For years, artificial intelligence was framed as a technology for companies with deep pockets: banks with large data teams, manufacturers with automated lines, or global platforms sitting on oceans of customer information. Malaysia’s latest AI agenda is trying to challenge that assumption.

Under the National AI Action Plan 2026-2030, also known as AI Nation 2030, the government is positioning AI not only as a tool for frontier industries, but as basic economic infrastructure for the sectors that keep the country running: micro, small, and medium enterprises, farmers, and plantation smallholders.

Also Read: Malaysia’s sovereign AI bet: Local context becomes the next startup moat

That matters because these groups are often the least equipped to adopt advanced technology, even as they have the most to gain from it. MSMEs dominate Malaysia’s business landscape, accounting for 84.4 per cent of all businesses in the services sector. In agriculture and plantations, smallholders and traditional producers remain critical to food supply, rural employment, and export-linked value chains such as palm oil.

The plan’s central bet is simple: AI adoption will not spread widely if it depends on every small firm or farmer building their own systems from scratch. Instead, Malaysia wants to lower the barrier to entry through shared platforms, vetted tools, common datasets, and training programmes that make AI usable without requiring every user to become a technologist.

From digitalisation to AI adoption

For many Malaysian MSMEs, the problem is not a lack of interest in technology. It is a lack of time, skills, and clarity.

A small retailer, logistics operator, home services provider, or food business may already use digital payments, accounting software, or online marketplaces. But moving from basic digitalisation to AI-enabled operations is a larger step. It requires knowing which tools are reliable, how they connect to existing workflows, and whether the benefits justify the cost.

The AI for MSMEs Impact Engine, labelled I10 in the plan, is designed to address this gap. Building on the Business Digitalisation Initiative, it aims to give MSMEs structured access to AI through a one-stop enablement ecosystem. Rather than asking small business owners to navigate a fragmented market of software vendors, the plan calls for modular and pre-vetted AI tools that can be integrated into platforms they already use.

The practical applications are not hard to imagine. AI can help a small retailer forecast demand, automate inventory tracking, answer customer queries, generate marketing content, or streamline invoices and payments. For a services business, it can support appointment scheduling, document processing, customer segmentation, and internal reporting.

The ambition is to provide 1.5 million MSMEs with scalable access to AI. If executed well, that could shift AI from being a premium productivity layer for larger companies into a utility for everyday businesses.

This is also where Malaysia’s plan fits into a wider Southeast Asian challenge. Across the region, MSMEs employ large numbers of people but often struggle with thin margins, low productivity, and limited access to digital talent. Governments from Singapore to Indonesia have launched digital adoption programmes, but AI introduces a new policy question: how to make advanced tools affordable and trustworthy for businesses that cannot absorb costly failed experiments.

Also Read: Why digitalising SMEs matters for Southeast Asia’s economic resilience

Malaysia’s answer is to create an AI marketplace where local providers can offer vetted, affordable services. This could also support domestic AI startups by giving them a clearer route to serve smaller customers at scale.

Bringing precision farming to small producers

The same logic runs through the plan’s approach to agriculture. AI in farming is often associated with large commercial operations using drones, satellite data, automated irrigation, and predictive models. Malaysia wants to make those capabilities available to smaller producers too.

The Agrofood: Scalable Agristack initiative, or I6, focuses on using data to improve precision farming and predictive analytics. In practice, this means helping farmers make better decisions about when to irrigate, how much fertiliser to apply, and how to reduce losses from pests, disease, and climate volatility.

The early phase will begin with pilots for precision irrigation and fertilisation in selected paddy and vegetable clusters. The plan then expands into weather analytics, automated pest detection, and a wider range of crops, including fruits.

This is not just about efficiency. Food security has become a sharper concern across Southeast Asia as countries deal with volatile commodity prices, changing weather patterns, and pressure on arable land. Malaysia, like many of its neighbours, must balance import dependence with the need to strengthen domestic production.

A scalable agristack gives the government and producers a shared digital architecture for agricultural data. If built carefully, it can allow farmers who lack expensive private systems to benefit from common datasets and AI models. That could help move decision-making from instinct alone to a mix of local experience and predictive insight.

The challenge will be trust. Farmers will not adopt AI simply because a platform exists. Tools must work in local languages, reflect local crop conditions, and prove their value in the field. Extension officers, cooperatives, universities, and agritech startups will likely play a crucial role in turning national infrastructure into everyday adoption.

Palm oil smallholders and the data divide

Malaysia’s plantation sector faces a similar divide. In palm oil, smallholders manage about 26.4 per cent of the country’s planted area. Yet they often operate with far less capital, data access, and technical support than large estates.

The AI Platform for Smallholder Empowerment, or I9, aims to narrow this gap by consolidating datasets into a unified platform such as MySawit. The goal is to give smallholders access to tools for pest and disease management, fertiliser optimisation, and more efficient monitoring.

The plan projects up to a 70 per cent reduction in manual labour and up to 2.7 times greater land coverage through AI-enabled automation, including drone services for spraying and monitoring. If those gains materialise, they could help smallholders improve yields and the quality of fresh fruit bunches, while reducing dependence on labour-intensive fieldwork.

The palm oil industry is also under growing scrutiny from global buyers and regulators over sustainability, traceability, and land-use practices. Better data systems could therefore serve a dual purpose: raising productivity for smallholders while helping the sector respond to market demands for transparency.

The missing pieces: data, skills, and inclusion

AI systems are only as useful as the data and people behind them. AI Nation 2030 recognises this through enabling initiatives such as the AI-Ready Data Ecosystem, which seeks to aggregate priority datasets and make them available through a National Data Exchange.

The proposal for a “Right-to-Data” channel for non-sensitive public sector data is particularly important. Local AI developers and agritech startups need access to reliable datasets to build models suited to Malaysian conditions, rather than depending entirely on generic imported tools.

Talent is the other foundation. The Talent Pipeline @ Scale initiative includes individual-based AI skilling credits aimed at workers in at-risk professions and low-income groups. This is a necessary safeguard. If AI adoption is framed only as automation, it will create anxiety among workers. If it is linked to upskilling and productivity gains, it has a better chance of being seen as augmentation rather than replacement.

Malaysia’s human-centric framing, tied to the MADANI vision, gives the plan its political and social logic. The test, however, will be implementation. Inclusive AI requires more than national targets. It needs simple procurement channels, local support networks, affordable tools, and measurable outcomes for users who do not have the luxury of experimenting endlessly.

Also Read: Meet the Malaysian AI startups pushing beyond the ChatGPT hype

By putting MSMEs, farmers, and smallholders near the centre of its AI strategy, Malaysia is making a statement about where digital transformation should happen next. The country’s AI future will not be judged only by the sophistication of its research labs or the scale of its data centres. It will also be judged by whether a paddy farmer in Kedah, a palm oil smallholder in Sabah, or a neighbourhood retailer in Johor can use AI to make better decisions and earn more from their work.

If AI Nation 2030 delivers on that promise, Malaysia could offer Southeast Asia a useful model: one where artificial intelligence is not just a race for the most advanced firms, but a practical tool for lifting the economic floor.

The post From paddy fields to small shops, Malaysia maps an inclusive AI future appeared first on e27.

Chinese enterprises are increasingly setting their sights on Southeast Asia, and the reasons go well beyond the familiar “supply chain diversification” narrative. e27 speaks to Lisa Li, China Lead Partner, KPMG Global China Practice, to unpack what is genuinely driving capital allocation decisions in Chinese boardrooms today.

From market opportunity to boardroom decision

According to Li, Chinese business leaders are turning to Southeast Asia due to a combination of pull factors, push factors, and strategic alignment.

The region’s enormous consumption potential — fuelled by a young demographic, rising disposable incomes, and rapid urbanisation — makes it an attractive frontier for Chinese companies in consumer goods, e-commerce, and digital services looking to expand their customer base.

Cost also plays a role. Land, labour, and utilities remain comparatively cheaper across most Southeast Asian countries than in China’s coastal manufacturing hubs, allowing companies to protect margins while diversifying production.

Also Read: Securing Singapore’s leadership in AI Innovation

Meanwhile, domestic competition in China has intensified, compressing profit margins and pushing decision-makers to look abroad. Southeast Asia’s geographical proximity and cultural affinity make it a natural first choice.

Policy dividends are another driver. The Regional Comprehensive Economic Partnership (RCEP) has lowered tariffs, streamlined customs procedures, and strengthened supply-chain connectivity across the region. Chinese firms are also aligning with national growth strategies; for instance, Singapore’s push to host regional headquarters even as companies manufacture in neighbouring countries, or the digitalisation and green transformation agendas being rolled out across ASEAN.

Finally, leading Chinese companies are confident they can replicate domestic success abroad. Having served hundreds of millions of consumers at home, they bring valuable experience in business models, branding, and supply-chain management to Southeast Asia’s emerging but fragmented markets.

A changing cast of investors

Li has observed a notable shift in who is expanding. Two decades ago, the landscape was dominated by large state-owned enterprises and centrally linked conglomerates, concentrated in energy, natural resources, and large-scale infrastructure — capital-intensive projects tied to national strategic objectives.

Today, private companies with more flexible decision-making and faster execution are emerging as the new driving force. A growing number of mid-sized and smaller private firms — many technology-driven, innovation-focused, or consumer-manufacturing oriented — are becoming frontline players. They are building brands, localising products, and tapping into Southeast Asia’s rising middle class across sectors ranging from smart home appliances and intelligent furniture to higher-value-added consumer goods.

That said, manufacturing remains one of the largest pillars of Chinese overseas investment. New energy vehicle (NEV) manufacturers, battery and spare parts producers, and the broader green energy supply chain continue to account for a substantial share of activity, even as tech-enabled and consumer goods companies increasingly drive deal volume and diversification.

Offence, defence, or both?

Asked whether this expansion is driven by genuine growth ambitions or by companies routing around tariffs and geopolitical risk, Li says both motivations have coexisted in recent years, though the balance has shifted.

When tariffs on most Southeast Asian countries rose in 2025, alongside tightened enforcement on origin verification, Southeast Asia stopped being viewed merely as an intermediate transit point for channelling exports to global markets. Chinese companies are no longer just seeking cost reduction; they are strategically expanding production, building ties with local consumers, and integrating into local business ecosystems for sustainable, long-term growth.

Localisation over geopolitics

On concerns about being perceived as “too close” to Beijing, or caught in US-China dynamics, Li is clear: current expansion is driven by growth considerations rather than geopolitical ones. Southeast Asia is increasingly seen not as a low-cost assembly hub for exports, but as a core strategic pillar where Chinese companies can build locally rooted, resilient, consumer-focused businesses capable of thriving independently.

Also Read: Singapore outsmarts the world in AI–ranked No.1 global hub

This is reshaping how companies structure their regional entities. Decisions on investment vehicles, ownership arrangements, and brand development are increasingly guided by localisation strategies. Many companies favour joint ventures with local partners for better market access, while branding leans towards local consumer tastes, often while retaining certain distinctive Chinese characteristics.

From tax structuring to strategic advisory

KPMG China’s role has evolved alongside these shifts. For years, the firm has supported cross-border M&A for Chinese outbound investors, working with the KPMG global network to provide integrated advisory services spanning financial advisory, due diligence, valuation, tax structuring, post-investment integration, and ongoing accounting and tax support.

But as greenfield investment gradually overtakes M&A as the dominant mode of Chinese expansion, particularly in Southeast Asia, KPMG is seeing a surge in mandates to help clients build new operations from the ground up. This includes site selection, joint venture partner vetting, and facilitating communication with local authorities to secure approvals and incentives.

Spotting trouble early

When expansion goes wrong, the fallout typically emerges within a year or two, says Li. Common failure patterns include financial strain from over-investment and underperformance, compliance gaps stemming from regulatory missteps and legal disputes, and talent loss driven by cultural integration challenges.

Early warning signs include eroding trust and communication between shareholders and management, cost overruns, weaker-than-expected market response, notable employee turnover, especially among core management and key technical staff, and rising disagreements with local partners.

Taken together, Li notes, these signals underscore the importance of decision-makers consistently reviewing business assumptions and promptly adjusting strategy as they navigate their overseas expansion.

The post It’s not just tariffs: The real reason Chinese capital is flowing into ASEAN appeared first on e27.

Southeast Asia’s financial services dealmaking held steady in the first half of 2026, with 31 disclosed M&A deals matching 2025 levels, even as disclosed deal value fell to US$936M from US$1.6B, according to EY’s latest financial services M&A analysis.

Wealth and asset management emerged as the standout gainer: deal volume nearly tripled to eight from three, while disclosed value jumped to US$145M from just US$800,000 a year earlier, reflecting rising demand from the region’s growing affluent population across Singapore, Indonesia, Vietnam, Malaysia and Thailand.

Banking and capital markets, still the largest segment by value, cooled to 14 deals worth US$669M, down from 20 deals worth US$1.1B, as regulation and legacy-system complexity slow full-scale acquisitions.

Insurance recorded more deals (nine versus eight) but smaller total value (US$123M versus US$478M). Foreign acquirers grew more selective (five deals, down from seven), but committed larger sums, US$410M versus US$344M, signalling international appetite for Southeast Asian financial assets persists despite near-term caution. EY expects larger transactions to return in the second half of 2026 if financing conditions improve.

REGIONAL

Malaysia stays Grab’s top market with US$622M in H1 revenue: The ride-hailing and delivery giant generated more revenue from Malaysia than any other market in the first half of 2026, underscoring the country’s outsized role in Grab’s recovery story.

ZUS Coffee weighs IPO to raise at least US$245M: The Malaysian coffee chain is exploring a public listing that could value it significantly higher than its last private round, signalling renewed investor appetite for SEA consumer brands.

VinFast and Gowa Motor to open 30 EV showrooms in Indonesia: Vietnam’s EV manufacturer is forming a joint venture with Indonesia’s Gowa Motor to accelerate its regional expansion amid intensifying competition from Chinese rivals.

Vietnam and Singapore firms to digitise cross-border LC verification: Technology companies from both countries are partnering to automate letter of credit verification, targeting a process still dominated by paper and manual checks.

Malaysia’s sovereign AI bet: Local context is the new startup moat
Malaysia’s AI Nation 2030 plan wants the country to move from an AI buyer to a producer, betting that locally trained models fluent in Bahasa Melayu can outperform generic global platforms in high-value domestic use cases.

Malaysia maps an inclusive AI future for farmers and small shops
Malaysia’s National AI Action Plan aims to give 1.5 million MSMEs and smallholders scalable access to AI tools, targeting up to 70% less manual labour in palm oil operations through shared platforms and vetted datasets.

Deepgram sets up APAC base in Singapore for multilingual Voice AI
Deepgram is establishing its Asia Pacific headquarters in Singapore, backed by a strategic investment from EDBI, after seeing a 96% year-on-year jump in API requests across the region’s 20-plus markets.

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INTERVIEWS & FEATURES

It’s not just tariffs: Why Chinese capital is flowing into ASEAN: KPMG’s Lisa Li tells e27 that Chinese firms are moving beyond tariff-dodging, drawn by Southeast Asia’s consumption potential and cheaper land and labour, with private firms now outpacing state-owned players.

Datakrew’s Hyundai pilot tackles the EV battery forecasting problem: Singapore’s Datakrew wrapped a year-long study with Hyundai CRADLE and GetGo, pulling 3.6B data points from 70 EVs to forecast battery health months in advance, within a claimed 3% prediction-error band.

Four lessons from GITEX Global: What Dubai’s AI playbook means for SEA: Sam Altman and UAE minister Omar Sultan Al Olama’s GITEX sessions revealed talent, not capital, as the real AI bottleneck, alongside energy supply emerging as AI’s next major constraint.

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INTERNATIONAL

Anthropic’s annualised revenue surges to US$6.5B: The AI safety startup has seen explosive commercial uptake, with revenue growing rapidly as enterprise demand for Claude accelerates globally, putting pressure on OpenAI’s market dominance.

Uber and Pony.ai plan 2,000 robotaxis across Europe: The ride-hailing giant is expanding its autonomous vehicle push into European markets with Chinese AV firm Pony.ai, a deal that could reshape its long-term driver model.

SoftBank pours US$200M into construction robotics firm Gravis: The Japanese conglomerate’s latest bet targets construction automation, a sector it sees as ripe for disruption given chronic global labour shortages.

Groq valued at US$3.5B after fresh funding round: The AI chip inference startup closed a new round following its Nvidia deal, with investors betting its speed advantage over GPU-based rivals will hold as LLM demand scales.

Wispr raises US$280M at US$2B valuation beyond dictation: The voice AI startup is pushing into broader agentic use cases after its rapid growth in speech-to-text, backed by significant new capital at a unicorn valuation.

SpaceX officially closes its Cursor acquisition: The move confirms Elon Musk’s aerospace company is expanding into developer tools, with Cursor’s AI coding platform now folded into SpaceX’s growing technology portfolio.

Uber adds Zipline drones to its Eats delivery network: Zipline’s autonomous drones will fulfil food delivery orders through Uber Eats, marking a meaningful step toward commercial drone logistics at scale.

YouTube to count views from the first second of playback: The platform’s updated view-counting policy will affect creator metrics and ad measurement, with knock-on implications for how brands allocate digital spend.

Meta faces trial over social media addiction claims: Facebook and Instagram are under legal scrutiny in a landmark US trial that could set precedent for platform liability over user harm and algorithmic design.

AI automation startup Relay shuts down, staff joins Google Chrome: Despite early traction, Relay could not survive in an increasingly crowded agentic AI market, with its team acqui-hired into Google’s browser division.

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SEMICONDUCTOR

Nvidia invests US$1.5B in SoftBank’s data centre unit behind OpenAI project: The chipmaker’s stake in SoftBank’s data centre developer deepens its position across the AI infrastructure stack and signals growing alignment between two of the industry’s most influential players.

NXP breaks ground on expanded Malaysia factory at 900,000 sq ft: The Dutch chipmaker’s facility expansion signals sustained foreign investment in Malaysia’s semiconductor manufacturing base, reinforcing the country’s role in global chip supply chains.

AI demand lifts Malaysia’s chip sector, but not every player wins
HSBC research shows Malaysia, Singapore and Vietnam are primary beneficiaries of the AI infrastructure boom, though companies without direct AI exposure face rising memory-chip costs squeezing margins instead.

CYBERSECURITY

Apple users hit by spyware alerts in unprecedented numbers: Security investigators report a surge in spyware notifications sent to Apple users globally, raising urgent questions about the scale and origin of the targeting campaign.

AI

Agentic AI adoption doubles to 51% among Singapore firms: A ServiceNow survey found that more than half of Singapore businesses now deploy agentic AI, the sharpest year-on-year jump recorded, outpacing adoption rates in most comparable economies.

Alipay launches agentic commerce platform for Chinese merchants: The payments giant is giving merchants AI-powered tools to automate customer interactions and transactions, a move that could influence how SEA super-apps evolve their merchant offerings.

Anthropic CEO frames AI backlash as a trust crisis: Dario Amodei argues that public resistance to AI is not about the technology itself but about institutional credibility, calling on the industry to prioritise transparency over capability announcements.

Zuckerberg’s AI vision fails to convince sceptics: Analysts and observers push back on Meta’s AI roadmap, questioning whether its open-source strategy and consumer AI products can generate the returns the market expects.

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THOUGHT LEADERSHIP

SEA solved distribution: Now fintech must scale on the balance sheet: Fathhi Mohamed argues Southeast Asia’s public payment rails have turned fintech into a utility business, where cheap, sticky deposits now matter more than another million app downloads.

Not every cheque keeps every door open for SEA founders: Surabhi Pandey writes that a funding round now carries a geopolitical footprint, urging founders to run due diligence on investors the way investors scrutinise them, to protect long-term strategic optionality.

AI won’t just automate tasks, it will repackage responsibilities: Daniel Tan argues the deeper shift isn’t task automation but the redesign of recurring responsibilities into reviewable, delegable systems, changing how individual contributors must think about ownership.

Your AI isn’t producing bad creative, your brief is: Aleks Farseev cites WARC research showing 88% of marketers produce more creative with AI, yet only 45% see a genuine quality lift, blaming stale demographic-only briefing.

Why Southeast Asia doesn’t need to pick a side in the AI race: Jan Alvin Pabellon argues the region’s advantage lies in connecting rival tech ecosystems rather than choosing between them, building trust infrastructure instead of competing on model scale.

AI is not the advantage, build what competitors cannot copy: Christopher Jackson urges SEA SMEs to protect know-how through trade secrets or patents rather than relying on AI-generated polish, which rivals can replicate just as quickly.

Strategic chokepoints: Designing leverage without owning everything: Niharika Ray argues durable market power comes from sitting at points where uncertainty must be resolved — trust, compliance, settlement — rather than from owning the entire value chain.

Social intrapreneurs can change the world too: Dr Erwin Chan writes that entrepreneurial change inside organisations doesn’t require founding a startup, just the discipline to pilot a scoped idea using existing budget and headcount.

The US$46,300 question: How low can Bitcoin go before buyers return: Anndy Lian notes Bitcoin’s Coinbase premium has stayed negative for 90 days as AI infrastructure spending diverts capital away from crypto, with a bear pennant pointing toward US$46,300.

Despite the rally, the CMC Fear and Greed Index stays at 39: Anndy Lian writes that Bitcoin’s 2.23% surge to US$64,300 and a cooling Fed rate outlook haven’t shifted sentiment, with the index still signalling market fear despite bullish technicals.

The post Ecosystem Roundup: SEA financial services deals hold firm despite sharp drop in value appeared first on e27.

Startup Bangladesh, the government-backed venture capital and fund management company under the ICT Division, has begun operational activities for the Bangladesh Fund of Funds, a new initiative designed to channel state capital through professional venture capital fund managers rather than only making direct investments into startups.

The fund has an initial size of BDT 400 crore (~US$33 million). Its launch through a Request for Expression of Interest was announced at an event in Dhaka attended by government officials, development partners, venture capital and private equity firms, startup founders, and investors.

Also Read: 20 game-changing startups driving Bangladesh’s innovation wave

For Bangladesh’s startup ecosystem, the structure matters as much as the amount. A fund-of-funds does not typically invest directly into companies. Instead, it backs venture capital funds, which then invest in startups. If executed well, this can help create more professional fund managers, improve investment discipline, and bring in additional private and institutional capital alongside public money.

That is the larger bet behind the Bangladesh Fund of Funds. The government wants each unit of public capital to attract more local, international, and development finance into the country’s startup market, where foreign investors have historically supplied the bulk of funding.

Over the past decade, Bangladeshi startups have reportedly raised around US$1.2 billion. But local investors accounted for only about 7 per cent of the capital deployed. That gap has long been a weakness for the ecosystem: founders often depend on foreign funds for growth rounds, while domestic pools of risk capital remain thin.

The new vehicle is meant to address that bottleneck by supporting selected fund managers who can deploy capital across a broader base of startups.

A policy shift from direct support to market-building

The launch comes as Bangladesh places greater political weight on startups and entrepreneurship as part of its economic development agenda. The government’s 2026 election manifesto emphasised startup growth, job creation, innovation, and the development of a technology-led economy.

In the current fiscal year, the government has allocated BDT 500 crore (roughly US$41 million) for startup development. It has also introduced tax and VAT incentives, including a zero per cent turnover tax, to lower the burden on young companies.

These measures come at a time when startup funding across much of Asia has become more selective. After the liquidity boom of 2020 and 2021, venture investors have shifted towards profitability, stronger governance, and clearer paths to scale. In Southeast Asia, this has pushed founders to raise smaller, more disciplined rounds and forced governments to think beyond grants and ad hoc startup programmes.

Bangladesh appears to be taking a similar route by trying to build financial infrastructure around its startup economy. The fund-of-funds model is already familiar in more mature markets, including Singapore, where public capital has often been used to crowd in private investors and support emerging fund managers. For Bangladesh, the challenge will be to adapt that model to a younger market where fund management capacity, exit pathways, and institutional investor participation are still developing.

Fakir Mahbub Anam, Minister for Posts, Telecommunications and Information Technology, described the Bangladesh Fund of Funds as a major platform for connecting entrepreneurs with capital and networks.

Also Read: Bangladesh’s startup ecosystem is entering a new phase of investability

“It will help connect promising Bangladeshi entrepreneurs with the capital, expertise, and global networks they need to grow,” he said at the event. “Through this initiative, we want to build a stronger pathway for innovation-led enterprises to create employment, attract investment, and contribute to Bangladesh’s future economy.”

Why fund managers matter

One of the less visible problems in emerging startup ecosystems is not only the lack of money, but the lack of experienced intermediaries to allocate it. Venture capital depends heavily on judgement: which founders to back, how to price risk, when to support follow-on rounds, and how to help companies navigate hiring, governance, expansion, and exits.

By investing through professional fund managers, Startup Bangladesh is signalling that the ecosystem needs more than a state chequebook. It needs investors who can repeatedly source deals, build portfolios, work with founders, and attract co-investors.

Nurul Hai, Managing Director and CEO of Startup Bangladesh Limited, said the initiative is intended to strengthen the deeper plumbing of the market.

“The Bangladesh Fund of Funds is not just about providing capital,” he said. “We want public capital to unlock much larger pools of private and international investment, strengthen professional fund managers and give high-potential Bangladeshi startups a clearer path to scale.”

The proposed structure includes fund-manager selection, co-investment mechanisms, and a sidecar facility, according to the presentation made at the event. Sidecar facilities are typically used to invest alongside a main fund or syndicate, allowing additional capital to follow selected opportunities without changing the core fund structure.

Japan International Cooperation Agency representative Morikawa Yuko said the fund could help deepen Bangladesh’s venture market by attracting institutional and foreign investment and bringing global VC firms into the ecosystem.

That external validation could prove important. Across Southeast Asia, development finance institutions, government-linked funds, and multilateral agencies have played a key role in supporting early venture ecosystems, especially where domestic pension funds, insurers, and family offices are still cautious about the asset class.

Bangladesh’s regional moment

Bangladesh is not usually grouped with Southeast Asia in a strict geographic sense, but its startup trajectory increasingly overlaps with the region’s. Its large young population, rising digital adoption, growing mobile payments activity, and dense urban consumer markets resemble the conditions that helped produce major tech companies in Indonesia, Vietnam, and the Philippines.

Yet Bangladesh has lagged behind those markets in venture depth. Indonesia has produced multiple unicorns and a relatively large local VC base. Vietnam has drawn strong interest from regional funds as a manufacturing and digital economy story. The Philippines has benefited from fintech and digital services growth, despite funding volatility. Bangladesh, by contrast, has produced notable companies in fintech, logistics, commerce, education, and health, but the capital stack around them remains less developed.

That makes the Bangladesh Fund of Funds both an opportunity and a test. If it backs credible fund managers, applies transparent selection criteria, and avoids political allocation of capital, it could help create a more durable venture market. If it becomes another top-down financing scheme without independent investment judgement, its impact may be limited.

The timing is also important. Regional investors are more cautious today, but they are still looking for underpenetrated markets with large domestic demand. Bangladesh, with a population of more than 170 million, remains one of Asia’s largest consumer markets. For startups, the question is whether that demographic scale can translate into venture-scale businesses.

Also Read: PulseTech delivers Startup Bangladesh’s first multi-fold return after revenue surge

The government’s role will be to reduce friction without crowding out private capital. That means supporting fund managers, improving tax clarity, encouraging exits, and giving institutional investors enough confidence to participate.

For now, the Bangladesh Fund of Funds marks a shift in ambition. Rather than backing individual startups one by one, the government is attempting to build a financing layer that can outlast a single budget cycle. Whether it succeeds will depend less on the announcement and more on who gets selected, how capital is governed, and whether private investors decide Bangladesh is ready for a larger seat at the regional startup table.

The post Bangladesh launches US$33M fund-of-funds to deepen startup capital pool appeared first on e27.

The conversation around artificial intelligence has become strangely polarised. One camp believes AI will replace millions of jobs. Another believes it’s the greatest productivity revolution in modern business.

I believe both camps are asking the wrong question.

After spending the last few years working alongside CEOs, Managing Directors and executive teams across financial services, technology and healthcare, I’ve come to a different conclusion.

AI won’t replace leaders. It will expose the ones who were never truly leading in the first place.

During a recent executive roundtable with multinational organisations, one question dominated the discussion.

“Did we spend too much, too fast, on AI?”

Some organisations had invested between US$200,000 and US$500,000 implementing AI platforms to gain first-mover advantage since late 2024. Yet despite sophisticated technology, many struggled to demonstrate measurable returns, till now.

The technology wasn’t broken. There just wasn’t a clear plan on what business outcomes AI was “supposed” to contribute to. The leadership operating system was faulty.

Technology moves faster than human transformation

Throughout history, every major technological leap has promised greater productivity. The Industrial Revolution automated manual labour. The internet democratised information. Cloud computing transformed collaboration.

AI is different because it is beginning to automate thinking itself. Yet while technology evolves exponentially, leadership capability often evolves incrementally, and in some cases, stays the same.

Many organisations have upgraded their technology stack without upgrading the way their leaders think, communicate and create trust for its implementation. This has created resistance to the immersive use of AI.

Now we have a dangerous gap. AI can generate reports. It cannot generate motivation. AI can analyse data. It cannot build psychological safety. AI can recommend decisions. It cannot inspire people to believe in them.

These have always been human responsibilities. So now, they have become competitive advantages. Imagine, would you have thought deep human connection to be a corporate advantage?

Also Read: The system behind the smile: How to make volunteer efforts sustainable

For years, organisations rewarded leaders primarily for technical expertise, operational efficiency and execution. Those capabilities remain important, but AI is rapidly commoditising technical knowledge.

When everyone has access to intelligence, leadership strength becomes the differentiator.

Leadership strength will be the ability to remain calm amid uncertainty. To think strategically when information is overwhelming. To communicate with clarity when ambiguity increases. To regulate emotion before making critical decisions. To create cultures where innovation feels safe rather than threatening.

This is why I have observed a consistent pattern. You cannot install AI on an outdated leadership operating system.

The organisations succeeding with AI are not necessarily those with the biggest technology budgets.

They are the ones who have leaders capable of helping people navigate uncertainty without losing trust, tying everything to a business outcome and not “AI for show”.

This is the biggest misconception about AI adoption, it is that implementation is primarily a technology project.

It isn’t, it’s a leadership transformation project. Employees rarely resist technology. They resist confusion. They resist poor communication. They resist feeling excluded from decisions that affect their future.

The highest-performing organisations don’t simply deploy AI. They create environments where people understand why change matters, how they contribute, and where psychological safety allows experimentation without fear.

Technology scales processes. Leadership scales people. The organisations that master both will outperform those investing exclusively in one.

From organisations competing through efficiency, today, they compete through adaptability. Tomorrow, they’ll compete through humanity.

Also Read: Why Singapore’s AI finance race is now about data, not models

As AI continues to level the playing field, qualities once considered “soft” will become remarkably hard to replicate.

• Empathy.
• Compassion.
• Presence.
• Influence.
• Resilience.
• Authenticity.

These are no longer leadership buzzwords but strategic assets.

Ironically, the more advanced AI becomes, the more valuable deeply human connection becomes.

Our most important question isn’t: “How quickly can we implement AI?”

It’s: “Are our leaders ready to lead in an AI-powered world?”

Because organisations don’t transform through technology. They transform through people who know how to lead technology. AI will undoubtedly reshape every industry, but it won’t replace exceptional leaders.

It will simply reveal who has been relying on authority, expertise or hierarchy instead of genuine influence.

The future belongs to organisations that invest as intentionally in leadership as they do in digital capability. The winners of the AI era won’t necessarily have the most expensive set ups, they’ll have the strongest leaders.

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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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