In the high-stakes world of enterprise software, a new rumor is sending ripples through IT departments from Singapore to Silicon Valley. Reports suggest that leadership within Microsoft, including Executive VP Rajesh Jha, may be exploring a radical shift in how the company extracts value from its software: moving from billing strictly per “human user” to a model that includes “AI agents” as billable entities.

While framed as a forward-looking AI strategy, industry skeptics are asking a tougher question: Is this a visionary move, or a sign of a giant feeling the heat of a changing kitchen?

The “agent” inflation

The proposed strategy suggests that as MS Copilot takes over more tasks, these “digital workers” should be counted alongside human staff in licensing agreements. On paper, it’s a logical evolution of the “Copilot” metaphor. In practice, it feels like a tactical move to bolster a stagnating seat count.

For the better part of two decades, Microsoft has maintained its grip on the corporate world through the Windows ecosystem and a formidable vendor lock-in strategy. But as enterprise clients become more cloud-agnostic and AI-savvy, the old tricks are losing their magic. If the massive $13 billion investment in OpenAI doesn’t result in a vertical spike in productivity soon, Microsoft may be forced to innovate its billing department faster than its engineering department.

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

The pressure of the OpenAI bet

The industry consensus is shifting. The initial “wow factor” of GPT-integrated tools is facing the cold reality of corporate ROI. Many organizations find that while MS Copilot is a helpful assistant, it hasn’t yet delivered the “technological breakthrough” promised to justify its premium cost.

This has led to whispers that Redmond is in a quiet “panic mode.” When a flagship investment doesn’t immediately “steer the ship” toward a new era of dominance, the fallback is often to squeeze more from the existing user base. By charging for “agents,” Microsoft could theoretically multiply its revenue without adding a single new human customer.

A string of bad luck

The timing of these pricing rumors couldn’t be more awkward. Following recent high-profile service disruptions—including the much-discussed Outlook connectivity issues that plagued teams during high-stakes aerospace simulations—Microsoft’s image as the “unshakable foundation” of enterprise is wobbling.

When your core tools face reliability questions, asking clients to pay for “AI agents” on top of human licenses starts to look less like a strategy and more like a gamble. The “viral” nature of these criticisms on professional networks suggests that the enterprise world is losing its patience.

Also read: Navigating the new era of brand mention tracking and AI visibility in Singapore

The clock is ticking

Microsoft’s reliance on its legacy ecosystem has served it well, but the “lock-in” is no longer an unbreakable chain. Competitive pressure from agile, AI-native startups and open-source alternatives is mounting.

If the “human + AI agent” model is indeed the path forward, Microsoft must prove it’s offering genuine value, not just a creative way to pad the invoice. Enterprise clients are looking for a reason to stay, but with little perceived “breakthrough” tech in recent years, the window to course-correct is narrowing.

Microsoft has long been the master of the “safe” choice. But as the “heat” rises, the question remains: Can they innovate their way out of this, or will they simply try to charge for the air in the room?

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About PRbyAI

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

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We have spent two decades glorifying speed. The mantras are relentless: “Done is better than perfect,” “If you’re not embarrassed by the first version, you launched too late,” and the ubiquitous, damaging directive to achieve a Minimum Viable Product (MVP).

The MVP framework has metastasised into something toxic: the pursuit of Minimum Viable Competence (MVC).

MVC is the cultural mindset where founders, desperate to hit an artificial launch date or secure a seed round, rush a product to market with just enough functionality to demonstrate viability, but with a foundational layer that is fundamentally and recklessly incompetent. This isn’t bootstrapping; it’s self-sabotage.

This rush creates a hidden, crippling liability that I call Competence Debt. It is more insidious and harder to repay than technical debt, and it is the single greatest reason why promising startups stall and collapse violently when they attempt to scale past the 10 million ARR mark.

The anatomy of competence debt

We all understand Technical Debt: the deferred cost of choosing a quick-and-dirty implementation over a better, more robust one. Competence Debt is the systemic equivalent, and it permeates the entire organisation, not just the codebase.

Competence Debt is incurred in three critical areas:

• The codebase and infrastructure (the hidden sinkhole)

The first version of the MVC product is often held together by duct tape, hasty third-party integrations, and code written by a single, exhausted founder or an inexpensive offshore team. The systems are non-compliant, non-secure, and barely documented.

The debt is incurred when this poor foundation is celebrated as a “lean” approach. When the company hits scale, the system begins to buckle. Simple feature updates take weeks instead of days. Security audits become catastrophic. The inevitable need for a rewrite, forcing the team to stop building new value and spend 12-18 months simply digging the company out of a self-made hole. This halts growth, burns capital, and destroys team morale.

Also Read: Why easy money kills startups

• The hiring and culture (the competence ceiling)

In the MVC rush, founders prioritise “bodies in seats” over quality talent. The first 5 to 10 hires are often friends, generalists, or candidates who accepted low salaries because the founder prioritised runway over excellence.

This creates a competence ceiling. Once the company needs specialised talent (a Head of Engineering, a VP of Sales), the existing incompetent leadership structure pushes back, either actively resisting change or passively stifling the growth of the better talent. The company can only scale to the lowest level of its existing leaders’ competence. The founder must then fire the people they started, or let the company stagnate.

• The customer promise (the broken trust)

The MVC approach forces a founder to sell a product they know is fundamentally incomplete. They over-promise functionality, stability, and support. This is a debt of trust.

When scaling, the customer experience becomes defined by outages, data errors, and the inability of the rushed infrastructure to handle volume. The resulting churn and brand damage are disproportionate to the early-stage “speed” advantage gained. The reputation that took 18 months to build can be destroyed in a single, prolonged outage caused by a brittle MVC-era server configuration.

Also Read: From shell to startups: Why scenario planning matters in volatile times

The imperative of over-engineering the foundation

The counterintuitive truth for founders seeking disruptive growth is that you must over-engineer the foundation.

Instead of MVC, the approach must be the Maximum Viable Problem (MVP) strategy: Build a product that is ruthlessly focused on solving one massive, complex problem for a tiny, elite group of early users. The solution, even if initially expensive and slow to build, must be structurally perfect, secure, and infinitely scalable from day one.

Why? Because the problem you are solving is the only constant. The code, the features, and the marketing are variables. If the solution to the Maximum Viable Problem is fundamentally sound, the company can pivot its features, its price, or its market, but it never has to stop building forward to repay a crushing Competence Debt.

The goal of the early stage isn’t speed; it is structural integrity. You are not building a paper prototype for a demo; you are laying the foundation for a skyscraper. If you build your skyscraper on a foundation of sand, it doesn’t matter how beautiful the lobby is. It will eventually crush the occupants.

We need to stop celebrating the founder who rushes a shoddy product to market. We should celebrate the founders who took an extra six months of relative silence, not to perfect the UI, but to build an unassailable engineering core.

When you receive that first major VC term sheet, are you prepared to show the investors the financial model, or are you secretly terrified of showing them the technical architecture that will support it? Are you building a business designed to look good for three years, or one engineered to survive thirty?

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

The post The Minimum Viable Competence (MVC) trap: Why your startup is built on sand appeared first on e27.

Algorithmic bias isn’t an ethics debate. For APAC startups, it’s actually a customer acquisition problem.

Picture this: you’re a founder running campaigns on Google or Meta, using an AI-powered optimisation tool your team swears by. The dashboard looks healthy, the algorithm is working, and it’s confidently serving your ads to urban, English-literate, smartphone-native consumers: the same segment other well-funded competitors in your space are chasing.

The algorithm isn’t broken, not really. It’s doing exactly what it was trained to do, and there lies the problem.

Most AI marketing tools were built on data that reflects who has historically converted, and in most cases, that customer profile was shaped by Western markets, existing financial access, and majority-language behaviour.

So when an APAC startup plugs in without asking questions, it inherits a very specific worldview of who your customer is supposed to be.

You don’t need a machine learning degree to understand the core mechanic. AI marketing tools learn from patterns: who clicked, who converted, who stayed.

And unlike a recruiter you can brief, the algorithm doesn’t tell you when it’s working from outdated assumptions. It just keeps optimising in the wrong direction.

More than a bias problem, this is a CAC problem

Here’s the reframe that matters for founders: the segments that AI tools tend to deprioritise are often the ones worth fighting for.

Underserved audiences in APAC are typically less saturated, and fewer competitors have bothered, which means lower costs to reach them.

They’re often faster-growing, representing first-time digital finance users, rising middle-class consumers, and gig economy workers entering the formal economy for the first time.

Also Read: AI didn’t invent bias, it inherited it

And once acquired, they tend to be more loyal. When you’re the first brand to reach someone in their language, on their terms, with a product that actually fits their life, you don’t lose them easily to a competitor whose algorithm never found them either.

The startup optimising only toward algorithmically “safe” audiences is competing on the most expensive, most crowded ground available. Meanwhile, the segment the algorithm flagged as low-converting might just be low-converting for the incumbent that trained the model.

Consider the trajectory of something like GCash in the Philippines or GoPay in Indonesia. The dominant narrative around their growth tends to focus on product. But a significant part of what made them work was a willingness to reach customers that existing financial infrastructure – and by extension, existing marketing logic – had written off.

Three things to do before you trust your tool’s outputs

• Ask where your tool was trained before you trust what it surfaces

Most vendors won’t answer directly, but the question is worth asking. Look at which audience segments the tool constructs automatically versus which ones you have to build manually. The defaults reveal the assumptions.

If the tool’s “recommended audience” looks nothing like the customer your product was built for, that’s not a good recommendation.

• Seed your own first-party data early and deliberately

The fastest way to correct for training bias is to give your algorithm a better signal. That means running intentional top-of-funnel campaigns to underserved segments: not to convert immediately, but to start generating behavioural data your tool can actually learn from.

It’s a slower start, but compounds significantly over time. The startup that builds a proprietary data advantage in a segment their competitors have algorithmically abandoned is the one that wins.

• Treat “low-converting segments” as hypotheses, not verdicts

When your tool tells you a segment underperforms, ask why before you cut it. Is the creative wrong for that audience? Is the landing page in the wrong language? Is the call-to-action built around a behaviour your customer doesn’t have yet?

The algorithm can’t tell the difference between “this segment won’t convert” and “this segment hasn’t been spoken to correctly,” and only you can make that call.

Also Read: The hidden dangers of AI bias: Where it can go wrong

The competitive case for equitable marketing

Building marketing infrastructure that works for the actual APAC customer, not the default archetype your software recognises, is a growth strategy.

Take the opportunity of the segments being systematically underserved by algorithmically-biased tools, because these are the market your competitors have outsourced the decision to a tool that was never trained to see them.

Equity by design, in marketing terms, is the unsexy work of auditing your stack, questioning your defaults, and deciding whether the “optimised” audience your tool serves up is actually your audience. The algorithm will always find you a customer. The question is whether it’s finding yours.

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

The post The AI marketing tools you’re using were trained on your competitor’s customer, not yours appeared first on e27.

Bitcoin and traditional equity markets moved in a tight, synchronised dance fuelled by a sudden thaw in geopolitical tensions. Bitcoin climbed 0.86 per cent to reach US$74,813.22, almost perfectly mirroring the 0.88 per cent gain across the broader cryptocurrency sector.

This movement appears deeply tethered to the S&P 500, with an 86 per cent correlation, suggesting that the digital asset is currently trading as a high-beta proxy for global risk appetite. Investors are clearly looking past previous volatility, focusing instead on a massive return of institutional capital and the possibility of a peaceful resolution to the conflict in the Middle East.

The primary driver of this price surge is a dramatic reversal in institutional behaviour toward spot Bitcoin exchange-traded funds. After a period of cooling interest, these funds recorded net inflows of US$411.5 million on April 15. BlackRock led this charge through its IBIT fund, which alone accounted for roughly US$214 million in new capital. This represents the second-largest daily inflow for April and serves as a powerful signal that institutional smart money is stepping back in to provide a robust floor for the market.

When large-scale buyers commit hundreds of millions of dollars in a single session, it creates a supply-demand imbalance that naturally forces the price upward, reinforcing the narrative that Bitcoin is no longer just a retail playground but a core component of modern portfolio management.

This resurgence in digital assets cannot be viewed in isolation from the record-breaking performance of the US stock market. On April 16, 2026, the S&P 500 gained 0.80 per cent to close at a historic peak of 7,022.95, while the Nasdaq Composite jumped 1.59 per cent to end at 24,016.02. This marked an impressive 11-session winning streak for tech-heavy indices.

Market sentiment was lifted by renewed optimism surrounding peace talks to resolve the war in Iran. As the fear of a broader regional escalation eased, the CBOE Volatility Index fell 1.03 per cent to 18.17. This decline in market fear directly benefited Bitcoin, as traders felt more comfortable moving back into riskier assets that had been suppressed by the threat of geopolitical instability.

Also Read: Is Bitcoin’s geopolitical rally sustainable? The data says maybe, but there’s a catch

Technically, Bitcoin’s price action appears increasingly constructive as it holds above critical support levels. The asset successfully held above the 50 per cent Fibonacci retracement level at US$74,479 and its seven-day simple moving average of US$74,586. These levels are essential psychological and mathematical markers for traders.

Staying above them confirms a bullish structure and prevents the cascading sell-offs seen at the height of the conflict earlier this year. As long as Bitcoin remains above this US$74,479 threshold, the path of least resistance appears to be toward the recent swing high of US$75,409. If that barrier is breached, the market will likely set its sights on the US$76,559 extension level.

While the headline numbers on Wall Street and in the crypto markets suggest a period of euphoria, the underlying economic data present a more nuanced and complicated reality. According to the Federal Reserve Beige Book, the US economy is growing at only a slight-to-modest pace. The report highlights that the war in Iran remains a major source of uncertainty, leading many businesses to adopt a wait-and-see posture regarding hiring and capital investment.

Furthermore, preliminary April data show that consumer sentiment has plunged to a historical low of 47.6 per cent. This disconnect between record-high stock prices and record-low consumer confidence is largely driven by persistent inflation concerns, even as energy prices, such as West Texas Intermediate crude oil, cooled slightly to settle at US$90.69.

The corporate sector reflects this divide between growth and geopolitical pressure. On one hand, tech giants and financial institutions are showing remarkable resilience. Broadcom surged more than 4.19 per cent following an extended partnership with Meta on custom artificial intelligence chips, and Tesla rallied 7.62 per cent to lead the major tech players. Large banks also contributed to the positive market mood, with Morgan Stanley rising 4.52 per cent and Bank of America gaining two per cent after delivering earnings that surpassed expectations.

These companies seem to be navigating the inflationary environment and the higher-for-longer interest rate landscape better than smaller firms. Other sectors more sensitive to energy costs, such as the energy industry itself, struggled as crude prices dipped, with TotalEnergies falling more than three per cent.

Also Read: Bitcoin’s US$74K surge: Institutional conviction or macro mirage?

In the bond and commodities markets, the signals remain mixed but generally supportive of the current risk-on environment. The 10-year Treasury yield is trading near 4.26 per cent, and while the yield curve remains inverted, with the two-year yield higher than the 10-year, equity markets have largely ignored this traditional recession signal for the time being.

Gold, often a rival to Bitcoin for the safe haven title, edged up 0.82 per cent to US$4,829.37 per troy ounce. The fact that both gold and Bitcoin are rising simultaneously suggests that while some investors are betting on peace and economic growth, others are still hedging against the possibility that inflation and war-related uncertainties could return at any moment.

The Russell 2000 also joined the rally, rising 0.30 per cent to 2,713.66, while the Dow Jones Industrial Average slipped 0.15 per cent to 48,463.72. This slight underperformance in the Dow suggests that the market favour is heavily skewed toward growth and technology rather than traditional industrial components.

Looking ahead, the market outlook for Bitcoin remains cautiously bullish, though it is heavily dependent on the continued transparency and volume of daily institutional reports. The key trigger for the next major move will be whether the momentum of these massive spot ETF inflows can be sustained throughout the week.

If the daily reports continue to show hundreds of millions of dollars entering the space, the psychological resistance at US$75,400 will likely crumble. Should the inflows dry up or turn into outflows, a pullback toward the US$73,549 swing low becomes a very real possibility. Investors must remain vigilant, as the current rally is built on the twin pillars of institutional support and fragile geopolitical hopes.

Also Read: Beyond the US$70K level: Why Bitcoin’s real test isn’t price yet

The transition from a speculative asset to an institutional one is nearly complete. Market participants now treat Bitcoin as a legitimate barometer of liquidity and risk. Every tick of the clock brings more data from providers like SoSoValue or Farside that dictates the near-term trend.

For the rally to continue, the support zone around US$74,479 must be defended at all costs. A failure there would signal that the institutional appetite is not as deep as current numbers suggest. Analysts are watching for a daily close above US$75,409 to confirm the next leg of the journey toward the US$76,559 mark.

Ultimately, the events illustrate a world where Bitcoin is no longer an outsider but a central character in the global financial narrative. I will keep watching the market.

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The post The US$76,000 question: Can institutional momentum sustain the current market breakout appeared first on e27.

Quick commerce has often been framed as a sub-sector: fast groceries, dark stores, and on-demand convenience. That framing is too narrow for Southeast Asia. What is happening now is not simply the rise of a new retail format. It is a deeper strategic shift in which e-commerce players are trying to capture a bigger share of everyday life, one urgent order at a time.

According to Ecommerce in Southeast Asia 2026 by MomentumWorks, quick commerce is becoming “a fight for user frequency, not a standalone business”. That is the right lens. The real prize is not a bag of milk, a phone charger, or late-night paracetamol. The real prize is habitual demand.

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

Once a platform becomes the default place consumers go for the next one hour, four hours, or same-day purchase, it stops being a shopping app and starts becoming an operating system for urban consumption.

Why frequency matters more than basket size

Traditional e-commerce in Southeast Asia was built around planned purchases. Consumers searched, compared, waited, and often bought non-urgent items such as fashion, beauty, home goods, gadgets, and seasonal promotions. Quick commerce changes the rhythm completely. Orders become smaller, faster, more local, and more frequent.

That matters because frequency is one of the strongest levers in platform economics. A consumer who orders twice a week is more valuable than one who orders once a month, even if the average order value is lower. More frequent behaviour means more data, greater payment engagement, more wallet share, and a higher chance of cross-selling into categories once considered outside the scope of e-commerce.

This is why quick commerce is strategically significant even if the unit economics remain tricky. It is a habit engine.

Southeast Asia is producing multiple models, not one dominant formula

MomentumWorks makes an important point that is often missed when investors compare Southeast Asia with India or China: the region does not yet have a single dominant fulfilment model for quick commerce.

In India, first-party dark stores have become the defining approach.
Southeast Asia looks messier. Shopee is using its on-demand fleet, often via ShopeeFood infrastructure, to pick up from e-commerce sellers for instant delivery. Grab is leaning on a partner-led model, integrating with existing supermarket chains and retailers. Lazada is pushing a more controlled first-party dark store model in selected areas, particularly through RedMart Now in Singapore. Foodpanda is extending pandamart. Independent players such as Astro in Indonesia, and FoodMax in Singapore are also still in the game.

That variety reflects the region’s structural reality. Southeast Asia is not one market. It is a patchwork of very different urban densities, retail systems, transport constraints, labour costs, and consumer expectations. A model that works in dense, affluent Singapore may not scale neatly in Jakarta, where traffic patterns, fulfilment complexity, and retail fragmentation create different constraints. Bangkok, Manila, Ho Chi Minh City, and Kuala Lumpur each add their own wrinkles.

Shopee, Grab, and Lazada are chasing different forms of relevance

The battle is not being fought by identical competitors.

Shopee’s push into instant delivery is defensive as much as offensive. TikTok Shop has changed how consumers discover products, but Shopee still has a strong logistics backbone and an embedded user base. By offering sub-four-hour delivery in five of six Southeast Asian markets, it is reinforcing a consumer proposition that users can feel immediately: speed.

Grab, by contrast, is extending an existing delivery ecosystem. Its expansion through GrabMart is less about reinventing e-commerce and more about monetising an installed network of riders, merchant relationships, and consumer trust around immediacy. For Grab, quick commerce is a natural adjacency to food delivery and mobility, not a wholesale bet on a new category.

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

Lazada’s approach is more selective and may offer higher margins. RedMart Now in Singapore suggests that Lazada sees quick commerce as a way to deepen engagement with premium households and high-frequency grocery demand, rather than chasing volume everywhere.
Each player starts with a different asset base. That is why the competitive end state remains unsettled.

The real map of demand is shrinking

One of the smartest ideas in the report is that platforms are starting to segment demand by proximity. Hyperlocal demand can be fulfilled within an hour. Local demand can often be served within four hours. Country-wide demand still belongs to conventional parcel logistics and next-day or scheduled delivery.

This seemingly simple shift has large implications.

It means inventory strategy becomes more important than pure assortment size. It means retailers with well-placed stores suddenly matter again. It means delivery fleets, mapping tools, and dispatch systems become strategic assets. It means brands have to decide which products belong in fast delivery, and which should remain in standard ecommerce. It means the geography of a city starts to shape platform economics in a far more direct way.

In short, the competitive map of e-commerce is shrinking from a nation to a neighbourhood.

Retailers and brands now face harder choices

Quick commerce not only changes platforms. It forces trade-offs across the entire ecosystem.

Brands must decide whether to build their own fast-delivery capability or partner with dominant platforms. They need to rethink pricing: should quick commerce carry a premium because of convenience, or be priced at parity to drive volume and customer acquisition? They must consider inventory placement, assortment design, and the role of local stores versus central warehouses.

Retailers face a different dilemma. Their physical footprint, once considered an analogue legacy, can become an e-commerce advantage if used as a fulfilment layer. But store-based picking can disrupt offline operations. That creates a tension between asset utilisation and operational simplicity.

For service providers and startups, the question becomes even sharper: where is the defensible layer? Pure last-mile delivery is increasingly commoditised. The more durable opportunities may lie in routing software, store operations, inventory intelligence, cold-chain logistics, or merchant tools that help brands navigate fragmented fulfilment models.

Southeast Asia’s cities make quick commerce plausible

The infrastructure base is stronger than it was a few years ago. Delivery fleets are bigger, dispatch systems are smarter, and consumers are more accustomed to app-based fulfilment. Large cities across the region are congested, mobile-first, and full of need-based purchases that still happen offline. That is fertile ground for quick commerce.

Also Read: Shopee, TikTok Shop, Lazada now control 84% of SEA’s e-commerce market

But the winner will not simply be the platform that delivers fastest. It will be the one that uses speed to deepen frequency, improve retention, and reshape consumer behaviour at scale.

In Southeast Asia, quick commerce is not about selling groceries faster. It is about owning the next urban habit. And the platform that wins habit usually wins far more than the basket in front of it.

The post Why quick commerce is really about frequency, not speed appeared first on e27.

There is a conversation happening in boardrooms across Singapore, Sydney, and Tokyo that almost never makes it into a marketing report.

Senior B2B marketers — the ones with the budgets, the data, and the track record — are quietly pulling spend away from digital channels. Not because digital doesn’t work. But because of their specific goal — getting in front of a CFO, a CTO, or a Chief Revenue Officer who actually controls the budget — it has become nearly impossible to break through.

I hear this every week. I run The Ortus Club, a B2B executive event agency that has hosted more than 2,500 invitation-only roundtable dinners, masterclasses, and summits across 40+ countries since 2015. Our clients are companies like Google, Visa, Meta, IBM, and Airwallex. And in the past 18 months, almost every single one of them has said a version of the same thing: digital is saturated at the top of the funnel. The executives we need to reach have stopped responding.

Our 2026 Event Marketer’s Playbook — which surveyed 295 senior B2B marketers across 30 cities — confirms what we are seeing on the ground. The shift is real, it is accelerating, and it is reshaping how the most sophisticated B2B brands in APAC are thinking about pipeline.

The executive attention problem is not going away

Let me give you the honest picture. A senior decision-maker at an enterprise company in Singapore receives, on average, somewhere between 100 and 200 unsolicited outreach messages per week across email, LinkedIn, and WhatsApp. Their EA screens calls. Their LinkedIn inbox is a graveyard of unanswered connection requests. Their email filters have become extraordinarily sophisticated.

The traditional B2B playbook — awareness campaign, gated content, MQL handoff to sales, SDR follow-up sequence — was designed for a world where digital channels were still relatively low-noise. That world is gone. What has replaced it is a senior executive who has essentially become unreachable through conventional means, and a generation of marketing teams who are still measuring success by the number of form fills.

What the data from 295 marketers actually shows

Across the 295 senior B2B marketers we surveyed for the 2026 Event Marketer’s Playbook, three findings stood out.

First, in-person executive events now rank as the single highest-ROI channel for pipeline generation at the enterprise level, ahead of paid social, content marketing, and outbound SDR programmes. This is not a soft preference — it is a commercial finding based on deal velocity and average contract value.

Second, the most cited reason for increasing event budgets in 2026 is not brand awareness. It is trust acceleration. Marketers told us repeatedly that a 90-minute dinner conversation compresses a sales cycle that would otherwise take six to nine months of digital nurturing. The decision-maker who sat across the table from your CEO at a roundtable last Tuesday is not the same prospect as the one who downloaded your whitepaper.

Also Read: Pre-launch marketing is a tease that works, how to get it right?

Third, the format matters enormously. Traditional conferences and trade shows are losing share to smaller, curated, invitation-only formats. The reason is simple: executives will not give up three hours of their time for a room of 500 people, but they will clear their calendar for a dinner of twelve where everyone in the room is relevant to them.

Why is this particularly true in APAC

Southeast Asia is not a monolith, and any B2B marketer who treats it as one will struggle. The relationship dynamics that govern enterprise purchasing decisions in Singapore are fundamentally different from those in Jakarta, Bangkok, or Kuala Lumpur. In most of this region, business does not happen between companies — it happens between people who have met in person, established trust, and decided they want to work together.

This is not a cultural observation. It is a commercial one. The B2B brands that have built the deepest enterprise pipelines in APAC over the past decade are almost universally the ones that have invested in face-to-face executive relationships — not the ones with the most sophisticated marketing automation stacks.

Digital channels are absolutely necessary for awareness and reach. But in APAC’s enterprise market, they are not sufficient for conversion. The gap between a warm digital lead and a signed contract is filled by human interaction, and the most efficient way to create that interaction at scale is through curated executive events.

What to actually do about it

If you are a B2B marketing leader reading this and your pipeline is heavily dependent on digital channels, here is what I would look at first.

Map your top 50 target accounts and ask honestly: which of those decision-makers have we had a real conversation with in the last six months — not a demo, not a webinar, an actual conversation about a problem they have? If the answer is fewer than ten, you have a relationship gap that no amount of retargeting spend will close.

Second, consider whether your events strategy is built for volume or for quality. A 500-person conference appearance and a 12-person invitation-only roundtable dinner are not the same thing. One builds brand awareness. The other builds a pipeline. You probably need both, but most B2B marketing budgets are still heavily skewed toward the former.

Third, think about what you are actually offering the executive when you invite them. The invitation-only format works because the value proposition to the guest is explicit: you will spend 90 minutes with 11 other senior leaders who share your challenges, in a pitch-free environment where you can speak candidly. That is a genuinely compelling offer. A webinar about thought leadership trends is not.

Also Read: Why traditional marketing fails for complex B2B and deeptech products

The harder truth

The brands that will struggle most in APAC’s B2B market over the next three years are not the ones with the smallest budgets. They are the ones that continue to optimise for the wrong metrics — click-through rates, MQL volumes, cost per lead — while their competitors are quietly building the executive relationships that actually convert.

The executives who matter most are not hiding. They are simply waiting to be approached in a way that respects their time and treats them as peers rather than targets.

That is a harder thing to build than a campaign. But it compounds in ways that a campaign never can.

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

The post The quiet exodus: Why APAC’s B2B marketers are ditching digital marketing for executive dinners appeared first on e27.

Every week, a founder somewhere in Southeast Asia sends a polished deck to an impact fund. The numbers are real. The mission is genuine. Three months later: silence.

They assume the deck wasn’t good enough. They tighten the narrative. Apply again. Same silence.

The deck was never the problem.

The myth: Impact funds are just VCs with a conscience

Most founders approach impact funds the same way they approach any VC, growth story, TAM slide, compelling founder narrative. That’s the first mistake.

Impact funds are not VCs with an ESG checkbox. They operate under completely different internal logic. Mandates tied to specific theories of change. LPs who care about measurable social outcomes, not just returns. Some can only deploy grants, blended finance, or catalytic capital, instruments that have nothing to do with equity.

When a founder sends an equity pitch to a fund that can only deploy grants, it doesn’t matter how good the deck is. The application fails before anyone reads slide two.

The reality: It’s a fit problem, not a writing problem

In my experience mapping 100+ impact programs across SEA, fewer than 30% are genuinely open to cold applications. The rest require a warm intro, a prior relationship, or a very specific instrument match that’s never published.

Here’s what most founders don’t know: impact funds rarely publish their real criteria. The website says “we invest in climate, health, and financial inclusion across SEA.” What it doesn’t say is that their last six investments were all health-only, all in Vietnam, all at Series B, structured as convertible notes with a three-year impact reporting requirement.

That’s not on the website. You learn it by being in the room.

Also Read: Why non-dilutive capital is the smarter first move for SEA founders in 2026

Three fit questions that actually matter, before you write a single word:

• Does your instrument type match what the fund can actually deploy?
• Does your geography and sector match their last five investments, not just their stated mandate?
• Is this fund relationship-first or application-first? (Some have never funded a cold application in their history.)

The fix: Do the work before the application

Before you open any application form, answer these:

• What instrument does this fund deploy, and does it match what you need?
• Who have they funded in the last 24 months, and do you look like those companies?
• Is there a warm intro available, or is this fund genuinely open to cold applications?
• What does their theory of change require you to prove, and can you prove it with your current data?

If you can’t answer all four, you’re not ready to apply. You’re ready to research.

The uncomfortable truth

The impact funding ecosystem in SEA has a discovery problem. The funds exist. The capital exists. The mandate overlap with what founders are building is real.

But the information is asymmetric. Funds know exactly what they want. Founders are guessing.

That gap, between what’s published and what’s actually fundable, is where most applications die. Not in the writing. Not in the pitch. In the research that should have happened before any of it.

The founders who figure this out stop chasing every fund that looks relevant and start treating fund selection like due diligence. Fewer rejections. More callbacks. And eventually, they stop wondering why the silence.

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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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Vietnam-based Farmnet, the trading arm of agricultural supply chain company TechCoop, has secured a US$11.75 million senior secured loan from Geneva-headquartered impact investor Symbiotics, in a deal that says as much about the country’s funding climate as it does about agritech.

While it is a financing announcement on paper, it is a sign that some startups in Vietnam are no longer waiting for venture capital to loosen up.

TechCoop claimed that the facility is the first offshore institutional loan raised by one of its Vietnam-incorporated entities.

Farmnet will use the money as working capital to support higher trading volumes with processors, co-operatives and small and medium-sized agricultural enterprises across the country.

Also Read: Techcoop CEO on scaling agritech, sustainable farming, and global expansion

That makes sense because Farmnet is not a software startup chasing growth with a burn-heavy model. It sits in the plumbing of Vietnam’s farm economy: buying, moving, and selling agricultural commodities across a fragmented supply chain that often struggles to access reliable financing.

In simple terms, Farmnet helps connect the people growing and processing farm produce with the buyers who need it, while helping finance the movement of those goods along the way. It trades products including cassava, coconut, cashew, durian, coffee, fresh fruit, and processed goods and says it operates in 20 locations nationwide, serving more than 641 co-operatives and agricultural enterprises.

There is nothing flashy about that business. That is precisely the point.

Why a loan, not another venture round?

For a company like Farmnet, debt can make more sense than equity.
Commodity trading is a working-capital business. Companies need cash upfront to buy produce, pay suppliers, manage inventory, and settle transactions before revenue comes back in. That is very different from the typical venture-backed pitch built around user growth, product development and long-term optionality.

A loan fits that operating model more neatly. It gives Farmnet capital for buying and moving goods without forcing TechCoop to dilute shareholders before it needs to. The company has already said the financing is part of a broader capital strategy that includes a planned Series B equity raise later this year, suggesting the debt is not replacing venture funding entirely but complementing it.

The choice also reflects the harsh reality of fundraising in Vietnam. Raising venture capital has become more difficult for many startups, especially outside consumer internet and pure software plays. Investors remain active, but they are more selective, more valuation-sensitive and far less willing to fund growth at any cost than they were during the peak years of 2021 and early 2022. That has pushed founders towards structures that are more disciplined and more closely tied to cash flow.

So, yes, the tougher VC market is part of the story. But it is not the whole story. Farmnet’s debt raise also appears to be a rational financing decision for a business whose growth depends on trade flows, not just product milestones.

Why Symbiotics and TechCoop fit together

The loan also highlights a straightforward commercial alignment between lender and borrower.

Symbiotics specialises in impact investing, with a long history of backing financial inclusion and businesses that serve underserved parts of the real economy. Vietnam’s agricultural supply chain aligns well with that mandate. Agriculture and fisheries accounted for 11.86 per cent of Vietnam’s GDP in 2025, according to the National Statistics Office, yet large parts of the sector remain underfinanced and structurally fragmented.

Around 70 per cent of farms in Vietnam operate on plots smaller than 0.5 hectares, which makes aggregation, logistics and financing more difficult. In that environment, a trader with distribution reach and established relationships can become a key market enabler.

Also Read: Techcoop secures US$70M in one of Vietnam’s largest agritech funding rounds

That is where the synergy sits.

For Symbiotics, the deal offers exposure to a business tied to real-economy activity, rural livelihoods, and supply chain efficiency — all areas that align with impact objectives, while still being anchored in a revenue-generating trading model.

For TechCoop, the benefits are equally clear. It gains access to offshore institutional capital, adds balance sheet strength, and receives external validation from a specialised lender. That should help it finance larger trading volumes and deepen relationships with processors, co-operatives and agricultural SMEs that need dependable counterparties.

In other words, Symbiotics gets measurable impact with commercial structure. TechCoop gets capital that matches how its business actually works. Everyone avoids pretending a commodities platform is just another venture-backed app.

What Farmnet plans to do with the money

The immediate use of proceeds is working capital, but that should not be read as routine housekeeping.

For Farmnet, working capital is what allows the engine to run faster. The company said the money will support increased trading activity across its network of processors, co-operatives and small and medium-sized agricultural enterprises. In practical terms, that means greater capacity to purchase commodities, manage transaction cycles, and serve counterparties that may not have strong access to financing.

That could be especially important in sectors where timing matters. Agricultural trade is full of cash-flow mismatches: growers and processors need payment certainty, while buyers often operate on different terms. A better-capitalised intermediary can reduce friction in that chain.

The facility should also strengthen TechCoop’s platform ahead of a broader regional push. The company has said parent firm TechCoop Investment & Technology, headquartered in Singapore, plans to expand into Cambodia, Laos and Thailand in 2026.

How common are loans and venture debt in Vietnam?

Not very, at least not yet.

Debt financing and venture debt remain relatively niche among Vietnamese startups compared with traditional equity rounds. Most early-stage founders still rely on angel money, seed funds, venture capital or, where possible, bank lending. The trouble is that banks often want collateral, profitability or longer operating histories, which many startups do not have. Venture debt providers, meanwhile, are fewer in number and tend to focus on businesses with stronger revenue visibility.

That leaves a financing gap.

For startups with real cash flow, repeat customers and tangible operating cycles, debt is becoming more attractive. It is particularly relevant in sectors such as fintech, B2B commerce, agritech and supply chain infrastructure, where capital is often needed to finance transactions rather than speculative customer acquisition.

But it would be a stretch to call venture debt mainstream in Vietnam today. The market is still developing, and founders remain more familiar with equity than structured credit. Farmnet’s transaction stands out partly because such deals are still uncommon, especially from offshore institutional lenders.

How much capital has TechCoop raised so far?

Based on the information publicly disclosed in this announcement, US$11.75 million is the latest and most clearly stated financing amount tied to TechCoop through Farmnet, and it marks the first offshore institutional borrowing by a Vietnam-incorporated TechCoop entity.

TechCoop has also said it is preparing a Series B equity round later this year. However, the company has not detailed in the source material the full amount of capital it has raised to date or the exact number of previous rounds. What is visible is a business now combining debt and equity as part of a more layered capital strategy.

That is notable in itself. Startups tend to signal maturity when they stop treating financing as a one-lane road.

Vietnam’s startup market is still cautious

Farmnet’s raise lands at a time when Vietnam’s broader startup investment market remains under pressure.

The country is still one of Southeast Asia’s more promising digital economies, but capital deployment has been slower, dealmaking more selective and late-stage funding harder to secure than during the boom period. Investors are spending more time on unit economics, governance and margins. Large cheques are rarer. Bridge rounds, structured financing and alternative capital have become more relevant.

Also Read: A new era of impact: Beyond the bottom line in Southeast Asia’s tech revolution

That does not mean Vietnam is out of favour. It means the bar is higher.
Against that backdrop, Farmnet’s loan looks less like an exception and more like a preview. Startups tied to essential sectors, with visible revenue and financing needs linked to actual transactions, may find lenders increasingly receptive — especially when the business supports supply chains that are critical to the wider economy.

For TechCoop, the message is simple: if equity is expensive and banks are not built for startup realities, debt from the right institutional partner can be the fastest way to keep goods moving.

And in Vietnam’s agricultural economy, moving goods is still where the real money gets made.

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For more than a decade, the landscape of student devices has been dominated by two categories: Chromebooks and tablets. Both are affordable, easy to manage, and good enough for the standard classroom toolkit — note-taking, online research, and structured learning platforms. They solved the budget problem. What they couldn’t quite solve was the capability ceiling.

A new entrant may quietly shift that balance.

The MacBook Neo, with a starting price around $599 and roughly $499 with student pricing, brings something historically absent at this price point: a full laptop running a desktop operating system within the cost range typically occupied by Chromebooks and entry-level Windows devices.

That doesn’t automatically make it the right device for every student. But it introduces a genuinely new option in the education technology conversation — and the implications for how we think about student computers are worth examining.

Four philosophies of student computing

To understand what the Neo offers, it helps to understand what each major device category was actually designed to do.

Rather than asking which device is “best,” the more useful question is: which design philosophy fits the student in front of you

Chromebook: The web-first model

Chromebooks became popular in education because they solve several practical problems simultaneously. They are inexpensive, lightweight, easy to manage at scale, and tightly integrated with the cloud productivity tools that now define most classroom workflows — essays in Google Docs, assignments on learning platforms, collaboration through shared documents.

For this kind of work, Chromebooks are perfectly adequate.

The trade-off emerges at the edges. More advanced computing tasks — running development environments, compiling programs, experimenting with system-level tools — are more constrained in ChromeOS than on traditional desktop systems. For most students, this may never matter. But for those who grow curious about how software actually works, the ceiling eventually becomes visible.

iPad: The touch-first learning model

Tablets take a different angle entirely. Rather than prioritising keyboards and file systems, they emphasise touch interaction, digital handwriting, and creative applications.

For many subjects, this is genuinely powerful. Students can annotate documents, sketch diagrams, record voice notes, and interact with educational apps in ways that feel immediate and natural. The iPad ecosystem excels at note-taking, drawing, and multimedia creation in ways that no laptop quite replicates.

The constraint, again, is at the boundary. Tablets are built around mobile operating systems. When students need to move beyond app-centric workflows — learning to program, running technical tools, working within a traditional file system — the environment can feel more limited than the task demands.

Also Read: Why AI literacy is the new core skill for 21st-century educators

Surface Go: The portable Windows PC

Microsoft’s Surface Go occupies an interesting middle ground. It offers a full Windows environment in a highly portable device, typically paired with a detachable keyboard.

This means students can run the same software ecosystem common to many professional and academic settings, including Microsoft Office, development environments, and specialised research tools. The Surface line makes an important argument: some students benefit meaningfully from access to a full operating system rather than a purely app-based environment.

The honest trade-off is hardware performance. At this price tier, the Surface Go’s specifications are modest, and battery life and processing speed can vary. But the philosophy it represents — full OS, real portability — is a sound one.

MacBook Neo: Full desktop computing at a lower price

The MacBook Neo is interesting because it does something that previously required a substantially larger budget.

For years, macOS laptops were positioned firmly as premium devices. Students who wanted access to the macOS ecosystem needed a MacBook Air or Pro — both significantly more expensive than entry-level education hardware. The Neo changes this equation.

At roughly $499 with student pricing, it places a macOS laptop in a price band historically occupied by Chromebooks and basic Windows machines. That matters because macOS is not just another operating system — it provides a full desktop computing environment with a Unix-based terminal, native development tools, and broad compatibility with professional applications across software engineering, data science, and design.

A student curious about programming, data analysis, or systems work can experiment with the same environment used widely across industry and academia, without a premium-device budget.

The Neo achieves this price point through deliberate compromises. The base configuration includes 8GB of memory, and connectivity options are more limited than those of higher-end models. For typical student workloads, neither limitation is likely to bite. But they are real and worth acknowledging before purchase.

The chip inside the Neo also deserves a moment’s attention. Rather than the M-series silicon found in the MacBook Air and Pro, the Neo runs on Apple’s A18 — the same chip family that powers the iPhone. This is not a downgrade so much as a deliberate economic move. Apple is leveraging iPhone-scale manufacturing to bring down the cost floor of laptop computing: a classic disruption from below, using existing platform economics to enter a new market tier. The A18 is not a weakened M-chip; it is a different optimisation entirely. Its 16-core Neural Engine — capable of on-device AI inference — is arguably over-specified for today’s classroom workflows. But not for tomorrow’s. As AI tools become embedded in how students research, write, and code, having capable edge inference in the palm of a student’s hand will stop looking like overkill.

Also Read: AI integration field notes for tech startups and scale-ups: Software engineering, product, and beyond

Side-by-side comparison

Each device prioritises a different dimension of the learning experience. The table doesn’t declare a winner — it maps the trade-off space.

One cost the table doesn’t capture: the external mouse. Apple’s trackpad ecosystem is also unusually strong. Because hardware, firmware, and operating systems are designed together, MacBook trackpads tend to behave consistently across models. In practice, many users find they no longer need to carry an external mouse — something that is less consistently true across the fragmented Windows laptop ecosystem.

The creator-consumer spectrum

One productive way to think about these devices is along a spectrum.

At one end are devices optimised for consuming and interacting with content: reading, writing, watching, and participating in structured lessons. Tablets and web-first laptops excel here, and for the majority of student workflows today, this is precisely what is needed.

At the other end are devices designed to make it easier to create, experiment, and explore computing more deeply — writing code, analysing data, running development tools, and understanding how operating systems behave. These tasks require a full computing environment.

The MacBook Neo becomes significant because it lowers the cost of entry into the second category. It doesn’t eliminate the trade-offs, but it moves the price barrier.

Longevity and capability

There is a subtler consideration that device comparisons rarely surface: students keep their primary device for several years, and the demands on that device tend to grow.

There is also something worth naming that spec sheets never say. As a parent of school-going children, I find myself asking a different question entirely: what kind of relationship with computing am I putting in my child’s hands?

A Chromebook is an excellent device for a child who uses the web. A MacBook Neo, with its Unix terminal and native development tools, is a different kind of invitation — for the child who wonders how the web works. That is not a hierarchy of worth; many students will not need or want to peer under the hood. But for the ones who might, the device either opens a door or quietly closes it. A terminal matters. A file system you can navigate and modify matters. The ability to run a local server, experiment with Python, or compile something matters — not because every student will do those things, but because the ones who will should not be penalised by the hardware they happened to start on.

Also Read: Malaysian SMEs grapple with a growing “confidence gap” in AI adoption

A system that handles Year 1 comfortably may feel genuinely constrained by Year 3, when coursework involves Python for data analysis, statistical tools, machine learning libraries, or small software projects. A more flexible computing environment doesn’t just serve current tasks — it preserves optionality as interests and requirements evolve.

Not a replacement , a new option

No single device category will dominate all educational contexts, nor should it.

Chromebooks remain excellent for web-centric learning environments. Tablets continue to shine wherever handwriting, sketching, and multimedia creation are central. Portable Windows machines offer compatibility with a wide range of existing software. Each philosophy addresses a real set of student needs.

What the MacBook Neo introduces is a fourth option that previously didn’t exist at this price: the combination of laptop simplicity and full desktop OS capability, accessible without a premium-device budget.

A subtle shift

The most interesting thing about the MacBook Neo may not be its specifications. It is the fact that a desktop-class laptop has entered a price range historically defined by lightweight web devices.

Whether this translates into widespread adoption in schools remains to be seen. Institutional purchasing decisions are slow, and the Chromebook ecosystem has deep roots.

But the Neo quietly unsettles an assumption that has shaped education computing for a decade: that affordability and capability must be traded against each other. For the student who is not just learning with a computer, but learning about computers , that unsettling may matter more than any benchmark.

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

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

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After years of expansion and strong funding, Southeast Asia’s startup environment has shifted. Capital is tighter, investor scrutiny is higher, and startups face increasing pressure to demonstrate value and sustainable growth.

The region remains one of the world’s most dynamic innovation markets. Companies across AI, fintech, SaaS and climate technology continue to launch and scale.

In the early stages, a company’s story is often simple. Founders focus on solving a specific problem for a defined market. But as startups scale — expanding across products, markets, funding stages — clarity can fade. Over time, the company become harder to understand.

In a crowded ecosystem, with thousands of companies competing for the attention of investors, partners and customers, narrative clarity becomes a strategic advantage.

Growth multiplies complexity

As startups expand, organisational and communication complexity often grows faster than leadership teams anticipate. Products launch, markets expand, teams scale and investor expectations evolve. Over time, messaging can fragment:

• One narrative is used for investors, another for customers
• Sales teams describe the value proposition differently across markets
• Product updates shift how the company is perceived
• Website content falls behind the actual business
• Marketing campaigns emphasise different messages each quarter

None of this is intentional. It’s a natural by-product of growth.

But when positioning becomes inconsistent, the result is friction — internally and externally.

Internally, unclear positioning slows decision-making and dilutes marketing effectiveness. Externally, customers, partners and investors may struggle to understand what the company represents.

Also Read: Avoiding costly mistakes: How cognitive biases can affect entrepreneurs

What differentiates firms is how clearly they communicate their value across corporate, technology, product and customer levels.

Southeast Asia’s most successful technology companies demonstrate this clearly. Companies such as Grab, Sea Group and Gojek built powerful narratives around financial inclusion, digital commerce and the transformation of everyday services. Their positioning helped shape how markets, investors and consumers understood their role in the region’s digital economy.

Narrative clarity is more than a tagline

Narrative clarity is often misunderstood as branding or messaging. In reality, it sits deeper within a company’s strategy.

It is the disciplined articulation of how a company defines itself in the market — the clear, consistent explanation of the problem it exists to solve, the unique approach it brings, and why it matters.

At its core, narrative clarity answers three fundamental questions:

• What important problem exists, and why is it becoming urgent now?
• How does our company uniquely solve it?
• Why are we the right company to lead this shift?

When these questions are answered clearly and repeated consistently, the company’s story becomes easier for investors, customers, partners and employees to understand — and easier for the market to remember.

It shapes investor narratives, website content, marketing campaigns, sales materials and conversations, media commentary and executive thought leadership.

Instead of each team creating its own version, the organisation operates from a shared narrative. Clarity creates coherence. Coherence builds recognition. Recognition builds trust.

Also Read: Value creation: The compression principle — How to edit your pitch down to its atomic core

Why narrative clarity accelerates growth

When positioning is clear and consistent, its impact compounds across teams, channels and markets.

• First, it aligns internal teams. Marketing, sales, product and leadership operate from the same narrative framework, allowing campaigns and resources to reinforce a consistent message.
• Second, it strengthens market recognition. Buyers and partners encounter brands through multiple touchpoints — media coverage, LinkedIn, industry events and analyst commentary. When each interaction reinforces the same narrative, recognition builds. And recognition builds trust.
• Third, it strengthens PR and thought leadership. Journalists and industry stakeholders gravitate toward companies with a clear point of view. When a company consistently speaks about a specific challenge or industry shift, it becomes associated with that conversation.
• Finally, it supports regional expansion. Southeast Asia is not a single market. Regulatory environments, buyer maturity and competitive dynamics vary across Singapore, Indonesia, Vietnam, Thailand and the Philippines. A strong narrative core allows companies to adapt locally without losing strategic coherence.

Why narrative clarity matters now

Southeast Asia’s startup ecosystem is challenging. Investors are evaluating companies more carefully in a tighter funding environment. Customers are comparing vendors across borders. Talent is increasingly drawn to organisations with clearly defined missions and direction.

Startups that establish narrative clarity early gain an advantage. They build investor confidence, shape industry conversations, attract strategic partners, and stand out in crowded markets.

As the region’s innovation economy grows, the companies that scale most successfully will not simply be those with strong technology.

They will be the ones the market understands — and remembers.

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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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