Artificial intelligence is no longer a distant promise for Southeast Asia; it is the single most consequential bet being made across the region’s venture capital landscape. In 2025, AI startup investment in Vietnam alone surged 13-fold to US$130 million, while Singapore continued to serve as the region’s capital allocator, with Temasek deploying US$34 billion globally and AI-native software emerging as the dominant investment thesis from seed to growth stage.

Across the six core markets of Singapore, Malaysia, Indonesia, the Philippines, Thailand, and Vietnam, a new generation of VC firms is reshaping how capital flows to founders building with and for artificial intelligence.

This listicle profiles 20 VC firms operating in Southeast Asia that have demonstrated a clear and documented commitment to investing in AI companies, whether through dedicated AI funds, AI-focused cohorts, or consistent backing of AI-native startups across their portfolios.

Each firm has been featured in e27 coverage and verified to be actively deploying capital in the region.

1. Vertex Ventures Southeast Asia & India

Vertex Ventures Southeast Asia & India is one of the region’s most established multi-stage VC firms, backed by Temasek Holdings. Known for its early bet on Grab, Vertex has built a pan-regional portfolio spanning Singapore, Malaysia, Indonesia, Vietnam, the Philippines, and Thailand.

Also Read: In Vietnam, the challenge isn’t talent but mindset, says Vertex’s Genping Liu

The firm operates with a founder-first philosophy, providing hands-on operational support from seed through to growth stage. In recent years, Vertex has deepened its focus on AI-native startups, enterprise software, and deep tech, reflecting the broader shift in SEA’s investment landscape toward technology companies with durable competitive moats.

Notable AI investments & activity: Portfolio includes Grab (AI-powered super-app), multiple enterprise AI and deep tech companies across SEA. Vertex Japan launched with a US$67M fund in March 2025 to connect Japanese AI startups with SEA markets.

2. Wavemaker Partners

Wavemaker Partners is a leading Singapore-based VC firm with dual presence in Southeast Asia and Los Angeles. Since 2012, the firm has backed over 200 companies and manages more than US$600 million across three fund families: Wavemaker Ventures (early-stage B2B tech), Wavemaker Impact (climate-tech), and Wavemaker Growth (bridging Series B gaps).

Wavemaker is particularly known for its thesis-driven approach to enterprise AI, deeptech, and sustainability, and has been one of the most active writers of early-stage checks in the region.

In November 2024, the firm launched a US$60 million growth fund specifically to support SEA’s most promising Series B-stage companies.

Notable AI investments & activity: Backed Carousell, Funding Societies, and multiple AI-native enterprise startups. Wavemaker Ventures led a US$4M round in DataMasque (data privacy AI) in June 2026. Wavemaker Growth Opportunities Fund targets AI-driven B2B companies at Series B.

3. Monk’s Hill Ventures

Monk’s Hill Ventures is a Singapore-based pan-Southeast Asia VC firm that focuses on early-stage technology companies. With 77 investments to its name, the firm is known for leading Series A rounds in the US$2M-US$10M range and providing deep operational support to its portfolio companies.

Monk’s Hill has consistently backed companies at the intersection of AI, deeptech, and enterprise software, and has been a co-investor alongside global tier-one funds including Sequoia and Lightspeed. The firm’s portfolio includes Glints, Lendingkart, and a growing cohort of AI-native B2B startups across the region.

Notable AI Investments & Activity: Led a US$28.8M round in Cinch (device-as-a-service, AI-powered) in April 2025. Co-invested with Iterative in Vietnamese AI wealth management startup 1Long (2024). Active in AI & deep tech, advertising & marketing, and enterprise software.

4. Golden Gate Ventures

Golden Gate Ventures is one of the region’s most prolific early-stage venture capital firms, with 128 investments across the region. Founded in Singapore, the firm has built a reputation for backing category-defining companies at the earliest stages. Golden Gate invests across a broad range of sectors with a strong emphasis on AI and deep tech, and has been an active participant in the region’s AI investment wave. The firm’s extensive network and deep market knowledge make it a preferred first institutional check for founders building AI-native companies in SEA.

Notable AI investments & activity: Portfolio includes Carousell (AI-powered marketplace), Carro (AI-driven auto platform), and multiple AI-native startups. Active investor in AI & deep tech across pre-seed, seed, and Series A stages in SEA.

5. Jungle Ventures

Jungle Ventures is a Singapore-headquartered investor with 151 investments across India and Southeast Asia. The firm has carved out a strong position as a lead investor in AI-native software companies, enterprise SaaS, and consumer technology. Jungle’s investment thesis has increasingly centred on companies that use AI to create defensible, scalable businesses in SEA’s diverse markets. In November 2024, Jungle published a widely cited report on seed investment trends in Asia, noting that median deal sizes are rising even as deal counts stabilise, a signal of increasing conviction in AI-first founders.

Also Read: Median rises, deals dip: Jungle Ventures unpacks seed investment trends in Asia

Notable AI investments & activity: Active in AI-native software, enterprise SaaS, and consumer AI. Published landmark report on seed investment trends in Asia (2024), highlighting AI as the dominant investment theme. Portfolio spans India and SEA with AI focus.

6. Quest Ventures

Quest Ventures is a Singapore-based pan-Asia VC firm with 119 investments across multiple verticals. The firm is known for its multi-sector approach and active presence in markets ranging from Singapore and Southeast Asia to Kazakhstan and the broader Asia-Pacific region. Quest has backed AI-powered startups across healthcare, robotics, IoT, and enterprise software, and has co-invested with global funds to support founders building with AI. The firm also played a key role in establishing a startup and innovation ecosystem partnership with the National Development Commission of the Philippines in 2023.

Notable AI investments & activity: Backed Vulcan Augmetics (AI-powered robotic prosthetics, 2023), Dolbomdream (AI-integrated IoT hugging vest, 2024), and multiple AI-native startups. Active in AI & deep tech, advertising & marketing, and enterprise software.

7. Antler

Antler is a global early-stage VC firm headquartered in Singapore with one of the most active AI investment programmes in Southeast Asia. Through its AI Disrupt programme, launched in March 2025, Antler specifically targets founders building AI-native companies with early commercial traction.

In the second half of 2025, Antler invested US$7.4 million into SEA startups, with US$2.8 million earmarked specifically for AI ventures. In December 2025, the firm deployed US$5.6 million across 14 AI startups in a single cohort. Antler’s portfolio spans over 1,000 investments across six continents, with a particularly strong pipeline in Malaysia, Singapore, Indonesia, and Vietnam.

Notable AI investments & activity: US$5.6M invested in 14 AI startups in one cohort (Dec 2025). US$2.8M for AI ventures in H1 2025. Backed Zeya Health (AI healthcare admin, Singapore), M3TRIQ (AI biotech, Malaysia), NCSpeech (AI fintech, Malaysia), Obiguard (AI governance, Malaysia), Otonoco AI (GenAI compliance, Malaysia).

8. Iterative

Iterative is a Singapore-based seed-stage VC firm that closed its US$55 million Fund II in November 2022, doubling down on early-stage founders across Southeast Asia and South Asia. The firm operates with a strong conviction in AI-native companies and has been a consistent co-investor alongside Monk’s Hill Ventures, Accelerating Asia, and other regional funds.

Iterative’s portfolio includes companies building AI-powered financial services, B2B marketplaces, and enterprise software tools. The firm is particularly active in Vietnam, Indonesia, Bangladesh, and Singapore, and has backed multiple companies that have gone on to raise Series A rounds from top-tier global investors.

Notable AI investments & activity: Co-invested with Monk’s Hill in 1Long (AI wealth management, Vietnam, 2024). Co-invested with Accelerating Asia in PriyoShop (AI-powered B2B retail marketplace, 2024). Backed Opilot (AI copilot startup, Singapore, 2024). US$55M Fund II closed to double down on seed-stage AI founders (2022).

9. Singtel Innov8

Singtel Innov8 is the corporate venture capital arm of Singtel, Southeast Asia’s largest telecommunications group. With a mandate to invest in startups that complement and extend Singtel’s core business, Innov8 has backed companies across AI, cybersecurity, cloud computing, IoT, and digital media. In August 2022, Singtel Innov8 received an additional US$100 million to back startups in Southeast Asia, the US, China, Israel, and Australia. The fund’s AI investments span enterprise AI infrastructure, AI-powered connectivity solutions, and AI-native applications that leverage Singtel’s regional network and enterprise customer base.

Notable AI investments & activity: Joined Airalo’s US$60M Series B round (AI-powered eSIM platform, 2023). Backed Handprint (AI-powered impact measurement, 2022). US$100M additional capital deployed across AI, cybersecurity, and cloud startups globally. Active in AI & deep tech, advertising & marketing, and enterprise software.

10. Tin Men Capital

Tin Men Capital is a Singapore-based VC firm dedicated to backing B2B tech founders across Southeast Asia through capital, strategic connections, and operational resources. The firm focuses on Series A and Series B investments in B2B technology and marketplace startups, with a growing emphasis on AI-driven solutions for traditional industries.

In June 2026, Tin Men Capital published a detailed investment thesis on where it sees the greatest opportunities for AI-powered operational improvement in sectors such as logistics, manufacturing, and professional services, underscoring the firm’s conviction that AI will transform Southeast Asia’s most entrenched industries.

Also Read: Solving operational problems in traditional industries: Where Tin Men Capital sees opportunities for impact

Notable AI investments & activity: Published investment thesis on AI-powered operational improvement in traditional industries (June 2026). Active in B2B AI, marketplace AI, and enterprise software. Focused on Series A and Series B AI-native B2B companies across SEA.

11. Kadan Capital

Kadan Capital is a Singapore-based early-stage venture capital firm founded by Rei Murakami, daughter of renowned Japanese activist investor Yoshiaki Murakami. Launched in September 2024, Kadan Capital has quickly established itself as an AI-native VC firm with a focus on backing founders building AI-powered companies across Southeast Asia and Japan. The firm’s investment philosophy centres on identifying AI-first companies that can create durable competitive advantages in SEA’s fragmented markets. Kadan Capital has been vocal about the structural challenges facing SEA’s venture ecosystem, particularly the lack of exit opportunities, and positions itself as a long-term partner for AI founders navigating these headwinds.

Notable AI investments & activity: AI-native VC firm with explicit focus on AI-powered startups in SEA and Japan. Rei Murakami commented on the structural challenges for AI exits in SEA (Feb 2025). Active in early-stage AI investments across Singapore and the broader SEA region.

12. East Ventures

East Ventures is one of Southeast Asia’s most prolific venture capital firms, with over 644 investments since its founding in 2009. Headquartered in Indonesia and Singapore, the firm operates across the full investment spectrum from pre-seed to growth stage, and has backed some of the region’s most iconic companies including Tokopedia, Traveloka, and Ruangguru.

In January 2025, East Ventures predicted a ‘significant surge’ in AI-first startups across SEA, and in February 2025, the firm secured the first close of a US$100 million cross-border fund with SV Investment. East Ventures’s annual Digital Competitiveness Index for Indonesia is one of the most widely cited reports on the country’s digital economy and AI adoption landscape.

Notable AI investments & activity: Backed Videotto (AI-native video editing, Singapore, 2025). Predicted ‘significant surge’ in AI-first startups in SEA (Jan 2025). US$100M cross-border fund with SV Investment (Feb 2025). Annual Digital Competitiveness Index tracks AI adoption across Indonesia. Launched IndoBuild AI Demo Day in Jakarta (Mar 2025).

13. AC Ventures

AC Ventures is a leading Indonesia-based VC investor that has established itself as one of the most active investors in the country’s tech ecosystem. The firm focuses on fintech, AI-native software, consumer technology, and mobility, and has backed companies that have gone on to become category leaders in Indonesia and across Southeast Asia. AC Ventures is known for its deep operational expertise in Indonesia’s market dynamics and its ability to support founders navigating the country’s complex regulatory and consumer landscape. The firm has been particularly active in tracking and investing in AI-powered mobility and fintech companies, and has published widely read analysis on consolidation trends in SEA’s mobility sector.

Notable AI investments & activity: Portfolio includes Beam Mobility and ION Mobility (AI-powered micro-mobility). Published analysis on AI-driven consolidation in SEA mobility sector (Jul 2025). Active in AI-native software, fintech AI, and consumer AI across Indonesia and SEA.

14. Alpha JWC Ventures

Alpha JWC Ventures is one of a prominent venture capital firm, with US$700 million in assets under management and a decade of investing in Indonesia and the broader region. Founded in 2015, the firm has built a portfolio of over 60 companies across AI, fintech, consumer technology, and healthcare, and has backed multiple unicorns and category leaders. Alpha JWC’s investment thesis centres on the ‘Indonesia+ angle’, backing companies that can win in Indonesia’s large, complex market and then scale across SEA. The firm has been increasingly active in AI investments, backing companies that use AI to transform financial services, healthcare, and enterprise operations.

Notable AI investments & activity: Backed Honest (AI-powered credit card issuer, US$100M raised, 2025). Launched SpeakUp (AI-powered whistleblowing platform for startups, 2025). Led pre-Series A round for Bumame (AI-powered healthtech, 2025). US$700M AUM with growing AI portfolio across Indonesia and SEA.

15. Gobi Partners

Gobi is an Asia-focused venture capital firm headquartered in Kuala Lumpur and Hong Kong, with US$1.6 billion in assets under management. Founded in 2002, Gobi has built one of the most geographically diverse portfolios in Asia, spanning Malaysia, Singapore, Indonesia, the Philippines, Pakistan, and Japan. The firm has made AI, robotics, and biotech a central pillar of its investment strategy, marking its first healthcare AI investment in Southeast Asia in 2024.

In July 2026, Gobi entered into a strategic collaboration with NTT to connect Japan’s tech sector with SEA startups, and in November 2025, the firm expanded into Japan as a Global Network Partner. Gobi also backed SkyeChip, a Malaysian AI chip design startup, in early 2025.

Notable AI investments & activity: Invested in SkyeChip (AI chip design, Malaysia, 2025). First healthcare AI investment in SEA (2024). Strategic collaboration with NTT for Japan-SEA AI co-investments (Jul 2026). AI, robotics, and biotech are core investment pillars. US$1.6B AUM deployed across Asia with growing AI focus.

16. Insignia Ventures Partners

Insignia is a leading growth-stage venture capital firm, with over US$516 million raised across its funds. Founded in 2017, the firm has invested in over 90 companies spanning fintech, e-commerce, healthcare, and SaaS, and manages capital on behalf of premier institutional investors including sovereign wealth funds, university endowments, and family offices from Asia, Europe, and North America. Insignia’s founder-first approach and deep regional network have made it a preferred partner for AI-native founders seeking growth-stage capital in Southeast Asia. The firm has been bullish on AI, web3, climate tech, and healthcare as the defining investment themes of the decade.

Notable AI investments & activity: Backed Carro (AI-powered auto platform), Ajaib (AI-driven investment platform), and Payfazz (AI-powered financial services). Raised US$516M with explicit bullishness on AI, web3, climate tech, and healthcare (2022). Backed Konvy (AI-powered beauty e-commerce, Thailand, 2022).

17. Kickstart Ventures

Kickstart Ventures is the Philippines’s largest technology venture capital fund, connecting global innovation with Southeast Asia’s leading conglomerates and the markets they serve. The firm invests globally in early-to-growth-stage tech startups, with a particular focus on companies that can deliver strategic value and financial returns to its corporate limited partners.

In 2026, Kickstart published a widely read analysis on how AI is recalibrating venture capital in Southeast Asia, positioning the firm as a thought leader on the intersection of AI and VC in the Philippines and the broader region. Kickstart has been a consistent presence at Echelon Philippines, where it has shared its investment thesis on AI-driven transformation.

Notable AI investments & activity: Published ‘Recalibrating Venture Capital in Southeast Asia with AI’ (Apr 2026). Presented AI investment thesis at Echelon Philippines 2024. Philippines’ largest tech VC fund with growing AI portfolio. Connects global AI innovation with Philippine conglomerates and markets.

18. Intudo Ventures

Intudo Ventures is a firm with a distinctive ‘Indonesia-only’ investment mandate, backed by the conviction that Indonesia’s US$1.3 trillion economy and 270 million population represent one of the world’s most compelling standalone investment opportunities.

In November 2024, Intudo closed US$125 million across two funds focused on Indonesia’s middle-class and sustainable industry. The firm has been vocal about why it believes treating Southeast Asia as a single cohesive market is a fallacy, and has built a portfolio of companies that are deeply embedded in Indonesia’s consumer and enterprise landscape. Intudo’s AI investments focus on companies using artificial intelligence to serve Indonesia’s rapidly growing middle class.

Also Read: Why ‘Indonesia-only’ Intudo Ventures believes SEA as one cohesive market is a fallacy

Notable AI investments & activity: US$125M across 2 funds focused on Indonesia’s middle-class and sustainable industry (Nov 2024). Backed Banyu (AI-powered seaweed value chain, Jan 2025). Backed Coldspace (AI-powered cold chain logistics, 2023). Active in AI-driven consumer and enterprise solutions for Indonesia’s middle class.

19. Do Ventures

Do Ventures is Vietnam’s leading homegrown venture capital firm, with a mission to support tech startup companies in Vietnam and Southeast Asia. The firm provides finance, mentorship, and strategic connections to founders building technology companies that address the needs of Vietnam’s rapidly growing digital economy. Do Ventures has been at the forefront of tracking Vietnam’s AI investment surge, the country’s AI startup funding rose 13-fold to US$130 million in 2025, according to Do Ventures’ own research. The firm has backed companies across fintech, enterprise software, and AI-native applications, and has positioned itself as the go-to early-stage partner for Vietnamese founders building with AI.

Notable AI investments & activity: Published Vietnam Innovation and Private Capital Report 2025, documenting AI startup investment surge from US$10M (2023) to US$130M (2025), a 13-fold increase. Backed FlexOS (AI-powered hybrid work platform, 2022). Active in AI-native fintech, enterprise software, and consumer AI in Vietnam and SEA.

20. 500 Global

500 Global (formerly 500 Startups) is one of the world’s most active early-stage venture capital firms, with a significant regional presence in Southeast Asia anchored in Singapore. The firm has supported over 5,000 founders across more than 2,600 companies in 80 countries, including 51 unicorns. In September 2023, 500 Global raised US$143 million for early-stage and growth vehicles in SEA. In June 2024, the firm doubled down on AI, announcing a strategy to back startups building AI applications for specific industry verticals, reflecting a deliberate shift from horizontal AI tools to vertical AI solutions. 500 Global has been a consistent presence at Echelon Philippines and other regional conferences, where it has shared its AI investment thesis.

Notable AI investments & activity: Doubled down on AI apps for specific industry verticals (Jun 2024). US$143M SEA fund raised (Sep 2023). Backed NexMind (AI-powered multilingual digital marketing, 2023). Backed Canva (AI-powered design platform), Grab, and Udemy. Portfolio includes 51 unicorns with growing AI cohort.

The post Inside SEA’s AI gold rush: The 20 investors writing the biggest cheques appeared first on e27.

Malaysia’s public-sector pension fund, Kumpulan Wang Persaraan (Diperbadankan), or KWAP, has moved to contain concerns over its exposure to eFishery, saying its total investment in the troubled Indonesian aquaculture startup amounted to about US$38.4 million and represented a 2.51 per cent stake in the company.

The clarification comes after media scrutiny of eFishery, once one of Southeast Asia’s most closely watched agritech startups, following revelations of financial manipulation and misrepresentation in its accounts.

Also Read: “There’s no excuse”: Aqua-Spark calls out eFishery’s deception

eFishery co-founder and former CEO Gibran Huzaifah was recently sentenced by the Bandung District Court to nine years in prison after being convicted of embezzlement and money laundering.

The fallout is significant not only because eFishery was a flagship Indonesian startup but also because its cap table included several institutional investors. KWAP said it was a minority shareholder, while most of the company’s shares were held by other investors, including major global institutions that were also affected by the misconduct.

A pension fund caught in a startup blow-up

KWAP manages Malaysia’s public-sector retirement fund and invests across equities, fixed income, money market instruments, and private-market assets. The fund said that, after irregularities at eFishery were discovered, it conducted an internal investigation and reviewed its investment processes, post-investment monitoring arrangements, and the information available to it during the investment period.

“Appropriate follow-up actions have been taken in accordance with KWAP’s internal governance and accountability framework,” the fund said, adding that it is pursuing all available avenues to maximise recovery of its investment.

KWAP did not specify how much of the US$38.4 million investment it expects to recover, nor did it name the other affected institutional investors. It also did not disclose whether any legal action has been initiated by the fund.

The size of the exposure appears modest relative to KWAP’s overall balance sheet. Based on unaudited results for the financial year ended 31 December 2025, the fund recorded gross investment income of about US$1.96 billion and total funds under management of roughly US$45.9 billion. Still, the eFishery case raises uncomfortable questions for institutional investors that increased allocations to private markets during the region’s low-interest-rate venture boom.

eFishery’s fall from startup darling status

Founded in 2013, eFishery built its business around smart feeding devices for fish and shrimp farmers, alongside financing and marketplace services. It was part of a broader wave of Southeast Asian agritech startups seeking to formalise fragmented supply chains, digitise smallholder farmers and connect producers with credit and buyers.

The company gained prominence because aquaculture is a large and strategically important sector in Indonesia, the world’s largest archipelago and one of the biggest fish-producing nations globally. Indonesia’s fishery and aquaculture economy supports millions of livelihoods, but the industry has long been dogged by inefficiencies, opaque middlemen networks, limited working capital, disease risks and thin farmer margins.

That made eFishery’s pitch attractive: data-led feeding systems, farmer financing, procurement and distribution could, in theory, improve yields and reduce waste. For investors, the company offered exposure to a sector sitting at the intersection of food security, fintech, climate resilience and rural digitisation.

Also Read: eFishery founder held by Indonesian police over alleged embezzlement

The company’s collapse in credibility is therefore a blow beyond one balance sheet. Southeast Asia’s agritech sector has already had to contend with a tougher funding environment since 2022, as investors moved away from growth-at-all-costs models and demanded clearer paths to profitability. A fraud case at a high-profile startup will almost certainly sharpen scrutiny of revenue quality, customer verification, loan-book exposure and related-party transactions across the sector.

Regional peers face a different investor climate

eFishery operated in a market with several regional peers trying to solve different parts of the aquaculture and fisheries stack. In Indonesia, JALA Tech focuses on shrimp farm management and monitoring tools, helping farmers track water quality and production data. Delos has built a technology and operational platform for shrimp farming, including farm design and productivity improvement. Aruna, another Indonesian startup, works on fisheries commerce by connecting fishers with domestic and export markets. FishLog has focused on cold-chain and fisheries distribution infrastructure.

The eFishery affair may benefit more conservative operators if investors begin rewarding slower, verifiable growth over aggressive expansion. But it may also make fundraising harder for the entire category, particularly for startups whose business models mix hardware deployment, farmer credit and marketplace revenue, areas where field-level verification can be expensive and messy.

KWAP tightens private-market approach

In its statement, KWAP said it has strengthened its private-market investment approach, including greater portfolio diversification, investing alongside experienced fund managers and strategic partners, enhanced post-investment monitoring, and closer oversight of material developments involving portfolio companies.

Those measures reflect a broader reassessment among Southeast Asian limited partners, sovereign funds and pension funds after the exuberant funding cycle of 2020 to 2022. During that period, global capital flooded into the region’s startups, pushing valuations higher across fintech, e-commerce, logistics, Web3 and agritech. As liquidity dried up, weak governance, inflated metrics and fragile unit economics became harder to hide.

For pension funds, the challenge is especially sensitive. Private-market investments can improve long-term returns and diversify portfolios, but failures involving fraud or misrepresentation carry reputational and political consequences. The ultimate beneficiaries are retirees, not venture capital partners.

Also Read: 10 years behind bars? eFishery case forces startup reality check

KWAP stressed that its broader fund remains diversified across asset classes, sectors and geographies, and said it remains committed to managing the fund prudently and transparently in line with its statutory mandate to help the Malaysian government meet pension obligations to public-sector retirees.

The eFishery case is unlikely to end with one clarification. For Southeast Asia’s startup ecosystem, it is another reminder that governance is not back-office plumbing. In private markets, where valuations often depend on company-reported numbers and investor trust, governance can be the difference between a breakout story and a costly write-off.

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Japanese financial services group SBI Holdings has acquired a majority stake in Singapore-based crypto exchange Coinhako, turning the company into a consolidated subsidiary after receiving approval from the market regulator Monetary Authority of Singapore (MAS).

The transaction, completed on July 16 through SBI Ventures Asset, involves both a capital injection into Holdbuild, Coinhako’s parent company, and a share purchase from existing shareholders.

Financial terms were not disclosed.

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

The deal gives SBI a regulated foothold in one of Asia’s most closely watched digital asset markets at a time when crypto exchanges, stablecoin issuers, and tokenisation platforms are moving from retail-led speculation towards institution-facing infrastructure. On the other hand, Coinhako gets a deep-pocketed parent with a large financial services network in Japan, a market where SBI has been one of the most aggressive incumbents in crypto, blockchain, and digital securities.

Founded in 2014 by Yusho Liu and Gerry Eng, Coinhako operates mainly through Hako Technology, which holds a Major Payment Institution licence from MAS, and Alpha Hako, a crypto asset service provider registered with the British Virgin Islands Financial Services Commission.

Coinhako is among the island nation’s earlier consumer-facing digital asset platforms and has survived multiple industry cycles, including the post-FTX regulatory tightening that pushed many exchanges out of the market.

A Singapore bet, not just a Coinhako deal

For SBI, the acquisition is less about buying a standalone exchange and more about securing a regulated bridge into Southeast Asia.

The Japanese group said Singapore is a key hub in its digital asset strategy, particularly as it works to build what it describes as a digital asset economic zone focused on Asia-Pacific. SBI has also been working with Startale on on-chain financial infrastructure, including JPYSC, billed by the company as Japan’s first trust-type yen-denominated stablecoin.

SBI Chairman, President and CEO Yoshitaka Kitao said the group aims to create a “global corridor for digital assets” by connecting exchanges across markets. Singapore, he added, plays a central role because of its regulatory position.

That framing makes sense. Singapore has spent the past few years trying to separate regulated digital asset activity from the excesses of the last crypto bull run. MAS has tightened retail access, introduced stronger requirements around custody and customer asset segregation, and pushed licensed players towards compliance-heavy operations. At the same time, it has encouraged institutional experimentation in tokenisation, stablecoins and cross-border settlement through projects such as Project Guardian.

Also Read: The future of stablecoin payments will be decided in emerging markets

This has created a market where the cost of compliance is high, but the regulatory signal is clearer than in much of the region. For a Japanese financial group looking to expand digital asset rails outside its home market, acquiring a licensed Singapore operator is faster than building from scratch.

Coinhako gets scale after a brutal market cycle

For Coinhako, SBI’s backing comes after a period in which many regional crypto firms have struggled to maintain momentum.

Southeast Asia was one of the most active crypto retail markets during the last bull cycle, driven by young populations, high mobile penetration and underdeveloped investment infrastructure in several countries. But the sector has since split sharply. Regulated platforms in Singapore, Indonesia, Thailand, and the Philippines have continued to operate under tighter rules, while weaker or offshore-led players have faded, frozen withdrawals or been forced into restructuring.

Coinhako now competes in Singapore against global and regional names including Coinbase, Crypto.com, Independent Reserve, Gemini, and OKX — all of which have pursued regulatory approval in the city-state to varying degrees. In the wider region, competition includes Indonesia’s Indodax and Tokocrypto, the latter backed by Binance; Coins.ph and PDAX in the Philippines; and Bitkub in Thailand. Several of these players have stronger domestic retail recognition in their home markets but lack the same Singapore regulatory positioning.

The exchange’s challenge has been familiar: surviving long enough to become relevant to the next phase of the market. Retail trading fees alone are no longer a compelling growth story. The bigger opportunity now sits around compliant custody, tokenised real-world assets, stablecoin settlement, cross-border payment corridors and institutional digital asset access.

“Joining SBI Group is the natural next chapter for Coinhako,” said Liu, Coinhako’s co-founder and CEO. He said the platform had spent the past decade building in “one of the world’s most progressive regulatory environments” and would use SBI’s scale to deliver new digital financial services across the region.

Stablecoins and tokenisation are the real prize

The most important clue in the announcement is not the acquisition itself, but SBI’s repeated reference to JPYSC and cross-border digital finance.

Stablecoins have moved from a crypto trading utility to one of the most closely watched pieces of payments infrastructure in Asia. Dollar-linked stablecoins dominate global usage, but regulators and banks across the region are exploring domestic currency-backed tokens for settlement, treasury management and tokenised asset transactions.

Singapore has already established a regulatory framework for single-currency stablecoins, initially covering tokens pegged to the Singapore dollar or G10 currencies issued in Singapore. Japan, meanwhile, has taken a more bank-and-trust-led route, creating a path for regulated yen-denominated stablecoins. SBI’s attempt to connect these developments through Singapore could position Coinhako as more than a retail exchange.

Also Read: Stablecoins surge in Southeast Asia 2026: A real shift or just a bridge to CBDCs?

The same logic applies to tokenisation. Financial institutions in Singapore, Japan and Hong Kong have been testing tokenised bonds, funds, deposits and foreign exchange settlement. The problem is no longer whether assets can be tokenised; it is whether distribution, compliance, liquidity and settlement can be stitched together across jurisdictions.

A licensed Singapore platform with an existing customer base and operational experience may give SBI a local testbed for these services. It could also help the group connect Japanese digital finance infrastructure with Southeast Asian users and institutions, though that ambition will depend heavily on regulatory approvals in each market.

Japan-Singapore ties add political timing

The announcement also lands during the 60th anniversary year of diplomatic relations between Japan and Singapore. SBI said it plans to hold its first overseas branch managers’ meeting in Singapore this summer, signalling that the city-state is becoming more than a regional office for the group.

The broader backdrop is a growing convergence between Japanese capital and Southeast Asian fintech infrastructure. Japanese banks, trading houses, and financial groups have been active investors in regional payments, digital lending and wealth platforms. SBI’s Coinhako move extends that pattern into regulated digital assets.

Still, execution will be difficult. Crypto regulation in Southeast Asia remains fragmented. Singapore is strict but clear; Indonesia has shifted oversight from commodities regulators towards financial authorities; Thailand has allowed licensed exchanges but imposed advertising and product restrictions; the Philippines remains active but cautious. A “corridor” strategy will require SBI and Coinhako to navigate each of these regimes rather than assume a single regional playbook.

The acquisition gives SBI a credible base in Singapore and gives Coinhako more institutional muscle. But the deal’s significance will be measured by what comes next: whether the pair can move beyond exchange trading into stablecoin settlement, tokenised assets and cross-border financial rails that regulators will actually permit. For now, SBI has bought itself a seat at Singapore’s digital asset table. The harder task is turning that seat into regional leverage.

The post SBI buys majority stake in Coinhako to deepen Singapore digital asset push appeared first on e27.

For two decades, winning search meant one thing: rank on page one. That game hasn’t disappeared, but it has quietly become the smallest of three games being played for your customers’ attention. Ask Google a question today, and it increasingly answers before the first blue link, inside an AI Overview. Ask ChatGPT, Gemini, or Perplexity, and there is no page one at all — just an answer, with a handful of brands woven into it. Either yours is one of them, or the conversation moves on without you.

That is why marketers now juggle three acronyms instead of one: SEO, AEO, and GEO. They are not competing philosophies. There are three layers of the same new reality, and in 2026, a business serious about being discovered needs all of them.

Three games, one customer

• SEO — Search Engine Optimisation — is the discipline we all know: making your website visible in traditional engines like Google and Bing through keyword targeting, backlinks, technical health (speed, mobile experience, crawlability), and content people actually find useful. Its purpose has always been simple: bring visitors to your site.
• AEO — Answer Engine Optimisation — is about winning the moment when a single answer gets lifted out and served directly: a featured snippet, a voice assistant’s reply, a line in Google’s AI Overview. Here, ranking a page matters less than structuring one — concise answers near the top, clear headings, and demonstrated authority on the topic, so the machine can extract you cleanly.
• GEO — Generative Engine Optimisation — which you may also see labelled AI SEO or LLM optimisation- is the youngest of the three disciplines and, increasingly, the decisive one. This is the work of making sure generative tools — ChatGPT, Gemini, Perplexity, Claude — decide you are worth naming when they answer a question: citing you, quoting you, recommending you. Unlike AEO, there is no single result to win. What matters is whether the places these models learn from — your structured data, review platforms, directories, forums, knowledge bases — tell one consistent, accurate story about who you are. Done well, your brand lives inside the answer even when no one ever reaches your website.

A useful shorthand: SEO is about keywords and clicks, AEO is about context and the answer box, and GEO is about entities and the mention.

Also Read: AI and the crisis of recognition: Do we still see the human behind the words?

Why 2026 is the tipping point

Three shifts make this urgent rather than theoretical. Zero-click behaviour is becoming the default — users take the answer and leave, never reaching a website even when your content produced that answer. AI platforms concentrate attention on a handful of sources they trust per query, which turns citation into a winner-take-all contest. And queries themselves have changed shape: people no longer type “website design Singapore” — they ask, “which company builds affordable websites for a small F&B business in Singapore?” Engines reward content that speaks the way people now ask.

Southeast Asia feels this earlier and harder than most regions. Its consumers are mobile-first and among the fastest adopters of AI assistants, and Singapore in particular is a brutally competitive, English-language market where a single AI answer can settle a shortlist. There is a quieter risk too: regional brands are thinly represented in the sources these models learn from. If you are not deliberately feeding the engines accurate, consistent signals, they will describe your category through your competitors — or describe you wrongly.

The moment it bites

Picture the buyer you most want. An operations director at a mid-sized Singapore company opens an AI assistant and types: “Best providers for this in Singapore — mid-sized team, tight budget. Give me three options.” Ten seconds later, she has three names, each with a tidy justification. Yours is not among them.

Nothing in your dashboard will ever record this. There was no impression lost, no ranking to recover, no analytics trail. In the old game, you could at least watch yourself losing from page two. In this one, invisibility is silent.

The content flood — and why creativity becomes the moat

Faced with all this, the reflexive strategy is volume: use LLMs to generate hundreds of optimised articles and carpet-bomb every question in your category. Here is the uncomfortable arithmetic — everyone can now do that. When every competitor can generate a thousand plausible “ultimate guides” overnight, generated volume is worth precisely nothing. The web is filling with synthetic sameness, and both search engines and AI models are getting sharper at collapsing near-duplicates and discounting content that adds no new information. A model deciding what to cite behaves, in this one respect, like a tired editor: it keeps what is distinctive and skips the rest.

So the differentiators flip. What earns citations is what generic generation cannot produce: first-hand data nobody else has, a point of view sharp enough to be quotable, and creative angles into whitespace no competitor occupies. Across the markets, the pattern is consistent — categories converge on the same three messages, and the brand that finds the untouched angle is the one that gets remembered, by humans and machines alike. You cannot prompt your way into being the answer. You have to say something worth answering with.

Also Read: Bitcoin at US$64,660: The hidden on-chain signal that suggests we’re still in a bear market

None of this replaces the fundamentals, which are quickly summarised: answer the actual question in your first sixty words; structure pages with clear headings, FAQs, and schema markup; keep your brand’s facts (what you do, where you operate) identical everywhere they appear; build presence on the third-party sources AI reads — reviews, directories, industry publications; and start measuring mentions and citations, not just clicks.

Creativity with evidence, not instead of it

The honest objection is that originality is expensive. Research, ideation, and testing take weeks that most teams don’t have. It’s a challenge we’ve encountered firsthand at SOMIN, where we’ve explored how AI can help teams analyse competitor and audience data, identify gaps in a category, and evaluate creative concepts before significant resources are committed.

In our experience, this has helped reduce research and ideation time for some organisations, giving teams more space to focus on creative thinking rather than repetitive groundwork. The machine does the reading. The humans get their time back to do the daring.

The future belongs to brands worth citing

AEO and GEO are not the death of SEO — they stand on its shoulders, because AI systems still select and cite from well-indexed, well-structured, credible pages. The strategy for 2026 is integration: SEO for discoverability, AEO for the answer, GEO for the recommendation, and creativity as the thread that makes any of it worth surfacing.

So ask yourself the question your customers are already asking their assistants: when an AI describes your category next year, will it have anything distinctive to say about you — or will it quote whoever was brave enough to be original?

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

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

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Singapore is often described as a small market. That is true in population terms, but misleading in almost every other way.

It is better understood as a compressed market.

Customers, investors, regulators, partners, talent, and competitors operate unusually close to one another. Information moves quickly. So does reputation.

In larger markets, a weak proposition may survive for years across separate cities or customer segments. In Singapore, the feedback tends to arrive much sooner.

This can make the market feel unforgiving. For founders who know how to listen, it is one of Singapore’s greatest advantages.

Density changes the game

Singapore’s startup ecosystem brings public institutions, multinational corporations, investors, universities, accelerators, and founders together within a remarkably small geography.

The country ranks second globally and first in Asia-Pacific in StartupBlink’s 2026 Innovators Business Environment Index. According to the Singapore Economic Development Board, 80 of the world’s top 100 technology companies have a presence here, with many using Singapore as a regional or global base.

For founders, this density reduces the distance between an idea and the people capable of testing, funding, regulating, or buying it. But proximity also raises expectations.

A poor customer experience does not remain isolated for long. An investor may know the company that rejected a pilot. A corporate buyer may speak to a former employee. A promising introduction may lead to three more, while a poorly handled one can quietly close several doors.

In Singapore, reputation is not simply a branding exercise; it’s more like operating infrastructure.

Also Read: Inside Singapore’s startup boom: The 21 firms investors can’t stop funding

Feedback arrives early

After working with thousands of startups and SMEs, I have noticed that founders sometimes misread Singapore’s speed of feedback.

When customers hesitate, they conclude that the market is too conservative. When a pilot does not convert, they assume local companies are too cautious. When growth slows, they point to the size of the domestic market.

Sometimes those explanations are valid. Often, the market is revealing something useful.

The proposition may not be specific enough. The proof may not be strong enough. The founder may be speaking to an interested user rather than the person who controls the budget. The product may solve a real problem without solving one urgent enough to earn funding.

Singapore compresses the time required for these weaknesses to surface. A founder who discovers a flawed assumption in three months is in a stronger position than one who spends two years scaling it.

Validation is not scale

The mistake is expecting Singapore to play every role.

It is an effective market for validation, partnerships, credibility, capital, and regional coordination. For many companies, however, it cannot provide the customer volume available in Indonesia, Vietnam, the Philippines, or Thailand.

Southeast Asia’s digital economy surpassed US$300 billion in gross merchandise value in 2025, according to the latest e-Conomy SEA report. That opportunity is spread across markets with different languages, regulations, price sensitivities, payment habits, and expectations of trust.

Singapore can provide a strong base. It cannot remove the need to localise.

The Singapore Business Federation’s 2025 internationalisation survey found that 84 per cent of internationalised Singapore businesses operate in ASEAN. Among businesses planning further expansion, 65 per cent intend to grow within the region.

This is an important distinction: Singapore may be where a company proves that its model works, but regional markets determine whether that model can adapt.

Assumptions do not travel well

APAC expansion rarely fails because a product suddenly stops functioning. It fails because assumptions travel further than evidence.

A company enters a new market with the same positioning, pricing, sales process, and customer experience. The team expects the formula that worked in Singapore to transfer intact. Then conversion slows.

Also Read: Singapore and Taiwan have a new window of opportunity, but will they seize it?

In one market, customers may expect to speak with someone before buying software. In another, the right local partner may matter more than a polished digital funnel. Procurement cycles, payment terms, hierarchy, and perceptions of foreign brands can vary significantly.

Localisation, therefore, is not simply translation; it’s more like the recalibration of trust.

Singapore helps by exposing founders to regional buyers, talent, investors, and partners early. But proximity to Southeast Asia should not be confused with understanding it.

Use compression deliberately

Founders can use Singapore’s compressed environment in four practical ways:

• Test the commercial argument. A successful pilot means little if no one will own the budget after it ends.
• Treat reputation as infrastructure. Delivery quality, communication, and follow-through compound quickly in a closely connected ecosystem.
• Design for regional expansion. Separate the features needed in Singapore from the languages, payment methods, onboarding models, and partnerships required elsewhere.
• Use rejection as market intelligence. Repeated objections are rarely random. They reveal problems with positioning, timing, trust, or value.

Small can be powerful

Singapore’s limited domestic market is a constraint. But constraints can improve companies when they force clarity early.

Founders here must think regionally, demonstrate credibility, and learn quickly. They operate in a market where feedback travels fast, and weak assumptions have fewer places to hide.

That does not make Singapore easy. It makes Singapore efficient.

The founders who benefit most are not those who treat the country as a smaller version of a larger market. They recognise it as a concentrated environment in which ideas, reputations, and opportunities move unusually quickly.

Singapore is not merely a market to conquer. Think of it as a pressure test.

Used well, that pressure can produce companies ready for much larger ground.

—

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

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

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Image credit: Zaonar Saizainalin via Pexels.

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For years, the travel industry focused on removing friction from the booking experience. And in many ways, it succeeded.

Flights, hotels, airport transfers, restaurant reservations, and activities can now be researched, compared, and confirmed in minutes. What once required printed itineraries, phone calls, or multiple agents now happens across a handful of tabs and apps. Travel planning has become faster, more intuitive, and more personalised than ever before. Global online travel bookings have now crossed the US$1 trillion mark, and the digital travel market is expected to grow to between US$1.4 trillion and US$1.6 trillion by the early 2030s.

This rapid growth reflects just how seamless the booking experience has become. But it has also created a new assumption: that once a trip is booked, the rest of the experience will simply work.

That is no longer true.

The real bottleneck in modern travel is not booking. It stays operational once the trip is in motion.

Today’s traveller is expected to function in real time. They are not just moving between destinations. They are navigating airports through app alerts, coordinating arrivals through messaging platforms, finding hotels through maps, adjusting plans through airline notifications, unlocking rides through transport apps, and paying digitally in unfamiliar places. Travel has become increasingly real-time, and that experience depends on being connected. According to IATA, 78 per cent of passengers now expect to use their smartphones for booking, payment, and navigating the airport experience.

This is a major shift in where travel friction actually lives.

The industry has spent years refining the front end of the journey. Searching, comparing, and buying are smoother than they used to be. But once the traveller lands, boards, reroutes, waits, or changes course, the pressure moves elsewhere. It moves to access. Can the map load? Can the message go through? Can the airline app refresh? Can the traveller receive the gate change, pull up the hotel address, reach a driver, or access the payment tool they rely on?

Also Read: Corporate travel in Southeast Asia was never broken, it was never built

Even short gaps in connectivity now create outsized disruption because so much of the travel experience is built on responsive, app-based behaviour. A missed update is no longer a minor inconvenience. It can delay a pickup, complicate a check-in, affect coordination with friends or family, or create confusion in moments when travellers need clarity most. This reliance is reflected in the rapid growth of travel apps, with global travel app revenue surpassing US$1.2 billion in recent years as travellers increasingly depend on mobile tools throughout their journeys.

That is why connectivity should no longer be treated as a travel add-on. It has become part of travel infrastructure. 

This is where technologies like eSIM are reshaping expectations. By enabling travellers to activate mobile connectivity instantly without relying on physical SIM cards, eSIM solutions reduce one of the most common points of friction in modern travel. Instead of searching for local SIM vendors or relying on inconsistent public Wi-Fi, travellers can stay connected from the moment they land, maintaining access to the tools they depend on throughout their journey.

But connectivity today is not just about getting online. It is about staying reliably connected in ways that match how people actually travel. That includes having access to essential apps even when data runs low, so travellers can still navigate, message, or access critical services without interruption. It means being able to share a hotspot with travel companions, ensuring that groups can stay coordinated without juggling multiple connections. It can also include added protections such as VPN access, helping travellers use public networks more securely while on the move.

The most useful travel solutions today are not always the most visible. Often, they are the ones who quietly keep the trip functioning. They remove friction in the background, support continuity, and help the traveller stay capable when the itinerary stops being linear. In practice, that means reducing the number of points where the journey can break.

Also Read: The AI travel revolution: Why hotels must be found by bots to be chosen by humans

This is especially relevant as travel becomes more dynamic. Plans change mid-route. Delays cascade. Travellers book later, adjust faster, and depend more heavily on digital tools while moving. The trip is no longer something managed only before departure. It is constantly being updated in motion.

That creates a different standard for what travellers need from connectivity. Being operational means being able to navigate, communicate, verify, pay, rebook, and adapt without losing momentum. It means the traveller can stay responsive when the situation changes. That may sound simple, but in practice, it is one of the most important forms of travel confidence.

This is where the conversation around mobile access needs to evolve. For too long, connectivity in travel has been framed mainly around convenience or cost. Those points still matter, but they no longer capture the full picture. The larger issue is continuity. When connectivity fails, travel does not just become less convenient. It becomes less functional.

That is also why solutions in this category need to be designed around real traveller behaviour, not just technical provision. Travellers do not think in terms of data alone. They think in terms of outcomes. Can they get where they need to go? Can they stay in touch? Can they handle the next change without friction?

Alongside reliability, predictability matters too. Unexpected roaming charges or bill shock can quickly turn a smooth trip into a stressful one. Modern connectivity solutions are increasingly designed to remove that uncertainty, giving travellers clear control over their usage and costs so they can focus on the journey itself.

The value is not just that travellers can get online, but that they can stay responsive as plans move. Whether that means accessing essential apps, managing movement on arrival, or staying connected through unexpected changes, the role of connectivity is increasingly tied to the traveller’s ability to keep the trip intact.

The travel industry has already made major progress in helping people book with ease. The next challenge is helping them move with confidence.

Because in modern travel, the hardest part is often not making the booking.

It is staying fully functional after the journey begins.

—

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

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

Join us on WhatsApp, Instagram, Facebook, X, and LinkedIn to stay connected.

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A government-commissioned study found that 24 per cent of Global Business Services roles in Malaysia are highly impacted by AI and 65 per cent are medium impacted. Nearly nine in ten GBS jobs are changing in some material way within the next three to five years. The same study put a number on the people involved: 59 per cent of the GBS workforce, around 163,000 employees, need upskilling to stay relevant in roles that are evolving faster than the job descriptions written for them.

That figure sits against a harder one. Business closures and downsizing have already cost Malaysia tens of thousands of jobs this year. The Human Resources Minister’s position has been measured: AI isn’t the primary driver of those losses today, and workers who build AI skills won’t be left behind. That’s reasonable. What it doesn’t settle is who’s responsible for building those skills, and whether companies are doing it.

The data suggests most aren’t. Only 37 per cent of organisations have active internal AI training programmes running, based on research AGOS Asia conducted with Roland Berger, published in September 2025. The other 63 per cent are leaving it to individuals or waiting for a better moment to invest. With 163,000 GBS roles already on a clock, that gap is a serious one.

It shows up in a specific place. The job descriptions companies are hiring against today were largely written before generative AI was a daily work tool. Most have been updated at the margins, a line about digital proficiency here, a mention of system experience there, and that has been treated as current. It isn’t. A job description built around a fixed set of tools is quietly signalling the wrong priorities to every candidate who reads it.

The bar isn’t that every person becomes a technologist. It’s that they have enough familiarity with the tools in their environment to work alongside them confidently, to know when an automated output needs questioning, and to contribute to conversations about how a process could work better. That’s a realistic expectation.

Also Read: Are you a human resource?

But it doesn’t happen by accident, and it doesn’t show up in a job description that hasn’t been touched in three years.

The qualities that actually determine whether someone can work effectively alongside AI, learning orientation, adaptability, and willingness to question automated results, rarely appear as real evaluation criteria. They sit in a paragraph about culture, and nobody tests for them in the interview.

Three questions hiring managers can use now to surface whether a candidate has the mindset the next three years will require.

• One: “Tell me about a process you changed without being asked to. What prompted it, and what did you do?” This separates people who treat improvement as part of their job from those who wait for instruction.
• Two: “Describe a time you had to learn a new tool or system quickly. How did you approach it, and what would you do differently?” This distinguishes people who adapt by instinct from those who need a formal programme before they’ll move.
• Three: “How do you stay current with changes in your field? Give me a specific example from the last three months.” The three-month constraint matters. It makes vague answers visible immediately.

Also Read: Human resources hacks for the bootstrapped startup

Hiring is only half of it. The obligation runs in both directions. Rewriting job descriptions without investing in people already in the function creates a split: new hires arrive with the right profile while experienced team members find themselves measured against criteria they haven’t been supported to meet. That shows up in retention before it shows up anywhere else.

The same TalentCorp study names talent retention and development as one of its core recommendations for industry players 5i, not a nice-to-have. Russell Parry at AstraZeneca built that thinking into their modular AI training programme from 2023: “We have seen measurable gains in both productivity and retention since rolling out our modular training approach. People want to work where they are being invested in, and they want to work on things that feel like the future.”

Most companies are measuring productivity. Fewer are measuring whether their people investment is affecting whether people stay. The 163,000 figure is a policy problem and a company problem at the same time. What happens inside individual organisations, at the level of the job description, the hiring conversation, and the performance review, is still a corporate decision. One won’t solve the other.

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A sharia bank in Jakarta asked me last quarter whether their new credit scoring model needed Sharia Supervisory Board review. They had deployed it three months earlier, trained on five years of their own portfolio data, and were preparing to roll it out across their consumer financing book. The risk committee was satisfied. Nobody had asked the sharia supervisory board.

That conversation is the part of Islamic finance’s AI story we have not yet written honestly.

I have spent four years inside sharia risk policy at Indonesian banks, and fifteen years across the country’s financial functions. The structures that govern sharia finance — fatwa, supervisory boards, classical jurisprudence applied to modern instruments — are robust at what they were designed to govern. They were not designed to govern algorithms that retrain themselves quarterly. The gap between what these institutions can review and what their banks are deploying is widening faster than anyone inside the system is willing to name.

I would call it the fatwa lag.

The structure that worked

Every sharia banking product, across the major Islamic finance markets, must pass through a formal sharia review before launch. In Indonesia, that means a fatwa from the National Sharia Council (DSN-MUI). At the institution level, every sharia bank operates with an independent Sharia Supervisory Board (DPS) that reviews products, contracts, and operational practices against classical jurisprudence.

The system has, for decades, worked. It has prevented riba from creeping into modern Islamic banking products. It has flagged gharar — excessive uncertainty — and maysir, speculation, inside derivative-like instruments that conventional finance accepted without question.

What it has not faced before is a class of products that change their own logic between fatwa hearings.

Also Read: In SEA, Millennial Muslims in Indonesia are more confident about using AI for travel: HHWT

Where AI breaks the system

Three problems are emerging quickly enough to deserve naming while there is still time to design around them.

The black-box gharar problem. Sharia explicitly prohibits gharar in contracts and transactions. When a customer is denied financing by a machine learning model that nobody at the bank can fully explain, the basis of the decision is opaque. Conventional finance has been wrestling with this through model explainability tools. Sharia finance faces a sharper version of the same question: at what level of opacity does a decision become non-compliant by virtue of the uncertainty alone?

The fatwa cycle versus the model cycle. A new sharia banking product typically takes six to eighteen months to receive a DSN-MUI fatwa. A credit model can be retrained quarterly, sometimes monthly. The current version of the model is therefore almost never the version that received scholarly review. The bank assumes the principle approved in the original fatwa survives across retraining cycles. In many cases, it does. In some cases, it cannot.

The board capacity gap. Sharia Supervisory Boards across ASEAN are composed of distinguished scholars — masters of classical jurisprudence, often with limited exposure to model architectures, training data biases, or drift monitoring. The review process was designed around contracts, not statistical artefacts. Asking these boards to certify AI-driven products in their current form is asking them to review what they were never trained to read.

What is starting to happen

A few institutions are quietly responding.

Joint sharia-and-model reviews. A small number of leading sharia banks now run parallel reviews — one by the DPS, one by the model risk function — and reconcile the two before deployment. The process is slow. It is also producing the most defensible decisions.

Bilingual practitioners. The most valuable people in this space are the ones with both sharia training and quantitative risk fluency. Universities in Indonesia, Malaysia, and the Gulf are beginning to design joint programmes, but the first graduates are years from sufficient seniority.

Conservative model design. Some sharia banks deliberately choose simpler, more explainable model classes for sharia products — accepting a small loss in predictive accuracy for the ability to defend each decision to the DPS. The institutions doing this do not advertise it publicly. It is the right instinct.

Also Read: Seasonal product cycles: Why some features only work at certain times

What the framework should look like

A serviceable AI compliance framework for Islamic finance would need at least three components.

A standing AI advisory protocol inside each Sharia Supervisory Board, with bilingual practitioners attached for technical translation. The classical scholarly authority remains on the board. The technical literacy that informs it sits beside.

A version-aware fatwa system. Rather than approving a model once at deployment, fatwas for AI-driven products should specify the boundary conditions under which the fatwa remains valid — training data scope, model class, performance envelope. Re-training inside those bounds requires no new fatwa. Re-training outside them does.

Cross-jurisdictional coordination. The DSN-MUI, the Shariah Advisory Council at Bank Negara Malaysia, and equivalents across the Gulf are wrestling with the same problem in isolation. A shared registry of approved AI compliance approaches, even at the level of guidance, would accelerate the system as a whole.

The macro stakes

Indonesia is the largest Muslim-majority economy in the world. Malaysia, Brunei, and the southern Philippines are growing sharia finance markets. The Gulf states host the deepest pool of sharia compliance scholarship globally. Each is now deploying AI inside financial services at the same pace as conventional banking — without the same maturity of risk infrastructure designed for the questions AI raises.

The Islamic finance system has spent forty years proving that principles can govern modern markets without being compromised. The next decade will test whether those principles can also govern markets that change their own logic between reviews. The institutions that answer that question first will set the standard. The ones that wait will inherit one.

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

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

Join us on WhatsApp, Instagram, Facebook, X, and LinkedIn to stay connected.

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Daniel Kokotajlo used to lead research at OpenAI, thinking several years ahead. He left in 2023 and gave up a chunk of equity/money to do it because he didn’t want to sign away his right to talk about what he was seeing. Since then, he’s built out some of the more detailed public forecasts of where AI is headed, and people in the field take him seriously, not because he’s dramatic, but because he isn’t.

So when he told an interviewer recently that he and his wife decided not to have any more kids, it landed differently than it would from someone hyping a headline. His forecasts, he said, had “collapsed toward the present.” Too uncertain. He doesn’t expect his six-year-old daughter to ever join a traditional workforce.

I’m not writing this to argue whether he’s right about the timeline. Reasonable people in AI disagree hard on the specifics; some think 2027 is absurdly aggressive, some think it’s conservative. That’s not the interesting part.

The interesting part is that someone with more visibility into this than almost anyone, when it came down to planning his own family’s life, didn’t hedge with optimism. He priced in the uncertainty and made a real decision around it. That’s a different thing than doomscrolling about AI. That’s someone treating an unstable variable like an unstable variable, instead of pretending it’ll sort itself out because it always has before.

Now zoom out to where I actually spend my time, which is talking to founders, funds, and increasingly, final-year students across Vietnam, the Philippines, and Indonesia, who are a few months from graduating into whatever the job market turns out to be.

Also Read: AI and the crisis of recognition: Do we still see the human behind the words?

Nobody’s telling them the plan might not hold. Universities are still building curricula around stable career ladders. Parents are still saying, “Finish your degree, get placed, climb”. Job boards are still structured like 2015. Meanwhile, the entry-level roles that used to be the first rung, junior analyst, junior dev, first line support, are the exact roles AI tools are already eating fastest, because they’re the most repeatable, most pattern-based work in any organisation.

That’s not a hot take; that’s just what’s happening quarter over quarter. The uncertainty Kokotajlo is pricing into his family planning is the same uncertainty sitting underneath every “get a good job” conversation happening in a Vietnamese household right now. Nobody’s saying it out loud. The gap between what these systems assume and what’s actually shifting keeps growing, and almost nobody’s naming it directly to the 22-year-olds who are about to walk straight into it.

Here’s where I’d push back on the doom version of this story, though, because I don’t think the answer is fear, and I don’t think it’s “learn to code” either; that ship’s more complicated than it was five years ago.

What I’ve noticed talking to students across the region who seem the least anxious about this isn’t that they’re smarter or more technical than everyone else. It’s that they’ve stopped treating “get hired by one company” as the whole plan. They’ve got a small portfolio of things they can point to, a project, a client, a certificate that proves they actually did something rather than just sat through a syllabus. They’re building proof of work before anyone’s paying them for it. They think in terms of what they can do, not what title they’re hoping to get.

Also Read: The fatwa lag: How AI is overtaking the system designed to govern Islamic finance

That’s not a hack, and it’s not new either; honestly, it’s closer to how things worked before large stable companies existed, when people had trades and reputations instead of resumes. What’s new is how early you need to start building that muscle now, because the old runway, degree, then job, then promotion, is getting shorter every year, not longer.

I don’t think Kokotajlo’s daughter’s future is as bleak as the framing sounds. Six-year-olds have a long runway to figure out a very different world. Final-year students don’t have that same runway. They’re standing at the door right now.

So if even the people closest to how fast this is moving are hedging their own kids’ futures instead of assuming business as usual, that’s worth sitting with for a second before you finish your final semester assuming the plan you were handed still holds.

The students I talk to who aren’t waiting around for that plan to confirm itself aren’t scared. They’re just already building something of their own.

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

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

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Most product leaders are taught to watch competitors, benchmark features, and track market share as if category collapse begins with a stronger rival building a better version of the same thing. That story is tidy, but it is not how extinction usually works.

Entire product categories do not disappear because somebody made a slightly better product. They disappear because the conditions that made the category necessary stop holding. What looked like a stable market suddenly loses its reason to exist in its current form. The product may still work. The customers may still know the brand. The teams may still be shipping. Yet the category is already moving from essential to optional, and from optional to strange.

Categories die when their old logic stops making sense

Every product category is built on a deeper logic than the features it happens to include. That logic usually answers a few quiet questions. Why does this need to exist as a separate product? Why is this problem important enough to buy directly? Why should this workflow live in one place rather than another? Why is the current buyer the right buyer? Why does the category deserve its own budget, its own owner, and its own operational space inside the customer’s world?

Extinction begins when those answers weaken.

A category can look healthy on the surface while its underlying logic is already decaying. Usage may still be present. Revenue may still look respectable. Buyers may still renew because change is inconvenient. But if the market has started solving the same job through infrastructure, platforms, defaults, or adjacent products, the category is already in trouble. It is no longer being chosen because it is the best expression of the need. It is being tolerated because history has not finished moving yet.

The most dangerous extinction event is when the job becomes ambient

The cleanest way to understand category collapse is to ask what happens to the core job over time.

Some jobs become more specialised. Those usually create new categories. Others become more routine, more embedded, and less worthy of a standalone purchase. That is when extinction risk rises sharply.

A category is in trouble when the job it solves starts becoming ambient. By that I mean the job still matters, but users no longer want to visit a dedicated product, maintain a separate workflow, train a separate owner, or justify separate spend to get it done. They want the capability where the work already happens. They want it built in, quietly available, and increasingly invisible.

Also Read: Your customers are not buying your product, they are buying a better version of themselves

Extinction is usually caused by a shift in habitat, not a flaw in the species

Product people often describe collapse as if the incumbent product failed to evolve. Sometimes that is true. More often, the more revealing question is whether the habitat changed.

In product terms, habitat means the wider conditions that determine how value is created and captured. It includes distribution, buyer incentives, workflow location, data gravity, trust, regulation, integration expectations, and the cost of switching behaviour.

A category can be well designed for one habitat and completely ill-suited for the next. What made it successful can even become the very thing that slows adaptation. Deep control becomes friction. Rich configurability becomes overhead. Dedicated interfaces become needless travel. Specialist ownership becomes an organisational drag. Premium economics becomes harder to justify once the capability starts appearing inside broader platforms.

When a category’s language starts sounding old before its revenue does

One of the earliest warning signs is linguistic. Customers begin describing the problem differently. They no longer use the language that built the category. They speak in broader outcomes, adjacent workflows, or platform expectations. The old category terms start sounding internal, vendor-led, or historically specific.

Language is often the first place where market reality moves. Customers stop asking for the product as a noun and start asking for the capability as a verb. They do not want the category. They want the result. That shift is dangerous because it weakens the psychological boundary that kept the category intact. Once customers stop believing the problem deserves its own named product class, bundling becomes easier, substitution becomes easier, and the product’s claim to standalone importance starts eroding.

When the buyer changes, and the category does not

Many product categories are built around a particular buyer logic. A certain function owns the problem, controls the budget, and values the product for reasons tied to a specific era of operating reality.

Extinction risk rises when the economic buyer changes, but the category continues selling itself to the previous one.

This is not just a go-to-market issue. It is often a sign that the product category is losing its place in the organisation. The new buyer may want broader workflow coverage, lower tool sprawl, tighter integration, stronger governance, or simpler procurement. A category that once won by being excellent at one narrow job may now look misaligned with how decisions are being made.

Also Read: When AI leaves the screen, cybersecurity becomes product responsibility

When data and workflow gravity move somewhere else

Some categories exist because they sit close to the data and close to the action. They have natural gravity. The product is where the relevant information lives, where decisions get made, or where execution naturally happens.

If the most important data starts accumulating elsewhere, or if the primary workflow shifts into another environment, the category begins losing its natural advantage. It has to work harder to stay relevant because the customer’s day now begins somewhere else. The product becomes a destination rather than a native layer of work.

When the category starts defending the process rather than creating leverage

One of the clearest late-stage signals is rhetorical. Category leaders begin talking less about new leverage for customers and more about the seriousness, depth, and discipline of the category itself. They argue that the problem is too important to simplify, too complex to embed, or too specialised to become part of a broader product.

Sometimes that is true. Quite often, it is the language of a category defending its old boundaries.

This matters because healthy categories usually talk about expanding possibilities. Dying categories increasingly talk about why the old structure must remain in place. They frame change as recklessness. They equate simplification with naivety. They protect the category’s architecture more fiercely than the customer’s changing reality.

How to predict extinction before it becomes obvious

The most useful way to predict category death is to stop asking whether the product is still good and start asking whether the category still deserves to exist in the same place.

That requires a different discipline of observation.

You have to watch where customers want the capability to live, not just whether they still value the capability. You have to watch who now owns the decision, not just who owned it historically. You have to study whether the problem is becoming more standalone or more ambient. You have to notice when the market’s language shifts from tool choice to expected default. You have to look for cases where the distribution starts with overwhelming superiority. You have to identify when the product’s natural habitat has moved, even though the organisation has not.

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