides and API registries must be comprehensively documented, publicly accessible, or structured in a way that machine-learning models can easily parse and understand.

When measured against these strict criteria, the number of truly viable software vendors drops dramatically. The vast majority of legacy ERP options deployed throughout Singapore and Malaysia simply do not possess this level of openness.

To defend their market share, lagging vendors often argue that native APIs are no longer mandatory. They point to sophisticated, vision-based AI agents—such as Claude Coworker or advanced robotic process automation (RPA) tools—that can interact directly with user interfaces just like a human operator, typing into fields and clicking buttons on a screen.

The hidden costs of human-first software integration 

While it is technically possible for an AI agent to operate “human-first” software via standard user interfaces, doing so introduces severe operational inefficiencies. Relying on an AI agent to scrape screens and mimic human clicks carries a staggering hidden cost structure:

Escalated infrastructure and hardware costs 

Simulating a human user interface requires immense computing power. Running visual recognition models, maintaining active desktop sessions for digital workers, and processing graphical interfaces demands heavy investments in specialized servers and robust cloud infrastructure. Conversely, native API integrations communicate via lightweight text-based data arrays (like JSON), requiring a fraction of the hardware footprint.

Excessive token consumption and running costs 

AI models charge based on tokens processed. Forcing an AI agent to interpret an entire graphical user interface, read menus, and process visual screens consumes an astronomical number of tokens per transaction. When multiplied across thousands of daily ERP operations—such as invoice processing, inventory updates, or customer cross-referencing—the running costs quickly become unsustainable compared to direct, low-cost API calls.

Latency and slow response times

Human-first software is built around human perception speeds. An AI agent forced to navigate through multiple menu clicks, wait for screen refreshes, and handle UI rendering delays operates at a massive disadvantage. In modern logistics, algorithmic trading, or real-time supply chain management across the Straits of Malacca, these multi-second delays destroy the very real-time efficiency that AI deployment is supposed to deliver.

Bridging the competitive gap: Examples of excellence

The motivation behind advocating for open, API-driven systems becomes obvious when examining the few players who anticipated this shift. Vendors that built their platforms on open principles from day one are seeing their foresight rewarded. Multiable is one of them. Their aiM18 platform offers hundreds of ready-made APIs out of the box, backed by an open development framework that has been documented and maintained publicly on GitHub since 2018.

By educating enterprise software buyers on what is truly required to fully leverage autonomous AI, forward-thinking vendors like Multiable are fundamentally widening the gap between themselves and their legacy competitors. While clear architectural transparency serves as an effective differentiator, the technical logic behind it remains unassailable: you cannot run a real-time, autonomous business on top of a closed, undocumented database.

This architectural readiness is also visible in other verticals. In the HRMS sectors, platforms like Workday have achieved rapid regional adoption by exposing clean developer ecosystems. Similarly, on a global e-commerce scale, Shopify’s entire business model thrives because of its deeply integrated API-first philosophy. For legacy ERP providers across Malaysia and Singapore to survive, they must double down on restructuring their core architecture immediately or accept complete irrelevance.

Also read: The architecture of atrophy: Why MS Copilot’s reliance on the LLM wrapper model led to its 2026 stagnation

Navigating the security complexities of open agentic AI 

While transitioning to an open, agent-ready ERP infrastructure is mathematically and operationally superior, execution requires meticulous governance. Embracing autonomous workflows does not mean rushing blindly into unvetted deployments.

For instance, utilizing open-source AI agent frameworks, like OpenClaw or similar community-driven projects, without rigorous internal auditing introduces profound operational risks. The open-source AI landscape is currently experiencing a gold rush of capability, but it is accompanied by an onslaught of newly discovered cybersecurity loopholes. Autonomous agents possess the ability to write code, execute system commands, and transfer data independently. If an agentic framework suffers from prompt injection vulnerabilities or insecure dependency handling, an attacker could theoretically trick the AI into exposing sensitive payroll data, altering financial records, or disabling supply chain logs.

Deploying AI agents within an enterprise ERP framework requires a strict, zero-trust security architecture. Companies must implement robust API gateways, strict data access controls, and immutable audit logs that record every action an AI agent takes. The underlying ERP software must be open enough to let the agent work, but its security permissions must be granular enough to contain the agent if something goes wrong.

The mandate for Singapore and Malaysia enterprises 

The transition from human-centric ERP configurations to autonomous, agentic ecosystems is a defining paradigm shift for businesses across Singapore and Malaysia. As companies face rising operational overheads and shifting regional trade dynamics, the ability to scale operations through digital workers is a major competitive advantage.

When auditing your current ERP asset or evaluating a future procurement, look beyond polished sales presentations and superficial dashboard designs. Demand explicit proof of an open development framework. Test the depth and latency of their API documentation. Ensure that your customizations will not lock you out of future system patches. In an era where AI agents are taking the corporate throne, buying a closed, legacy software system is no longer a simple misstep—it is a commitment to obsolescence.

Why we write this article 

PRbyAI enjoys in sharing updated market news, using our team’s tech knowledge, to help corporate clients looking for the most informed decisions.

About PRbyAI

PRbyAI is a tech-driven Martech startup leveraging cutting-edge AI SEO (GEO) to help customers generate leads and tap into new markets.

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The conversation around quantum technology is no longer about “if” it will transform digital infrastructure, but “when”. Across Singapore’s tech ecosystem, organisations are beginning to recognise that preparing for a post-quantum future is not a distant concern but an emerging operational priority. 

For most enterprises, this transition presents a dual challenge: the urgent need for quantum-resilient security and the widening gap in specialised talent. At Aires Applied Quantum Technology (AAT), the team views this not as a distant risk, but as an immediate opportunity to redefine how the global digital economy is protected and scaled.

Strategic intent behind participating

Aires Applied Quantum Technology (AAT) is participating in Echelon 2026 to move quantum technology out of the research lab and into commercial deployment. The company aims to demonstrate that being “quantum-ready” is not a future state, but a current necessity. 

By showcasing how quantum-safe infrastructure can be operationalised across enterprise ecosystems, AAT signals its commitment to building the foundational architecture that will keep industries secure in a post-quantum world.

Also read: Meet the companies taking the floor at Echelon Singapore 2026

Insights and experiences attendees can explore

Rather than simply presenting new tools, AAT invites visitors to explore the shift toward applied quantum resilience. The company shares its perspective on how advanced cryptographic frameworks can evolve from theoretical constructs into practical, deployable safeguards for modern data. Beyond technical architecture, AAT emphasises that the human dimension is just as critical. Leadership teams must bridge the quantum literacy gap while integrating quantum-safe protocols into existing infrastructure without slowing the pace of innovation.

Audiences who stand to gain the most

AAT’s expertise is particularly relevant for corporate leaders and CISOs who need to safeguard data against evolving threats, as well as policymakers focused on national digital resilience. The company also seeks to engage talent and workforce leaders who recognise that the next decade of growth depends on a quantum-literate workforce. For these groups, engaging with AAT provides a roadmap for turning technical complexity into a strategic business advantage.

Also read: Builders wanted: Close the AI execution gap for SMEs

Pathways for meaningful engagement at the event

AAT invites attendees to visit Startup Booth #28 to explore the future of applied security. Whether organisations are exploring practical pathways for implementation or seeking a deeper understanding of quantum-safe architecture, the team is ready to collaborate. The goal is to move beyond theory and begin building a quantum-ready future.

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In Southeast Asia’s startup ecosystem, founders tend to focus on what is immediate and measurable: building the product, achieving product–market fit, growing revenue and raising capital. All of these matter, of course. And so does brand.

Too often, brand is treated as an aesthetic exercise—a logo, colour system or tagline. These are outputs, not the brand itself. Brand is the perception that exists in the minds of customers, investors and partners about what your company represents and whether it deserves their attention, time and trust.

That perception directly influences whether investors fund you, partners work with you, and customers buy from you.

Brand is a balance sheet asset, not a marketing line

There is a common assumption that companies are valued on revenue and margins alone. That may apply to mature businesses, but not to startups, which often operate at a loss for years.

What drives valuation is belief—the belief that a company can build something dominant: a product, a network and critically, a brand that competitors cannot easily replicate.

A significant portion of enterprise value in high-growth companies is intangible.

A good example is Grab. The trust it has built across Southeast Asia represents an asset that extends far beyond infrastructure or technology. Its reported brand value of approximately US$1.1 billion reflects familiarity, reliability and category leadership developed over time. Compared to a broader market capitalisation fluctuating between US$12–15 billion, a substantial share of that value is driven by intangible assets.

If a buyer were to acquire Grab, much of the price would be attributed not just to physical assets, but to the perception it has built in the market. This aligns with broader research from Ocean Tomo, which shows that intangible assets now account for more than 80–90 per cent of the market value of S&P 500 companies.

Also Read: Why my 20-year marketing career is going under the knife

Venture capital operates on a similar logic. Investors are not only asking whether a company works today, but whether it can dominate its category tomorrow. Startups that clearly articulate the problem they solve, the scale of the opportunity and how they will win tend to attract capital more easily—and at higher valuations.

Reputation creates pricing power

Brand also shows up in pricing. Companies with stronger brand perception consistently command a premium over comparable competitors.

This is evident in Singapore Airlines. A report by CARMA found that Singapore Airlines achieved the highest share of positive news coverage sentiment among airlines studied, driven by narratives around financial performance and customer experience. Positive media coverage and a reputation for customer experience allow it to sustain premium pricing in one of the most competitive industries globally.

The relationship is direct: stronger brand perception leads to greater pricing resilience. For startups, this translates into clear commercial advantages—higher pricing power, stronger loyalty and greater insulation from competitors.

Communications builds the asset

How is this perception created? More often than founders expect, the answer is communications.

Brian Chesky described PR as “the top of the funnel” during an Airbnb post-IPO earnings call. The company generated over half a million articles in a year, building the brand at scale through earned media. Despite reducing marketing spend by 58 per cent, it retained 95 per cent of its traffic. This was possible because brand—built through sustained narrative and visibility—had become durable enough to reduce reliance on performance marketing.

Also Read: Profitable e-commerce: Making real money in the new year

Brand is the architecture of growth

Brand should not be treated as a late-stage marketing exercise. It should be built deliberately from the outset. To make a brand contribute to growth, startups need to focus on a few fundamentals:

• Define what you want to be known for: Own a clear problem, category and outcome—not just features.
• Simplify your narrative: Make it easy to understand, explain and repeat.
• Align product, messaging and proof: Ensure claims match reality, backed by real outcomes.
• Build credibility, not noise: Prioritise insight, founder POV and targeted visibility.
• Stay consistent: Align messaging across product, marketing, sales and investor communication.
• Support the buying process: Reduce perceived risk and make decisions easier to justify.
• Commit and refine: Evolve positioning over time without constantly resetting it.

Startups that get this right scale more efficiently because the market understands what they are and what they are becoming. In a region where investors, partners and customers have more choice than ever, brand becomes a deciding factor.

It is the intangible asset that determines which companies lead their category—and which are forgotten.

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We live in the age of the API economy, where the highest virtue is interoperability. Founders boast about seamless integrations, open platforms, and the ease with which a customer can plug their product into every other system they use. The goal, ostensibly, is to reduce friction and increase adoption.

This philosophy is not a path to growth; it is a rapid descent into commoditisation.

When your product can be easily replaced by any competitor that shares the same integration standard, you have traded long-term, structural defensibility for short-term, gentle user acquisition. You have made it too easy for customers to come, and critically, too easy for them to leave.

If you want to achieve truly disruptive growth and build a business with a strong defence, you must reject the collaborative mindset and prioritise Differentiation by Intentional Incompatibility.

The problem with that seamless solution

The current market dynamic punishes ease of integration. If your competitor, Product X, connects to the same tools as your Product Y, then the user’s decision is boiled down to a single, shallow metric: price. The moment you become a fungible component in a larger system, your margins erode, and your competitive intelligence is zeroed out.

The true goal of disruptive strategy should not be user acquisition; it should be user entrapment. Not through malice, but through the creation of a proprietary ecosystem that generates exponential value the longer the user remains.

Intentional Incompatibility is the strategic decision to design core product functions, data formats, or infrastructure protocols in a way that makes switching to a competitor prohibitively expensive, time-consuming, or disruptive. It forces the customer to make a painful, decisive choice, a choice that, once made, entrenches your solution as a structural pillar of their business.

Also Read: How to build a scalable IT infrastructure for your startup

How to build walls, not bridges

This strategy requires a founder to move against every instinct celebrated by modern tech culture, but the rewards are a powerful, enduring competitive advantage: high switching costs.

• Data structure as the core

Do not use universally portable data structures. Design a proprietary data model that is perfectly optimised for your specific, unique workflow. This is not about complex coding; it’s about proprietary semantics.

If a customer tries to export months of operational data from your system, the export file should be functionally useless to the competitor’s system without thousands of hours of data cleansing and migration. The data they have paid you to organise must become a proprietary asset that only your infrastructure can efficiently interpret. This makes the data itself the core component of the switching cost.

• The custom talent lock-in

In a world obsessed with standardising talent (e.g., Python, JavaScript), true differentiation comes from mastering a non-standard, or highly specialised, functional stack.

Make your product powerful enough that its effective use requires hours of dedicated training or certification specific to your platform. This creates a talent lock-in for your customer. They cannot simply hire a generic developer to maintain your system; they must hire a costly, dedicated expert who specialises only in your ecosystem. The cost of hiring and training new staff to manage the competitor’s system now becomes a major factor in the purchasing decision.

• The core workflow for divorce

Avoid easy, synchronous integrations with the mission-critical tools of your largest competitors. For instance, if a competitor is deeply entrenched in the Salesforce ecosystem, do not build a single-click integration that allows customers to maintain a functional equilibrium between both systems.

Instead, build a unique, superior feature that replaces a core, deeply painful function the competitor currently handles. Force the user to choose to divorce their workflow from the competitor and migrate it entirely to your platform. This is a difficult sale, but once the customer commits to that workflow divorce, they are anchored to you. They are no longer simply adding a new tool; they are adopting a new way of working.

Also Read: The best ways to find a local partner in Southeast Asia for your company

The courage of the anti-collaborator

The Second Mover often succeeds by being more compatible with existing systems (as seen in the earlier discussion). But the category-defining winner often succeeds by enforcing incompatibility to establish a new, proprietary standard.

Think of Apple’s walled garden: the intentional friction between iOS and competing software forces users into an ecosystem where the value only increases with deeper commitment. This isn’t about arrogance; it’s about strategic defensibility.

This strategy requires courage because it means you will lose the easy customers. But you will win the structural customers who are the ones who bet their operational integrity on your platform.

If you are building something truly disruptive, you are not meant to play nicely in the sandbox. You are meant to redefine the shape of the sandbox entirely. If your competitive advantage can be undone by a single, well-documented API integration, then your product is a feature, not a company.

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While Amazon, Dell, JP Morgan, and many others have asked their employees to return to the office and adopt a full-time work culture, Southeast Asia (SEA) has been swimming against the tide, becoming a vibrant hub for “digital nomads.” 

The Philippines introduced a digital nomad visa (DNV) aiming to attract remote workers employed by foreign entities. Singapore’s flexible work arrangement mandate, along with Thailand’s Destination Thailand Visa, are decentralising the workforce and redefining the traditional workplace.  

For leaders in the C-Suite, this shift presents a challenge: we are now legally and culturally obligated to support a workforce that operates entirely out of sight.  

To thrive in this borderless landscape, we must embrace three fundamental changes in how we define and build trust.  

The device, not the login, is the new perimeter 

For decades, enterprise security has been anchored on a simple yet effective principle: the castle and moat. If an IT administrator could physically handle a laptop, configure it behind a corporate firewall, and hand it to an employee, the device was inherently trusted. This “chain of custody” ensured that IT teams could verify, secure, and trust every endpoint. It was a model built on tangible control and physical proximity. 

However, hybrid work dissolves the boundaries that the castle-and-moat approach depends on. Devices are now being shipped directly from manufacturers to homes in Manila, coworking spaces in Bangkok, or coastal cottages in Cebu.  

In this new reality, the digital perimeter can no longer be confined to networks or passwords alone. While the industry has made strides towards passwordless authentication, leveraging facial recognition and fingerprints, these advancements are not impervious. Sophisticated deepfakes and other emerging threats have demonstrated their ability to circumvent biometric systems.

Moreover, most modern attacks, such as session token theft and Adversary-in-the-Middle (AiTM) attacks, occur after a user logs in. The biometric check was valid, but if the device itself is compromised, the attacker inherits that trust. 

To effectively counter these threats, the endpoint itself must become the new perimeter. 

Security must evolve beyond simply asking “Who is the user?” Instead, it must question: Is the device compliant? Where is this access coming from? Is the user behaviour consistent with expected patterns?

These questions require rich, continuous context and not a single data point. To gather and interpret this context effectively, organisations will have to orchestrate two technologies that used to work in silos: identity management (IdP) and unified endpoint management (UEM). When integrated seamlessly, IdP tools provide robust identity verification, while UEM ensures the device posture. In this model, trust is not granted once but continuously verified until the device proves itself worthy of access. 

Moreover, adopting an endpoint management strategy ensures that security is built into the enrollment process the moment the user unboxes the hardware. This means that by the time your employee boots the device, it’s health-certified, encrypted, and identity-verified, all without IT touching a key. 

Also Read: How hybrid learning is revolutionising the landscape of education

Shadow IT isn’t the real problem, but a symptom of friction  

We’ve consistently treated unauthorised tech as one of the greatest risks —and for good reason. In the past, employees would slip in removable drives without the business’s knowledge or approval. Then the cloud arrived, opening a can of worms. And just when we thought we had a handle on things, with generative AI and large language models, we’re facing a new frontier of what we call shadow AI. 

However, this ongoing effort to eliminate Shadow IT has always been a losing one.  

When we impose clunky, multi-layered VPNs or restrictive protocols on a digital nomad working out of a co-working space, we create friction. And imposing a zero-use mandate doesn’t eliminate usage; instead, it drives the stealth usage up. Employees seek new tools to bypass security. And often, they don’t even see it as wrongdoing. Nearly 40 per cent of GenZ workers use AI to automate tasks without their manager’s approval, and one in five say they couldn’t perform their current job without AI tools. 

So clearly the answer isn’t to impose a blanket ban on new apps.  

It’s important to understand the “why” behind Shadow IT. Engage your employees, ask what they need to do their jobs effectively, listen to their preferred and recommended tools, and then work to onboard them safely. 

This approach gives two things. First, it gives you visibility into what’s being used and what shouldn’t be. If a tool poses questionable risk, step in and blacklist it. Second, it reveals gaps in your own ecosystem. Employees are often signalling what’s missing, and addressing those gaps could dramatically improve productivity while maintaining security. 

Instead of building a higher wall, build a smarter system — an orchestration layer where security is invisible. We secure the enterprise best when the employee doesn’t even know we’re doing it. Because the real risk isn’t shadow IT; it’s refusing to adapt to it. 

Also Read: AI human hybrid support: Why customers still prefer real conversations

Compliance must be continuous 

Being merely “flexible-compliant” is no longer sufficient. Across Southeast Asia, regulators are intensifying their regulatory enforcement. In 2025 alone, Thailand’s Personal Data Protection Committee (PDPC) imposed fines totalling THB 21.5 million (US$0.66 million) for violations of the Personal Data Protection Act (PDPA) — including one case involving a state agency.

In markets like Singapore and Thailand, non-compliance carries severe financial and operational consequences. Organisations face fines of up to SG$1 million (US$0.79 million) or 10 per cent of annual turnover, potential imprisonment for responsible individuals, and lasting reputational damage. Beyond regulatory penalties, businesses may be subject to lawsuits from individuals affected by data breaches, including claims for emotional distress. In many cases, authorities can mandate immediate corrective orders, forcing organisations to implement security measures within extremely tight timelines. 

Compliance, therefore, should not be viewed as a one-time milestone but as an ongoing state that must be continuously maintained. 

To operate effectively across diverse jurisdictions, organisations need a centralised management layer that acts as a digital single source of truth. One that delivers unified visibility across every endpoint, enforces consistent policies regardless of location, and enables real-time responses that surpass geographic boundaries. Integrated systems become critical here: endpoint management solutions combined with audit automation tools allow organisations to generate reports on demand while continuously monitoring the fleet’s compliance posture across regions. While resilience ensures operational continuity in a hostile environment, compliance ensures you meet the law. 

Legislative shifts in Singapore and the Philippines have essentially turned every kitchen table and living room into a branch office. The perimeter, as we knew it, no longer exists. We must accept that the network is now perpetually hostile. While we may not control the router in a Manila apartment, we can surely secure the device and identity behind it. The leaders who define the next decade will be those who understand a simple truth: Security is no longer the gatekeeper of work. It is the enabler of it. 

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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.

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