There’s a paradox at the heart of modern international business.

We’ve digitised nearly every aspect of operations. Marketing runs on sophisticated attribution models. Sales teams use AI-powered CRMs. Supply chains are optimised down to the last mile.

Yet when it comes to moving money across borders—one of the most fundamental business functions—most companies are still using infrastructure designed for a pre-digital era. And paying dearly for it.

The opacity problem in cross-border payments

Traditional banking thrives on information asymmetry.

When you execute an international wire transfer through a legacy bank, you’re operating in a black box. The exchange rate you receive isn’t the interbank rate—the actual rate at which currencies trade. It’s a marked-up version, typically 1.5-2% above market.

This markup doesn’t appear as a line item. It’s embedded in the rate itself. Your finance team sees money leave in one currency and arrive in another, with what appears to be normal conversion loss.

The real question is: how much of that “conversion loss” is actual market movement, and how much is bank margin?

Most companies can’t answer that question. And that’s precisely the point.

The economics of scale—working against you

Here’s what makes this particularly painful for growing businesses.

As you scale internationally, this problem compounds. A startup processing $100K in cross-border payments loses $1,500-$2,000 annually to FX markups—annoying, but not existential.

A mid-market company processing $10M? That’s $150,000-$200,000. Suddenly, hidden FX fees rival your entire marketing budget.

Yet finance teams often lack visibility into this cost center because it’s not categorized as “fees”—it’s just absorbed into COGS or operational expenses.

This is margin erosion in its purest form: value quietly transferred from your business to financial intermediaries, with no corresponding increase in service quality.

Also read: Why WorldFirst’s latest move could change how digital platforms scale worldwide

The infrastructure shift that’s already happening

Forward-thinking CFOs have started asking a different question.

Not “What does our bank charge?” but rather “What does international payment infrastructure actually cost in 2025?”

The answer increasingly involves purpose-built fintech platforms designed for cross-border commerce. Companies like WorldFirst have built infrastructure that:

1. Provides transparent, near-market FX rates—typically 0.3-0.5% above interbank, versus 1.5-2% for traditional banks
2. Eliminates hidden intermediary fees—no correspondent banking markups
3. Offers real-time visibility—you know exactly what you’re paying before you commit

This isn’t about chasing marginal savings. It’s about fundamentally rethinking payment infrastructure as a strategic function rather than a commodity service.

The new customer economics

WorldFirst’s current offer for new customers illustrates where the market is heading:

• 5 free international transfers (complete fee waiver)
• 50% reduction in FX costs on ongoing transactions
• Auto-applied incentives (no manual intervention required)

For a business processing $1M annually in cross-border payments, this translates to $10,000-$15,000 in recovered margin, every year, indefinitely.

But the more interesting insight isn’t the promotional pricing. It’s that platforms can afford to offer these economics because their infrastructure costs are fundamentally lower than legacy banking systems.

This is what disruption actually looks like: not flashy innovation, but structural cost advantages that incumbents can’t match without cannibalizing their existing business model.

What this means for strategic planning

If you’re a CFO or finance leader planning for 2025, cross-border payment optimisation should be on your roadmap—not as a “nice to have,” but as a margin protection initiative.

Ask yourself:

• Do we have visibility into our actual FX costs? Not what we’re told they are, but what the market spread actually is?
• Are we treating payment infrastructure as strategic or commodity? If commodity, you’re likely overpaying.
• What would we do with an extra $15K, $50K, or $150K in annual margin? Because that’s what’s at stake.

The pattern we’re seeing

We work with hundreds of scaling businesses across Southeast Asia and beyond. The pattern is unmistakable:

Companies that successfully scale internationally have optimized their payment infrastructure early.

Not because they’re obsessed with saving pennies. But because when you’re operating on 10-20% margins (typical for e-commerce, manufacturing, or marketplace businesses), a 1.5% hidden cost is the difference between sustainable growth and a slow bleed.

The businesses still using traditional banks for cross-border payments fall into two categories:

1. Early-stage companies that haven’t reached scale where it matters yet
2. Mid-market companies with institutional inertia—”we’ve always done it this way”

The latter group is leaving significant money on the table. And in an increasingly competitive global market, that’s a luxury fewer businesses can afford

Also read: What facilitates the adoption of digital currencies in Southeast Asia?.

The action item

This isn’t a dramatic transformation. You don’t need to rip out existing systems or retrain your entire finance team.

It’s a simple evaluation:

1. Calculate your actual annual cross-border payment volume
2. Estimate your current all-in FX costs (including hidden markups)
3. Compare to alternative infrastructure pricing
4. Run a pilot with a portion of your volume

For most businesses with meaningful international exposure, the ROI is immediate and substantial.

The question isn’t whether to optimize payment infrastructure. It’s whether you can afford not to.

Ready to benchmark your current FX costs? Explore WorldFirst’s new customer offer and see where you stand.

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For much of the internet’s history, visibility operated like a formula. Feed any search engine the right signals — keywords, backlinks, structured data — and your content could rise through the search rankings to be seen by potential customers. Digital influence was largely a technical exercise, but the way people seek information has fundamentally changed.  Generative AI systems are now used to remove the labour of decision-making and are expected to produce answers and recommendations, not search results.

This shift is reshaping the entire logic of discoverability. When answers replace links, the criteria for visibility changes too. That is where Generative Engine Optimisation (GEO) comes in: the emerging discipline that determines how brands appear in AI-generated responses or whether they appear at all.

From signals to semantics: A new foundation for visibility

Traditional SEO rewards pages that satisfy ranking algorithms. GEO, however, is rooted in meaning. Large language models (LLMs) also index content, but that’s not all they do.  It interprets data for users, it sets criteria, it makes recommendations, and when challenged, it doubles down on those recommendations.

In this world where LLMs mediate decisions, visibility is earned through consistency. LLMs look for and evaluate coherence, narrative alignment, and reliability across the broader information ecosystem when generating responses or recommendations.  To appear, a brand must sound consistent no matter where it appears: an owned website, a media interview, an annual report or an analyst brief. When generative models detect stable patterns, they treat them as trustworthy reference points. Conversely, when they encounter contradictions, they simply omit the brand from the answer.

The question for leaders shifts from “How do we rank?” to “How are we described when we are not in the room?”

The new hierarchy of credibility

GEO reshapes traditional communication principles by redefining what credibility looks like in an AI-mediated landscape. Experience is no longer about broad claims but about demonstrable outcomes and evidence of impact. Expertise is conveyed through spokespersons whose perspectives are clear, quotable, and consistent.

Also Read: AI in banking: Unlocking success with ChatGPT and embracing the future

Authority stems from being featured in reputable, high-quality platforms and contexts that AI systems recognise as reliable, like events, in traditional media. Lastly, trust emerges when a brand’s internal messaging aligns with how external sources describe it. Together, these elements create a semantic identity: a coherent, machine-readable portrait of the brand.

AI as the new gateway to information

As generative engines take over more search behaviour, the cost of inconsistency grows. A brand that doesn’t appear in AI-generated answers becomes digitally invisible, even if its SEO footprint remains strong. Meanwhile, companies with aligned narratives gain semantic weight and become the default examples referenced by LLMs.

We are already seeing early adopters shape how entire industries are defined. Their language becomes the vocabulary that AI uses to describe the market.

Transforming communications strategies

GEO also changes how communications leaders create and monitor content. Content should not be viewed as a standalone asset; it is crucial data input that AI systems analyse and learn from. This makes structure as important as storytelling, demanding content that is precise, contextual, and easy for machines to interpret. Credible media placement gains new weight as LLMs increasingly prioritise trusted sources.

At the same time, monitoring now extends beyond sentiment or volume to assessing how AI systems describe the brand, what they overlook, and where misunderstandings occur. Ultimately, influence is shifting from optimising for algorithms to optimising for the quality and accuracy of the answers machines produce.

GEO is not a replacement for SEO — it is the next layer

While SEO ensures content is accessible, GEO ensures it is understood, making both essential for modern visibility. To succeed in this new environment, brands must regularly audit how they appear across generative systems, address narrative inconsistencies across channels, and create content that is reusable, structured, and easily quotable. It also requires treating communication as a unified ecosystem rather than a collection of isolated outputs. In this context, meaning and distribution — not volume — becomes the decisive asset.

Also Read: Are large Vietnamese tech enterprises ‘indifferent’ when competing with ChatGPT?

What this means in the new year

Generative AI will no longer be a novelty but the main interface through which information is accessed. Search will feel less like “searching” and more like conversing. Consumers will expect direct, personalised answers, and brands will compete for inclusion within those answers, not for page-one rankings.

GEO will become a baseline requirement for digital existence. Brands that invest early in semantic clarity and consistency will shape category narratives. Those that lag may find themselves gradually omitted from the AI-generated knowledge graph — a form of invisibility that is difficult to reverse once established.

The organisations best prepared for this future understand one thing clearly: in the age of AI, visibility is not determined by how loudly you speak, but by how clearly you are understood.

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For a long time, venture studios were defined by their ability to build companies end-to-end. A single team would generate ideas, form founding teams, develop products, and support early fundraising. For several years, this integrated model worked well.

As we move through 2025 and prepare for 2026, however, that definition is starting to fall short. Across Asia and other startup ecosystems, a clear pattern is emerging: venture studios are increasingly partnering with one another, and this is less a trend than a structural adjustment to how startups are now built and scaled.

Why the single-studio model is no longer sufficient

The operating environment for early-stage companies has changed in meaningful ways.

• First, global readiness is expected much earlier. Local validation alone is rarely enough to support long-term growth or follow-on investment. Market entry strategy, early partnerships, and initial sales conversations now need to be considered from the start.
• Second, execution capabilities have become more specialised. Product development, go-to-market execution, partnership building, and fundraising each require distinct skill sets. Maintaining excellence across all of these functions within a single studio has become increasingly inefficient.
• Third, precision matters more than speed. Starting quickly is no longer the main advantage. What matters more is being connected to the right customers, partners, and investors at the right moment.

In response, venture studios are rethinking where they create the most value—and where collaboration makes more sense than internal ownership.

Also Read: Real estate sales development: Unlock the power of partnership and collaboration

Collaboration as role clarity, not expansion

The recent rise in venture studio partnerships is often misunderstood as an effort to scale faster or increase visibility. In practice, most collaborations are far more deliberate. They are based on clear functional role-sharing rather than broad cooperation.

Some studios focus on early company formation and business design. Others specialise in market entry, sales execution, or cross-border partnerships. Still others are strongest in capital formation and investor networks. Increasingly, studios are choosing not to duplicate these capabilities internally.

Recent partnerships, including collaborations with firms such as One Tree Hill Ventures, reflect this approach. Rather than attempting to control the entire startup lifecycle, each organisation focuses on the stage where it can operate most effectively. Outcomes are then passed to the next execution partner in a structured way. The objective is not speed for its own sake, but reducing execution risk and building repeatable paths to growth.

Addressing the execution gap after introductions

Another factor driving collaboration is a persistent gap in the startup ecosystem: strong initial engagement, weak follow-through.

Demo days, conferences, and curated meetings have multiplied, yet many promising conversations fail to translate into concrete outcomes. This challenge is not limited to founders. Venture studios and accelerators face the same issue internally, where introductions are made but ownership of next steps remains unclear.

Partnership-driven models help address this problem by clarifying responsibility. When execution roles are explicitly defined across organisations, connections are more likely to move beyond discussion and toward action. In this sense, collaboration becomes less about expanding networks and more about increasing execution density.

Redefining venture studio competitiveness for 2026

As we approach 2026, venture studio performance is no longer judged primarily by how many startups are launched or how quickly ideas are turned into products.

Instead, more relevant questions are emerging:

• Where does this organisation create the highest execution leverage?
• Which parts of the startup journey are better handled by partners?
• Can this structure be repeated and scaled across multiple companies?

Also Read: Weathering the tariff turbulence: How AI and collaboration can lift SEA SMEs

Partnerships offer practical answers to these questions. They are not a signal of weakness, but a recognition that specialised strengths, when properly connected, outperform fully integrated but diluted models.

Collaboration as a sign of maturity

The growing number of venture studio partnerships suggests that the sector itself is maturing. Organisations are becoming more explicit about what they do well—and equally clear about what they choose not to do.

Looking ahead to 2026, the differentiator for venture studios will be less about how much they can build alone and more about how clearly they define roles, connect execution, and sustain those structures over time.

Collaboration, in this context, is not a compromise. It is a strategic response to a more complex and interconnected startup environment.

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If you walk around the Gelora Bung Karno (GBK) stadium complex in Jakarta on a Sunday morning, you will witness a fascinating spectacle. It is a runway of neon-colored carbon-plated shoes, smartwatches that cost more than a motorcycle, and activewear that screams luxury. Running in Indonesia’s capital—and in other major hubs like Surabaya or Malang—has transcended mere cardio. It has become the supreme social currency of the urban middle class.

But recently, a glitch has appeared in this well-curated matrix.

A new, bizarre service has surfaced in the underbelly of X (formerly Twitter) and community Telegram groups, creating ripples of confusion and amusement across the local tech ecosystem. They call themselves “Joki Strava” (Strava Jockeys).

For a fee ranging from IDR 50,000 to IDR 100,000 (roughly US$3 to US$6), these individuals offer a service that sounds like a plotline from a dystopian satire: they will log into your fitness account, strap your phone (or theirs) to their arm, and run a 10K at a blistering pace on your behalf.

You get the stats. You get the glamorous map route. You get the kudos. They get the sweat.

As a tech observer based in Indonesia, I find this phenomenon to be more than just a quirky viral trend. It is a profound case study on the fluidity of Southeast Asia’s gig economy, the commodification of data, and the extreme lengths users will go to purely for digital validation.

The mechanics of ‘outsourced’ vitality

To understand the Strava Jockey, one must first understand the unique digital landscape of Indonesia. This is a country where the informal economy has always been incredibly agile in adapting to digital platforms. We have seen “click farms” selling likes, “game jockeys” ranking up Mobile Legends accounts, and now, we have fitness proxies.

The transaction is shockingly simple, bypassing the need for complex APIs or platform loopholes. It relies entirely on crude account sharing—a cybersecurity nightmare, yet a risk users are willing to take. The client provides their login credentials. The jockey, often a genuine athlete or a student with high stamina and low cash flow, performs the activity.

Once the run is complete, the data syncs. The client then screenshots the “Morning Run” summary—complete with an impressive Pace four (four minutes per kilometre) and a high calorie burn—and posts it to Instagram Stories.

The caption usually involves faux-humility: “Felt heavy today, but glad I pushed through.” Meanwhile, the actual runner is likely catching their breath on a curb, waiting for the bank transfer to arrive.

Also Read: Indonesia’s antivirus reliance: A cybersecurity blindspot

Why buy sweat? The economy of vanity

From a Silicon Valley perspective, this makes zero sense. The value proposition of Strava is self-quantification; cheating defeats the entire purpose of the product.

However, from a Southeast Asian sociological perspective, it makes perfect sense. In Jakarta’s hyper-competitive social hierarchy, health is the new luxury. Being fit signals that you have the time and discipline to train—assets that are scarce in a city known for its punishing work hours and gridlock traffic.

A Strava screenshot is not just data; it is a “Proof of Life” for the elite. It signals: “I am part of the successful tribe.”

The demand for jockeys arises from a gap between aspiration and reality. The peer pressure to join running clubs (which are essentially networking hubs) is immense. But building the aerobic base to run a 10K takes months of painful effort. The vanity economy offers a shortcut: Buy the result, fake the process.

It is the digital equivalent of wearing a knock-off Rolex. The function is irrelevant; the signalling is everything.

The resilience of the micro-gig economy

The Strava Jockey phenomenon offers a crucial insight into the Indonesian market: If a platform has a social metric, locals will find a way to monetise it.

We often talk about the “Gig Economy” in the context of Gojek or Grab—formalised, app-based labour. But the Strava Jockey represents the “Shadow Gig Economy.” It is unregulated, decentralised, and incredibly efficient.

These jockeys are micro-entrepreneurs. They have identified a market inefficiency (rich people want stats but hate running) and provided a solution. They are monetising their own biological assets (lungs and legs) in a direct peer-to-peer transaction.

It also highlights a form of “Platform Leakage.” The transaction happens off-platform (negotiated on WhatsApp, paid via QRIS/e-wallet), meaning Strava captures none of the value, even though their app is the core product being sold.

Also Read: Malaysia, Indonesia escalate AI oversight with temporary Grok block

A challenge for health-tech trust

While amusing, this trend poses a serious question for the future of health-tech and insurance-tech (insurtech) in the region.

As insurance companies increasingly move towards “wellness-based pricing”—offering lower premiums to users who share their fitness data—the existence of Strava Jockeys breaks the trust model. If a user can outsource their cardio to a semi-pro runner, the data becomes corrupted.

How can an algorithm differentiate between a 40-year-old corporate executive suddenly running a sub-40-minute 10K, and a 20-year-old jockey carrying his phone?

Conclusion: The black mirror of the tropics

The rise of the Strava Jockey is a quintessentially Indonesian tech story. It blends high-tech adoption with deep-seated cultural behaviours—specifically panjat sosial (social climbing) and gotong royong (mutual assistance, even in cheating).

It serves as a reminder to founders and investors targeting this region: You can build the most sophisticated tracking algorithm in the world, but you cannot code against human nature.

In the vanity economy, reality is negotiable. We have entered an era where your Uber driver can bring you food, your Gojek driver can bring you packages, and now, your Strava Jockey can bring you health—or at least, the digital illusion of it.

The sweat is real. The stats are real. The only fake thing is the person claiming the glory. And in the economy of likes, perhaps that is the only metric that matters.

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When my mother retired, she still loved cutting hair for seniors at the community centre. Her old clipper became her favourite companion, a symbol of care and pride. Years later, as her memory began to fade, she could no longer find that clipper. She searched everywhere, frustrated and sad, certain it was still around.

I realised then that she was not just looking for an object. She was searching for a piece of herself, the part that gave her purpose.

That moment became the start of my journey with AI storytelling. Because memory, once lost, is hard to retrieve. But the story, when shared, becomes timeless.

Preserving what fades

When a loved one begins to forget, their stories start to scatter like leaves in the wind. AI tools today can help us gather those fragments and hold them gently.

I used ChatGPT to help me write down her memories. I used Artflow to recreate images of her when she worked, laughing with her clients. I added her voice using simple audio tools. Suddenly, I had something precious, not just data, but emotion captured in motion.

It was not perfect, but it was deeply human. AI did not replace her story. It helped me remember it.

When technology becomes empathy

The truth is, AI cannot feel. But it can help us feel more. It can listen patiently, arrange words and images, and remind us of details we might overlook.

For families facing dementia, this becomes powerful. When you turn daily conversations into short stories, photos into memories, and voices into keepsakes, you are not using technology. You are using love in a new language.

Every time I create a short AI film about my mother, I feel as though I am giving her story back to her. It is a conversation between past and present.

Also Read: Preserving memories in the age of AI: How technology helps us remember who we are

Storytelling as connection

AI storytelling is not only for families. It can help communities preserve culture, educators record wisdom, and midlifers document their second acts.

We often underestimate the stories we carry. But every memory, even an ordinary one, can spark belonging.

When someone says, “No one wants to hear my story,” I remind them that memory is not about the audience. It is about continuity. It is how we remind ourselves that we mattered, that we made someone smile, that we once changed a small part of the world.

Healing through creation

The act of turning memories into art is healing in itself. You do not need technical skills. You only need intention.

When I guide participants in storytelling workshops, they often cry, laugh, or sit in quiet reflection. AI becomes a mirror for emotions they did not know how to express. Some use it to honour a lost parent. Others use it to capture childhood laughter or forgotten dreams.

The process heals because it allows us to hold both the pain and the beauty of remembering.

The gentle reminder

Stories are our real inheritance. They carry the colours of who we are. AI simply gives us a new brush to paint them with.

So if you have a memory worth keeping, do not wait. Speak it. Record it. Write it. Let AI help you shape it, not to make it perfect but to make it last.

Because one day, someone you love will look for a piece of you the same way my mother looked for her clipper. And when they do, your story will be there, waiting to be found.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

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In 2025, artificial intelligence (AI) transitioned from a boardroom buzzword to a primary driver of unemployment. The shift was surgical, targeting specific job functions that were once considered the bedrock of corporate tech.

According to data compiled by UK-based forex company RationalFX, nearly 245,000 jobs were lost in 2025 as companies swapped human salaries for software subscriptions.

Customer support: The first domino

The most visible victim of this transition was the customer support sector. Salesforce, a leader in CRM software, provided a stark example of this trend. CEO Marc Benioff announced that the company had slashed its customer support workforce nearly in half (from 9,000 positions to just 5,000) by deploying AI agents last year.

Also Read: Big Tech’s efficiency paradox: Record profits, record layoffs

Similarly, Amazon confirmed 14,000 job cuts specifically linked to AI adoption and the goal of making its corporate structure “leaner”. These 14,000 roles were part of a larger 20,000-person layoff wave at the company in 2025.

Amazon’s leadership described AI as “the most transformative technology we’ve seen since the Internet.” However, for thousands of employees in customer service and HR, that transformation meant the end of their livelihoods.

Replacing the “paper pushers”

The automation wave is also sweeping through HR, marketing, and financial operations. IBM, one of the industry’s oldest players, cut roughly 9,000 roles in 2025. While the company was tight-lipped about the specifics, reports indicated that the restructuring focused on non-tech jobs that could be partially replaced by AI. IBM successfully automated routine tasks such as drafting emails, managing internal queries, and analysing spreadsheets.

Professional services giant Accenture is executing a similar strategy. The firm announced a sweeping reduction of 11,000 employees over just three months as part of a US$865 million restructuring plan to pivot toward AI-driven operations. Even as it lays off thousands, it is doubling its AI and data specialist headcount, which now stands at 77,000.

The rise of “AI-first” hiring

The report by RationalFX highlights a disturbing trend: even when companies were not actively laying off, they were refusing to hire humans for roles that an AI can perform. Duolingo CEO Luis von Ahn clarified that while the company would not necessarily fire existing staff, they would only hire a human if “the AI cannot do the job it is tasked with properly”. This “AI-first” hiring policy has already led to the elimination of hundreds of contractor positions at the language-learning app.

Also Read: Why Asia’s tech giants are cutting from the middle

As enter 2026, the “middle class” of tech — support, administration, and middle management — finds itself in the crosshairs of a technology that doesn’t sleep, doesn’t require benefits, and, increasingly, doesn’t make mistakes.

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US equities ended Thursday on a high note, breaking a brief two-day slide as optimism around artificial intelligence reignited investor appetite. The catalyst came from across the Pacific: Taiwan Semiconductor Manufacturing Co.’s strong earnings and bullish 2026 guidance reassured markets that AI demand remains robust rather than speculative. This sentiment lifted chipmakers such as Nvidia and ASML to record levels, pushing the Nasdaq Composite up 0.25 per cent to 23,530.02, while the Dow surged 0.60 per cent to 49,442.44 and the S&P 500 edged higher by 0.26 per cent to close at 6,944.47.

Meanwhile, Asian markets extended their momentum into Friday, with the MSCI Asia Pacific Index hitting a new all-time high and poised for its fourth straight weekly gain, the longest such streak since May, fuelled largely by tech strength, including a jump in Indian equities after Infosys delivered upbeat results.

In contrast, the crypto market pulled back modestly, shedding 0.75 per cent over the past 24 hours. This dip reflects a classic post-rally consolidation, but deeper forces are at play. Bitcoin dominance climbed to 59.12 per cent, signalling a flight to relative safety within the digital asset space as traders rotated out of altcoins.

The Altcoin Season Index declined 11 per cent in a day, underscoring waning enthusiasm for riskier tokens, a pattern reminiscent of 2025, when Bitcoin outperformed altcoins by 38 per cent amid macroeconomic uncertainty. Layer-1 networks such as Solana and Ethereum lag, and social sentiment metrics indicate declining momentum for smaller-cap projects. If the Altcoin Season Index remains below 25, this Bitcoin-centric phase could persist.

Also Read: Nasdaq tumbles, but Bitcoin soars past US$97K on massive short squeeze

Regulatory ambiguity added another layer of caution. In Washington, the CLARITY Act stalled due to disputes over whether stablecoin issuers should be allowed to pay interest, a seemingly technical detail with profound implications for how regulators classify digital assets. Simultaneously, Binance temporarily halted deposits and withdrawals for several tokens, including ARB and 1INCH, citing technical reviews.

Such moves often stem from compliance checks, but they fuel market-wide nervousness, particularly among altcoin traders who rely on liquidity and exchange access. Bitcoin itself remains somewhat insulated. US spot ETFs now hold US$126.8 billion in assets under management, providing a structural bid that buffers against retail-driven volatility.

Perhaps the most telling signal comes from derivatives markets. Open interest in perpetual futures swelled by 18.9 per cent to US$655 billion, but this surge coincided with US$68 million in Bitcoin liquidations, US$55 million from long positions alone. Funding rates spiked by 60 per cent, revealing overcrowded bullish bets.

With Bitcoin’s RSI hovering between 65 and 78, the asset remains technically overbought despite the minor pullback. This suggests that the market is undergoing a necessary deleveraging phase rather than a fundamental reversal. Such corrections are typical after sharp rallies, especially when leverage builds rapidly.

Also Read: Why Bitcoin’s correlation with gold just hit a record high

From my viewpoint, this moment encapsulates the diverging narratives shaping financial markets in early 2026. Traditional equities, particularly those tied to AI infrastructure, benefit from clear earnings visibility and institutional backing. TSMC’s forecast acts as a proxy for real-world AI adoption, not just hype. Crypto, however, still operates in a regulatory grey zone where policy delays and exchange actions can trigger outsized reactions.

The current rotation into Bitcoin reflects a maturing market. Investors increasingly treat it as digital gold or a macro hedge, while reserving altcoins for higher-conviction, higher-risk scenarios. That said, Ethereum’s staking activity continues to reach all-time highs in transaction volume, suggesting an underlying utility that may eventually decouple it from broader risk-off moves.

The key levels to watch remain Bitcoin’s US$93,000 support and the Altcoin Season Index threshold. If Bitcoin holds firm and the index rebounds above 25, altcoins could stage a recovery. But if regulatory headwinds intensify or macro data shifts, the safety-first trend will likely deepen. For now, the dip appears corrective, a pause for breath after a sprint, not the start of a retreat.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

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Vietnam’s e-commerce numbers are no longer just impressive; they are disruptive. A US$16.3 billion GMV market growing nearly 35 per cent year-on-year signals not expansion, but acceleration into a new competitive phase. What stands out isn’t just scale, but velocity: Vietnam is now Southeast Asia’s fastest-moving e-commerce battleground.

TikTok Shop’s surge is the clearest marker of this shift. Its rise from challenger to near co-leader reflects how social commerce has moved from experiment to default discovery engine. Live-streaming isn’t a feature anymore; it’s the funnel. Shopee’s declining share shows that logistics dominance alone is no longer enough, while Lazada and Tiki’s marginalisation underscores how unforgiving the new algorithmic economy has become.

Equally telling is the seller shakeout. Fewer sellers generating more revenue points to a maturing market where platforms prioritise efficiency, engagement, and conversion over sheer participation. This mirrors a broader regional trend: Southeast Asia’s e-commerce boom is giving way to consolidation, margin pressure, and ruthless optimisation.

Vietnam’s category mix — led by beauty and fast-growing health segments — aligns with regional consumption shifts, but its urban concentration and low average order values reveal unfinished depth. Compared to Singapore’s profitability and Indonesia’s massive scale, Vietnam’s edge is speed.

For founders and operators, the message is clear: Vietnam offers explosive growth, but survival now depends on mastering platforms, content, and algorithms — not just being present.

REGIONAL

TikTok Shop is eating Vietnam’s e-commerce market alive: Vietnam’s e-commerce market reached US$16.3B in GMV in 2025 across its four largest platforms (Shopee, TikTok Shop, Lazada, and Tiki) up 34.8% YoY, according to Metric.vn. That’s US$44.5M transacted daily, with 3.9M items sold, a 15.2% increase.

Late-stage capital tightens grip on Southeast Asia’s fintech market: In 2025, total fintech funding across the region decreased 21% YoY to US$1.4B; Late-stage funding not only held up but expanded, rising 13% to US$930M, underscoring a decisive shift away from early experimentation towards de-risked growth.

CoinGecko eyes US$500M sale as crypto M&A heats up: CoinGecko’s potential sale underscores crypto’s maturation: data aggregators are no longer scrappy startups but strategic assets in a US$2.5T to US$3T market. For Malaysia, success could spotlight its under-the-radar crypto talent amid Singapore’s regulatory shine.

Southeast Asia’s cyber boom is fuelled by fear—and AI: The region’s cybersecurity market is exploding, valued at US$2.8B in 2024 and forecast to grow at a blistering 28.5% CAGR through 2030, according to MarketsandMarkets. This isn’t hype; it’s a data-backed arms race.

China’s humanoid robot leader AGIBOT sets sights on Southeast Asia: AGIBOT’s commercial offerings span multiple use cases: the A2 series for reception and hospitality; the X2 series for entertainment and education; the G2 series for industrial manufacturing; the D1 series for inspection operations; and the C5 autonomous floor-care robot.

Toku files for SGX Catalist IPO, doubles down on partner-led go-to-market strategy: The IPO marks a significant milestone for Toku, as it seeks to capitalise on rising demand for intelligent customer engagement solutions.

SGInnovate backs Botsync in extended Series A amid AMR market surge: In 2025, Botsync claims it recorded 240% growth in production trips, surpassing one million live production trips in real-world environments. Revenue grew 230% YoY, primarily driven by expansions from existing customers rather than new logos.

Philippines to join Malaysia, Indonesia in blocking Grok: The move comes after concerns about sexualised images generated by the system, said Henry Aguda, the country’s Information and Communications Technology Secretary. Aguda said the cybercrime centre is working with the telecoms commission to implement the block.

FEATURES & INTERVIEWS

Smarter AI models don’t automatically translate into adoption, says i10X’s Patrick Linden: The i10X co-founder argues that trust, discovery, and workflow integration—not raw model intelligence—remain the biggest barriers to AI adoption.

AI’s first real casualties: The tech jobs that vanished in 2025: According to data compiled by UK-based forex company RationalFX, nearly 245,000 jobs were lost in 2025 as companies swapped human salaries for software subscriptions.

Why Toku’s public listing could reset expectations for Singapore startups: Toku’s proposed SGX Catalist listing signals renewed confidence in Singapore tech IPOs, validating Asia-built AI infrastructure, disciplined scaling, partner-led expansion, and region-first strategies as founders and investors navigate 2026.

Big Tech’s efficiency paradox: Record profits, record layoffs: The report from RationalFX highlights that tech layoffs are not a sign of corporate distress, but a calculated restructuring. By removing “layers of management,” companies are attempting to become “leaner” and more agile.

Why Asia’s tech giants are cutting from the middle: The reality is that the traditional IT service model — built on large-scale human labour — is being challenged by new technologies that require a completely different, and often smaller, skill set.

INTERNATIONAL

Prudential, HSBC join US$220M Series D for Hong Kong’s WeLab: WeLab said the funds will support expansion in Southeast Asia, deepen its leadership in Hong Kong, and help launch new AI-driven business lines, along with product and platform enhancements.

Australia deactivates 4.7M under-16 social media accounts: Platforms such as TikTok, Snapchat, and Instagram provided data to the Office of the eSafety Commissioner, which is reviewing compliance. Meta reported removing over 500K accounts, including 330K from Instagram and 173K from Facebook.

OpenAI debuts Google Translate-like ChatGPT for over 50 languages: ChatGPT Translate mirrors the interface of Google Translate and lets users translate text with style presets such as “more fluent” or “academic.” It currently supports text input on desktop, and both text and voice input on mobile browsers.

Publishers seek to join Google AI copyright lawsuit: Publishers Hachette Book Group and Cengage Group allege Google copied content from their books without permission, as part of broader legal disputes involving authors and visual artists over AI training practices.

SEMICONDUCTOR

TSMC Q4 revenue hits US$33.2B; The Taiwan-based semiconductor foundry reported revenue rise 20.5% and net income climb 35% YoY, while revenue and net income increased 5.7% and 11.8% from the previous quarter, respectively.

South Korea holds emergency talks on US AI chip tariffs: The meeting, led by Industry Minister Kim Jung-kwan, came after the US outlined a plan to impose a 25% tariff on certain AI chips that are imported into the US and then reexported to other countries.

Taiwan firms to invest US$250B in US chip production: In return, the US will cut reciprocal tariffs on Taiwan to 15% from 20% and remove tariffs on some pharmaceuticals, aircraft parts, and natural resources. TSMC has bought land in Arizona and may expand operations there.

South Korea to invest US$159M in chip, battery research: The funds will be distributed across 27 projects, targeting the development of advanced technologies in these sectors. About US$127.3M will go to 18 semiconductor projects, including next-generation chip packaging and advanced automotive chips for software-defined vehicles.

AI

Building digital trust in an era of AI: The role of verifiable technology: AI-driven fraud is eroding digital trust, pushing organisations beyond cybersecurity toward identity verification, where blockchain-based verifiable technology emerges as a scalable solution to restore authenticity, security, and confidence in digital interactions.

Why AI security demands a different playbook in Asia: Asia’s rapid AI adoption is exposing enterprises to new AI-specific threats beyond traditional cybersecurity, making AI governance, monitoring, and regulation critical to prevent shadow AI risks, data leaks, and costly breaches.

AI’s promise in Asia: Can technology finally include everyone?: Asia’s AI boom risks excluding people with intellectual disabilities unless inclusion is embedded by design, unlocking social impact, fairer systems, and major untapped market opportunities across education, work, and care.

AI storytelling for healing: Turning memories into digital legacies: A personal journey shows how AI storytelling helps preserve fading memories, turning family stories, images, and voices into lasting emotional keepsakes that restore purpose, connection, healing, and continuity across generations.

THOUGHT LEADERSHIP

Nasdaq tumbles, but Bitcoin soars past US$97K on massive short squeeze: US stocks retreated amid tech rotation and geopolitical pressure, while global markets stayed mixed. Bitcoin surged past US$95,000 on ETF inflows, signalling crypto’s growing decoupling from equities.

The rise of ‘Strava Jockeys’: How Indonesia’s vanity economy is hacking the fitness tech ecosystem: Running in Indonesia has become elite social currency, spawning “Strava Jockeys” who sell fake fitness data—exposing vanity economics, shadow gig work, and fragile trust in health-tech platforms.

Why venture studios are choosing collaboration over competition: Venture studios are shifting from end-to-end builders to specialised collaborators, partnering across formation, market entry, and capital to reduce execution risk, close follow-through gaps, and scale startups effectively by 2026.

Do you know what ChatGPT is saying behind your back?: AI doesn’t gossip, but it constantly evaluates you—logging prompts, shaping assumptions, and influencing outcomes in ways users rarely see, question, or fully understand.

Why signals matter: Build from zero to a quadrillon: Most Singapore startups fail by chasing noise, not signal. Signal-aware founders prioritise speed, focus, culture, decision-making, and resilience—identifying what truly matters at each growth stage to build enduring, scalable companies.

Value creation: When startups die surrounded by capital: Startups increasingly fail not from capital scarcity but organisational “respiratory failure”, where misaligned narrative, go-to-market, and operations prevent funding from reaching teams that create durable value.

Why does cybersecurity training for employees in Malaysia matter and how to go about it?: As Malaysian businesses navigate the complexities of an increasingly advanced landscape, the importance of cybersecurity cannot be overstated.

The post Ecosystem Roundup: TikTok Shop disrupts Vietnam e-commerce; Fintech funding tightens; CoinGecko mulls US$500M sale; AI job cuts deepen appeared first on e27.

With its vast landscapes and fertile soils, Indonesia stands as an agricultural powerhouse, offering immense opportunities in staple crops and horticulture. Staple and horticultural crops contribute roughly US$50 billion to the national GDP. Across 26 million hectares of arable land, approximately 15.5 million farming households work tirelessly to cultivate essential crops like rice, corn, chillies, and potatoes, feeding the nation and driving the agricultural economy.

Yet, despite having the largest arable land in Southeast Asia and ranking among the world’s top producers, Indonesia’s crop yields lag behind its neighbours. Indonesia’s staple crop, rice, yields an average of 4.7–5.3 tons per hectare, lower than Vietnam’s 5.7–6.0 tons and China’s seven tons per hectare.

Indonesia is also the fourth-largest chilli producer, yet its chilli pepper yields hover around 8–9 tons per hectare, behind China’s 22 tons and Thailand’s 14 tons. Potato yields range from 15 to 20 tons per hectare, comparable to China and Thailand but significantly lower than Laos, where yields reach 32 tons per hectare. 

Now, imagine increasing yields by 50 per cent or even doubling them within a single growing season, without expanding farmland. The impact would be game-changing, not just for food security but also for smallholder farmers, many of whom earn as little as US$87 per month, even 35 per cent below Java’s typical regional minimum wage.

So why is productivity still a challenge? Farming is an uphill battle, full of risks. As conditions evolve, challenges multiply, making higher yields even harder to achieve. To understand why output continues to lag, we must look at four critical challenges that shape farmers’ reality:

• Extreme weather
• Persistent pest outbreaks
• Limited understanding of soil health
• Lack of reliable access to farming knowledge

In this article, we will explore each of these challenges in depth, highlighting opportunities for intervention and innovation to drive a more resilient and sustainable agricultural future.

Battling extreme weather: Farming in unpredictable conditions

The rhythm of farming has long danced to the tune of rains and tropical sun:

Rice farmers in Java and Sumatra schedule their planting with the onset of the wet season so that their sawah (paddy) fields are naturally flooded.

Corn farmers meticulously time their sowing schedules to ensure that young seedlings benefit from ample moisture during the early rainy season, establishing a strong start before any dry spells occur.

Highland potato farmers in Dieng, dealing with cool, damp conditions and heavy rains, strategically time their fungicide applications to shield crops from fungal infections.

Even in normal years, Indonesian farmers contend with weather patterns that can be unpredictable. However, recent extreme weather events have pushed these challenges to unprecedented levels. El Niño in 2023–2024 prolonged the dry season, disrupting planting schedules and stressing crops.

The consequences have been significant, though not all of them are well-documented. In 2024, rice production suffered an estimated decline of around 18 per cent compared to 2023, as farmers struggled to adapt to the delayed rains. In Kabupaten Sikka, drought conditions led to approximately 20 per cent of the corn crop failing in 2024, highlighting the vulnerability of local agriculture to shifting climate patterns.

Also Read: Unlocking agritech’s potential: Can Southeast Asia rise to the challenge?

With extreme weather events becoming more frequent, traditional planting schedules are no longer reliable. While completely preventing weather-related adversities is impossible, early warning signs can help mitigate their impact.

The never-ending firefight: Why reactive pest management fails

Farmers pour everything into their land—time, money, and sweat—but what if the result is watching it all be destroyed by pests or wither away from diseases they couldn’t cure? 

Farmers face a relentless battle against stubborn pests and diseases. Corn farmers are fighting Anthracnose, known locally as hama patek, which can cause a drastic yield reduction of up to 94 per cent. Highland potato farmers in Indonesia are battling the ever-evolving Phytophthora, which frequently mutates locally, reducing its sensitivity to commonly used fungicides. Cabai rawit, or chili peppers, face the Gemini virus, which thrives in tropical climates. Unlike in Western countries, where cold weather limits its spread, the virus persists year-round in Indonesia, gripping farms.

Farmers are fighting back the best way they know how: pesticides. But here’s the problem. Out of fear of losing everything, many farmers apply pesticides at levels far exceeding recommended doses. Utami et al. (2020) found that farmers in the Upper Citarum River Basin applied an average of 24.6 kg of pesticides per hectare annually—much higher than the 16.2 kg per hectare used in Vietnam and 8.4 kg per hectare in Thailand. This overuse not only doubles expenses but also poisons the soil and puts additional pressure on the growing plant.

It feels like an endless battle—spray more, spend more, yet still lose crops. But the real way forward isn’t just dumping more chemicals into the fields. The key is understanding the land, the pests, and how to fight them smarter, not harder. Instead of reacting to problems after they arise, farmers can tackle root causes to prevent them.

In this way, farmers can break out of this exhausting cycle and actually build a more sustainable way to protect their harvests for the long run.

Uncharted ground: The overlooked role of soil health in farming

Over months of farming, the nutrients that make crops thrive are gradually depleted, leaving the land weaker with each harvest, unless nutrient replenishment strategies are taken to restore balance. Take potatoes, for example. After a season of potato farming, nitrogen levels in the soil plummet because potatoes are heavy feeders of nitrogen. If farmers don’t replenish it properly, the next crop will struggle to grow, leading to lower yields and weaker plants.

Many farmers rely on past experience, assessing soil color by sight and texture by touch—but soil conditions can change due to factors like erosion, rainfall, and previous crop nutrient uptake, making past experience unreliable as the sole guide. Guesswork cannot determine the precise nutrient adjustments needed for planting.

This is where soil analysis comes in. A good soil test tells farmers exactly what their land is missing—whether it’s nitrogen, phosphorus, or potassium—so they can apply the right nutrients at the right time. Soil analysis also determines whether the soil is in the right condition to absorb nutrients, as pH levels and electrical conductivity (EC) play a huge role in this.

Soil pH determines acidity or alkalinity, which directly affects nutrient availability. For example, phosphorus fertilisers are most effective at a pH of 6.0–7.0, but when the soil becomes too acidic (which often happens due to over-fertilisation), phosphorus binds with other elements and forms insoluble compounds, making it less accessible for plant uptake and hindering growth. 

EC measures the concentration of dissolved salts in the soil, influencing nutrient absorption. Low EC may indicate a lack of essential ions, making fertilisers less effective, while high EC can signal excess salts, making it harder for roots to absorb water and causing nutrient imbalances that hinder plant growth.

Also Read: The agritech challenge in Indonesia: Can AI and mobile apps enhance productivity?

Instead of treating all land the same, farmers need better access to soil testing and guidance on how to adjust their approach. Understanding their soil’s nutrient levels, pH, and EC can help them make small but powerful changes—like adjusting fertiliser types, correcting pH imbalances, managing EC levels through proper irrigation or organic amendments, or rotating crops strategically. It’s not just about saving money; it’s about protecting the land so it can keep producing for generations to come.

The knowledge crisis: Why “asking the neighbour” isn’t enough

Picture this: A chilli farmer in Sumatra struggles with wilting crops. He asks a neighbour, who recommends doubling pesticide use. The neighbour’s farm thrives, but his farm worsens. Why? Because soil isn’t universal. 

Research by Istriningsih et al. (2022) found that 80 per cent of farmers rely on peer advice as their primary source of information, placing even more trust in neighbours than retailers (59 per cent) or farmer group leaders (50 per cent). Yet, soil health varies significantly.

A study in Medan, sampling every 250 meters, found soil pH ranging from 4.61 (acidic) to 5.87 (slightly acidic), highlighting that even adjacent land can differ in fundamental ways (Agrosains: Jurnal Penelitian Agronomi, 2021). This dependence on non-scientific guidance often leads to inconsistent or ineffective farming practices.

One of the biggest challenges Indonesian farmers face is the lack of access to reliable, expert guidance. While community-driven knowledge is invaluable, it is often based on local experience rather than data-driven insights.

Soil quality, microclimates, and environmental conditions can shift dramatically from one farm to the next, making generalised advice risky. The reality is clear: what works for one farm may fail on another. Without tailored recommendations, farmers remain vulnerable to suboptimal practices that hinder productivity.

A better way: Tech that works for farmers (not the other way around)

Technology alone won’t solve Indonesia’s agricultural productivity gap—but practical, localised innovation can play a key role. Solutions that combine field-level data, agronomic expertise, and real-time insights are starting to emerge across the country.

Tools such as weather monitors, soil analysers, and AI-driven advisory systems are helping farmers make more informed decisions, reduce guesswork, and improve yields without adding pressure to land or labour. Companies like DayaTani are exploring these opportunities by providing farmers with technologies that can provide personalised guidance that reflects local conditions, farming practices, and resource availability. 

The potential upside is significant: improved yields, reduced input costs, and greater resilience in the face of climate stress. But the path forward will require collaboration between agritech startups, research institutions, local governments, and the farming communities themselves.

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WeLab, a Hong Kong-headquartered pan-Asian fintech platform, has closed its Series D strategic financing round with US$220 million, cementing its position with the largest digital banking capital raise in Asia for 2025.

The round, comprising both debt and equity, came from investors, including Prudential Hong Kong, Fubon Bank (Hong Kong), Hong Kong Investment Corporation (HKIC), TOM Group, Allianz X, and HSBC.

The funding underscores intensifying investor focus on Hong Kong’s fintech sector amid broader regional digital finance expansion.

Also Read: HK government arm invests in WeLab to power fintech innovation across Asia

WeLab intends to deploy the money primarily towards expanding its virtual banking operations in Hong Kong and Indonesia, enhancing AI-driven credit scoring, and scaling cross-border lending products.

CEO Simon Lo has stated the funds will support product innovation and market penetration in Southeast Asia.

WeLab and its track record

WeLab operates two digital banks as well as multiple online financial services in Hong Kong, Mainland China, and Indonesia, with over 70 million individual users and over 700 enterprise customers. Over the past three years years, the firm’s revenue grew from US$450 million in 2023 to US$780 million in 2025 (73 per cent cumulative growth), per audited financials.

The user base also expanded to 60 million across Asia, with Hong Kong loans originations up 120 per cent to US$3.2 billion.

WeLab achieved breakeven in Q4 2024; net profit US$85 million in 2025.

In 2024, regulatory scrutiny in Indonesia led WeLab to a 15 per cent loan write-down, offset by 40 per cent deposit growth.

Since inception in 2013, WeLab has raised US$900 million across 10 rounds, including a US$240 million Series C in 2021 led by General Atlantic.

Surging investor interest in Hong Kong fintech

Fintech has captured outsized investor attention in Hong Kong, accounting for 28 per cent of all tech funding in 2025 per PitchBook data — up from 15 per cent in 2022. This surge aligns with US$3.4 billion in total tech investments across the city in 2025, driven by regulatory tailwinds and proximity to mainland China’s vast market.

Key metrics include:

• Average deal size in fintech: US$45 million in 2025 (vs. US$28 million in 2023).
• Number of fintech unicorns: Three (Airwallex at US$5.5 billion valuation, WeLab at US$4.3 billion post-Series D, and ZA Tech at US$7 billion).

Accelerants for digital banking growth and key players

Digital banks in Hong Kong are proliferating, with customer deposits hitting HK$110 billion (US$14.1 billion) by end-2025 — a 350 per cent rise since 2022 — per Hong Kong Monetary Authority (HKMA) reports.

Also Read: How digital banking is driving financial inclusion in SEA

Growth drivers include:

• Regulatory sandbox: HKMA’s 2018 virtual bank licences enabled eight operators, with low barriers to entry (minimum capital US$383 million reduced for innovators).
• Open banking APIs: Mandated rollout in 2024 boosted interoperability, driving 45 per cent year-on-year transaction growth.
• Consumer shift: 62 per cent of adults now use digital-only banking (Statista 2025), spurred by 0.1 per cent interest rates on deposits vs. traditional banks’ legacy systems.
• China integration: Cross-border QR payments with mainland fintechs processed US$25 billion in 2025.

The five major players in digital banking are:

1. ZA Bank: 2.5 million users, US$2.5 billion in loans.
2. Mox Bank: Standard Chartered-backed, 1.8 million accounts.
3. Livi Bank: HSBC-led, focusing on mid-market lending.
4. Airstar Bank: Xiaomi-backed, SME-centric.
5. WeLab Bank: WeLab’s virtual arm, now with 1.2 million users post-2023 launch.

Top 5 largest fintech deals in Hong Kong

Hong Kong’s fintech funding landscape has seen substantial activity, with WeLab’s raise topping the charts for 2025. Data from Tracxn and CB Insights as of Q4 2025 reveals the following top five largest deals:

These deals highlight a concentration in lending and payments, with total fintech funding in Hong Kong exceeding US$1.2 billion since 2020.

Also Read: Late-stage capital tightens grip on Southeast Asia’s fintech market

The latest fund-raise positions WeLab amid Hong Kong’s maturing fintech ecosystem, where digital banks now hold 8 per cent market share in retail lending. Investors eye spillover effects into Southeast Asia, e27.co’s core focus region.

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