After more than 16 years working as a financial advisor in Singapore, I’ve noticed a change that I didn’t expect to see this early. Some of the most financially engaged conversations I’m having today are not with people approaching retirement or preparing for their children’s education. They’re young adults in their late teens and early twenties.

When I began my career in finance, it was common for people to start thinking about financial planning only after significant life events like getting married, buying a home, or becoming a parent. However, I’ve noticed a shift with many Gen Z Singaporeans initiating these important discussions much earlier in their lives. 

At first, it might seem like this trend is driven by social media, financial influencers, or easier access to information. While those elements do play a part, I sense there’s something more profound at work. The young adults I encounter today are navigating a very different economic landscape compared to what my generation faced.

A generation responding to economic reality

Today, a significant number of young Singaporeans are grappling with a genuine housing challenge. According to transaction data from 2025, the average resale HDB flat in Singapore is priced around SG$652,000 (US$504,039), while a typical condominium costs about SG$2.13 million (US$1.65 million), and a landed property can reach nearly SG$5.93 million (US$4.59 million). This stark reality has made housing affordability a central topic in financial discussions.

The broader market reflects this pressure. According to Reuters, Singapore’s HDB resale prices rose 9.6 per cent in 2024, nearly double the growth recorded the year before. For many young adults, homeownership remains achievable, but the financial runway required to get there has become significantly longer.

During the COVID-19 era, Gen Z stepped into adulthood under unique circumstances. Unlike earlier generations, many faced layoffs, business closures, and economic instability while growing up. These experiences have undoubtedly shaped their perspectives. What truly fascinates me is not just that Gen Z is starting to plan for their futures sooner, but also the reasons behind this proactive approach.

What Gen Z is actually asking

Younger consumers are often thought to be mainly focused on investing, trading, or quickly finding ways to increase their wealth. However, my observations tell a different story.

Also Read: How tech startups can attract Gen Z and millennials seeking flexibility and purpose

The questions I hear most often are surprisingly practical:

• Should I build an emergency fund before investing?
• How much insurance do I actually need?
• How do I prepare for buying a home in Singapore?
• What happens if I lose my income unexpectedly?
• How do I enjoy life now without compromising my future?

These are not questions about getting rich. They are questions about creating stability. That aligns with broader research. Deloitte’s 2025 Gen Z and Millennial Survey found that the cost of living remains one of the top concerns among Singapore’s Gen Z, while younger workers are increasingly prioritising financial security, well-being, and sustainable career growth over traditional status markers.

It’s fascinating to see that younger Singaporeans are starting to build their financial habits much earlier than many might think. According to a SingSaver survey, a remarkable 85 per cent of Gen Z participants began saving before turning 22, in stark contrast to only 41 per cent of Millennials. The study also revealed that Gen Z individuals are more inclined to adhere to a budget compared to their older counterparts.

These insights truly resonate with my daily experiences. I’ve noticed that many young adults are engaging in financial planning not out of a desire for wealth, but rather to cultivate a sense of resilience in their lives.

The rise of the “invisible financial cage”

As I reflect on my journey, I’ve come to realise that financial planning transcends mere monetary concerns; it’s fundamentally about the choices we can make. I often refer to the concept of the “invisible financial cage.” This describes individuals who, despite seeming successful outwardly, lack the freedom to make choices that truly enhance their lives. They may find themselves stuck in jobs detrimental to their well-being, delaying significant life decisions, or enduring tough situations simply because they feel trapped by their financial circumstances.

Throughout my career, I’ve had the privilege of working alongside senior bankers, business owners, and executives who, despite their impressive earnings, often feel confined. It’s important to recognise that earning a high income doesn’t necessarily equate to true financial freedom.

Early in my career, I encountered a 29-year-old accident victim whose insurance payout fell short for long-term disability support. Witnessing the real-life impact of poor planning profoundly shifted my perspective on this profession. It taught me to see financial planning not just as a means to accumulate wealth but as a way to build a protective safety net for individuals and families. This understanding also influences my views on Gen Z and their financial needs.

What I see is not a generation obsessed with wealth. I see a generation trying to build resilience.

Also Read: A millennial’s perspective on working with Gen Z

What businesses often misunderstand about Gen Z

A common misconception about Gen Z is that they are reckless with their finances or solely focused on making quick money. In reality, my experiences reveal a different perspective. Many young individuals approach their financial matters with care and consideration. They dedicate significant time to understanding their options, seeking out educational materials, and comprehending the motivations behind their financial choices before taking action.

They tend to be more careful with their finances compared to earlier generations. This change is significant for financial institutions, insurers, and fintech companies. Many young consumers prioritise understanding over simply seeking out products.

Young consumers are seeking knowledge before receiving suggestions. They desire a deeper understanding before making commitments. Building trust is becoming essential in today’s market. Companies that thrive with Gen Z will be those that empower individuals to make informed choices, rather than just pushing more products on them.

Why this matters beyond financial services

For employers, there’s an important takeaway. Financial well-being is becoming a significant concern in the workplace. Employees grappling with worries about housing costs, debt, healthcare bills, or their future security carry these burdens with them, even into the office.

As organisations continue investing in employee well-being initiatives, financial education and planning support may become increasingly important components of that conversation. The scale of the challenge facing younger Singaporeans is evident in the housing market. Reuters reported that Singapore recorded a record number of million-dollar HDB transactions in 2025, highlighting how dramatically financial expectations and planning timelines have shifted compared to previous generations.

Looking ahead

Having spent 16 years in this field, I’ve come to realise that Gen Z’s increasing focus on financial planning goes beyond just finance. It’s about their need to adapt. With rising costs, extended financial timelines, and more uncertainty than earlier generations faced, young Singaporeans are stepping up to take charge of their financial futures sooner than ever.

This could lead to a generation that transforms the very essence of financial planning. From my perspective, that might actually be a positive change.

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The post Why Singapore’s Gen Z handles money differently and what it means for finance appeared first on e27.

An AI model judged too dangerous to release has exposed an uncomfortable truth: the legacy systems quietly running our banks, hospitals, and power grids are far more vulnerable than we let ourselves believe. The threat isn’t old code — it’s abandoned code. And the response isn’t a patch. It’s a fundamental rethink of how we build, defend, and value software.

For forty years, the smartest thing you could say about a critical system was four words: it works, don’t touch it.

That was wisdom. Stillness was a virtue. The system that ran untouched for a decade had earned its keep. Every night it read a number, did some math, wrote the number back, a million times without a mistake. You didn’t audit it. You didn’t rewrite it. You built a glossy app on top and left the engine alone, the way you’d leave a load-bearing wall alone.

I want to argue that something just quietly reversed that logic. The very stillness that earned our trust — unexamined, unchanged, unread — is now precisely what makes a system dangerous. The code didn’t move. The world around it did.

What changed

In April 2026, Anthropic announced a model it decided the public could not have.

It’s called Claude Mythos Preview, and the company chose not to release it. Instead, they handed it to a coalition of roughly fifty critical-infrastructure organisations — AWS, Google, Microsoft, Apple, Cisco, JPMorganChase, the Linux Foundation among them — under a program called Project Glasswing. The idea was to let the defenders patch before the rest of the world caught up.

Read that again. A technology company built something and then concluded the responsible move was to withhold it. That alone should make you sit forward.

What does Mythos do? It reads code and finds the ways code breaks. Pointed at OpenBSD — an operating system hardened by some of the best security minds alive for decades — it surfaced a flaw that had been hiding for twenty-seven years. Pointed at a ubiquitous video library, it found a bug in a single line that automated tools had run past five million times. And when asked not merely to find a weakness but to weaponise it, the model that came before it succeeded almost never. Mythos succeeded most of the time.

The reaction told you everything. Within weeks, the US Treasury Secretary and the Fed Chair pulled major bank CEOs into a room. India’s Finance Minister convened the RBI and the heads of the banks. The European Central Bank called an urgent meeting. Central bankers across the world held emergency sessions about a model they are not even allowed to use.

And the containment failed almost immediately. The model leaked — not through some cinematic hack, but through borrowed credentials from a contractor and a guessed web address. Even fifty handpicked partners couldn’t hold it for a day. Anthropic itself estimates that comparable capability, including in open form, becomes broadly available within roughly twelve to eighteen months.

So that’s the clock. Eighteen months to confront what we’ve avoided for thirty years.

It was never really about COBOL

The easy version of this story is about old banking mainframes. By widely-cited if aging industry estimates, COBOL still underpins something like 95 per cent of ATM transactions, and hundreds of billions of lines of it remain in production. Some single banks run three hundred million lines at their core, written in the 1980s, last understood by people who have since retired or died.

That story is true. But it’s too small.

Mythos doesn’t read COBOL. It reads code. It does not care whether the lines were written in a language older than the moon landing, or in a framework that felt modern in 2012. What it hunts is not age. It is abandonment — code that nobody owns, nobody reads, nobody fully understands anymore, still quietly wired to the network, still moving something that matters.

Also Read: Why the US tech rebound matters for SEA’s AI and venture ecosystem

And here is the trap most leaders will walk straight into: the belief that building something new makes them safe.

It doesn’t. Newness isn’t a state of safety. It’s the first day of a countdown. That twenty-seven-year-old flaw was, once, a fresh commit written by a careful engineer who believed it was correct. Every piece of legacy code was somebody’s clean, modern, well-intentioned new code. Age didn’t make it vulnerable. Time merely revealed what was always there, while nobody was looking again.

In one specific way, new software is more exposed, not less. The old mainframe was a windowless bunker — dangerous because nobody had the map, but also sealed, air-gapped, sitting in obscurity behind decades of forgetting. The thing we build today is a glass house. It lives on the public internet by default. It speaks through a hundred APIs. And it is assembled — not written, assembled — from a thousand prefab parts shipped in from open-source factories none of us inspected. The infamous Log4Shell crisis wasn’t old code failing. It was modern code importing a tiny utility nobody had read, inside nearly everything. We didn’t write that bug. We installed it.

Then comes the sharpest irony of this exact moment. The same AI revolution that produced Mythos is also flooding the world with machine-generated code faster than any human can read it. We are manufacturing tomorrow’s abandoned systems today, at industrial scale, and calling it productivity. The gap between lines written and lines understood has never been wider. That gap is the attack surface.

So the variable was never age. It was attention.

Where stillness is most sacred

Now widen the lens past banking to where “don’t touch it” is treated as scripture.

Utilities run operational technology often older than the banking code, because you do not casually reboot a power grid to install a patch. Hospitals run frozen embedded systems inside MRI machines and infusion pumps, certified once and never touched again. Logistics, water, energy, public records — the systems a country actually rests on — much of it held together by the quiet assumption that nobody was looking.

This isn’t hypothetical. We’ve already seen it at human speed. A piece of malware once erased a global shipping giant’s entire logistics backbone in hours; the company survived partly because a single server in Ghana happened to be offline. A worm walked into the national health service through unpatched machines and turned ambulances away.

Those attacks were carried out by people. Slow, tired, fallible people. Now imagine the same intent, equipped with something that never sleeps, never retires, and no longer needs a hunch.

The honest comparison, and where it breaks

The instinct is to call this Y2K again, and that instinct is half right.

Y2K is the right metaphor for the mobilisation. A vast inventory of legacy code, a global scramble, a deadline, and an enormous surge of demand for people who could go in and fix it. That surge is, quite literally, what built the modern Indian IT industry — Infosys, TCS, and Wipro booked the work, earned the trust of Western clients, and never looked back.

But Y2K is the wrong metaphor for the threat. Y2K was bounded, dated, and deterministic. Everyone knew the deadline, the failure, and the fix. You could declare victory at one minute past midnight and go home.

This has no midnight. It is open-ended and adversarial. There is no single patch, no finish line, no moment when you are done. The discovery engine keeps improving while you sleep. So if you take only one lesson from Y2K, don’t take “there will be a project.” Take “there will be a permanent capability — and someone will own it.”

Also Read: The sovereign AI moat: Why integrated risk is the only way to scale intelligence in 2026

There is no fix, there is a posture

This is the part nobody wants printed on a slide. There isn’t a fix — because we’ve been misnaming the problem the whole time. We thought we had a maintenance problem. We have a metabolism problem.

A building, once built, can stand untouched for a century. We quietly borrowed that mental model for software — construct it, certify it, occupy it, walk away. But software was never architecture. It’s closer to something alive. And living things that stop renewing don’t hold steady; they rot. We simply couldn’t see the rot because nothing was poking at the body. The system looked healthy because no one was testing whether it still was.

So if there’s no fix, what’s left? A change of posture. From building to tending. From done to alive.

That sounds soft until you make it concrete, and then it turns brutal. You can no longer answer a sleepless adversary with a quarterly patch committee. The attacker works in hours; a defender who works in months has lost the arithmetic before anyone arrives. The only thing that collapses that asymmetry is symmetry — attention as continuous as the attack. And it begins with the most unglamorous act of all: knowing what you own. You cannot defend what you cannot see, and most organisations genuinely do not have a complete list of what runs inside their own walls, who wrote it, or who still holds a key.

Here is the inversion that is the answer. For forty years, we optimised software for stability — its highest virtue was that you never had to touch it. The new world flips the virtue. The system that survives is not the one that never moves. It’s the one that can be moved safely every single day. Changeability becomes the security property. The organisation that can rewrite, redeploy, and re-examine a component on an ordinary Tuesday without fear is the one that outruns the threat — not because it’s invulnerable, but because it heals faster than it can be wounded.

Stop chasing invulnerability; it was always a fantasy. Chase resilience.

The roles ascend

A living system needs organs — and that is what our software roles are quietly becoming.

Start with a reframe. The engineer was never valuable because they could type. They were valuable because they understood — and code was simply the only interface we had for expressing that understanding to a machine. Now the machine can take intent more directly. So the typing falls away, and what’s left standing is the thing we were paying for all along: the judgment. The job was never the code. The code was the proxy.

So the builder ascends. The question shifts from did I write this correctly? to is this what we meant, and can I prove it does that? Quality stops being the people who find bugs after the fact and becomes the people who author the intent and the test of the intent — then validate that the generated thing honors it. We used to pay people to write the answer. Increasingly, we pay them to know whether the answer is true.

The same inversion hits security, and it’s the sharper one. The old model was the firefighter: sit in the station, wait for the alarm, run toward the smoke. But when an unsleeping engine surfaces weaknesses every week, incidents stop being events and become weather. You cannot staff for weather with a fire brigade. The role becomes the gardener — continuous, vigilant, tending both the known cracks and the ones still surfacing. And the scarce skill is no longer the patch. The machine can produce ten thousand findings; the irreplaceably human act is deciding which of them matters, what is worth defending, and how. Not coding the defense. Discerning it.

Be honest about the cost, though, because it’s the opposite of comfort. This is a higher bar, not a lower one. To author intent, you must actually know what you want — precisely enough to specify it, precisely enough to test against it. And most organisations have never had to. The slow act of writing code let them discover their intent by trial and error, hiding the fact that they often didn’t know what they meant. Take the slow part away, and you expose the gap. The hardest thing in the new world isn’t the machine. It’s learning to say clearly what we want.

The opening for India and the Philippines

Here is where I stop describing weather and start arguing.

Notice that every shift in this essay is the same movement at a different scale: value is leaving production and migrating to intent, judgment, and care. It’s true for the individual engineer. It’s true for the organisation. And it’s true for entire nations.

The countries that built their software industries on cost arbitrage are standing at a fork — because the same AI that creates this mountain of remediation work is also eroding the bodies-on-seats model that historically did the remediation. India’s IT industry is approaching three hundred billion dollars in revenue. The Philippines, my home base, crossed thirty-eight billion in IT-BPM exports and is climbing toward security, modernisation, and engineering rather than seats.

Also Read: When startups fail, should VCs go to jail?

The wrong response is to wait for the tickets to arrive and bill by the hour. The right response is to own the capability — to build the AI-augmented modernisation platforms, the secure-code practices, the disciplined incremental migration (the strangler approach that drains a legacy system one capability at a time rather than the big-bang rewrite that has wrecked more than one bank) — and to do it as intellectual property made here, not labour rented from here.

Y2K rewarded whoever showed up with hands. This one rewards whoever shows up with a system. For a region with deep engineering talent and a thirty-year track record of doing exactly this unglamorous, mission-critical work, that is not a threat to survive. It is the largest opening in a generation — if we choose to build the tools instead of waiting to be handed the tickets.

What this asks of you

If you run anything that matters — a bank, a utility, a hospital network, a government platform — the comfortable sentence has expired. It works, don’t touch it is no longer a caution. It is exposure.

A few questions worth sitting with before the clock runs out:

• What are you protecting with stillness that you should be protecting with attention?
• If a machine can now write the answer, what exactly were you being paid for — and are you ready to do that instead?
• Can your organisation say clearly what it wants, or has it only ever discovered its intent by accident, one line of code at a time?
• Are your defenders still waiting for the alarm, in a world where the smoke never stops?

The work was never the keystrokes. It was always the knowing. We just couldn’t see it because the keystrokes were in the way.

Magicians conceal. Builders reveal. The old systems kept their secrets because no one was asking. That era is ending — so turn on the lights, look hard at what you’ve been afraid to touch, and decide now whether you’ll be the one who builds the response or the one who rents it.

You have about eighteen months before someone else looks first.

The post “It works, don’t touch it” is now the most dangerous sentence in tech appeared first on e27.

Every week, a new AI tool launches, promising to transform marketing. One that writes content, another that generates videos, a third that automates outreach. Finally, one that builds reports.

For a while, it felt like the companies that adopted the most AI would win. But something interesting has happened over the last two years.

Many businesses have successfully reduced the cost and time required to execute marketing activities. They can produce more content, launch more campaigns, and generate more reports than ever before.

Yet, many struggle with the same business problems: Revenue growth has slowed, customer acquisition costs remain high, and retention rates haven’t improved.

Marketing teams are busier than ever, but leadership teams often have less confidence in the numbers they’re looking at. The problem isn’t a lack of AI but a lack of systems.

The hidden cost of too many tools

Most companies didn’t intentionally design a fragmented technology stack. It happened gradually. A CRM was added to manage leads, an analytics platform to measure performance, a customer support tool was introduced to handle tickets and so on.

Then AI tools arrived and were layered on top of everything else. Individually, each decision made sense. Collectively, many businesses ended up with data spread across multiple platforms, teams working from different reports, and leadership making decisions based on conflicting information.

There seems to be no tally between marketing reports one customer acquisition cost and the numbers the finance is look at. Product analytics tells a different story about user behaviour while attribution changes depending on the platform being used.

The same customer often exists across multiple systems with different histories attached to them. This creates a dangerous situation. Companies become highly efficient at producing activity while becoming less effective at understanding what is actually driving growth.

According to Gartner, organisations use only around one-third of their marketing technology capabilities despite continuing to invest in new platforms. At the same time, the marketing technology ecosystem has expanded to more than 14,000 products.

The challenge for modern businesses is no longer access to technology but creating clarity.

Also Read: AI and accessibility: The untapped solution to the cybersecurity skills gap

What makes a marketing stack AI-native?

Most conversations about AI marketing focus on tools; a better approach is to focus on outcomes. Every marketing system, regardless of industry, needs to answer five questions.

• Do we understand our customers?

Before creating campaigns, businesses need a reliable way to understand customer behaviour, objections, motivations, and buying triggers. AI can now analyse interviews, support tickets, reviews, sales calls, and survey responses at a scale that would have been unrealistic a few years ago. The value is in reducing assumptions in addition to analytics.

• Can we create and test ideas faster?

AI has dramatically lowered the cost of content production. Articles, advertisements, videos, creative concepts, and landing page variations can now be produced significantly faster than before.

This matters because growth is often a function of experimentation. The companies that can test more ideas typically learn faster.

• Can we reach the right people consistently?

Distribution remains one of the most overlooked growth challenges.

AI can assist with segmentation, personalisation, and campaign execution, but distribution still requires a system that ensures the right message reaches the right audience at the right time.

• Can we measure what matters?

This is where many AI implementations break down. The purpose of measurement is not reporting but decision-making.

If leadership cannot confidently answer where customers come from, which channels generate profit, or which activities drive retention, then adding more AI tools rarely solves the underlying problem.

In fact, many companies end up solving the wrong problem entirely. What appears to be an acquisition issue may actually be poor activation. What looks like a retention problem may be a pricing issue. Sometimes the bottleneck isn’t growth at all, but inconsistent measurement across teams.

Understanding where growth is breaking down is often more valuable than buying another tool.

• Can information move across the business?

The most valuable AI systems are often the least visible. They’re the automations that eliminate manual work, connect disconnected platforms, and ensure information flows seamlessly across teams. When customer data moves effectively between systems, businesses spend less time managing tools and more time making decisions.

Also Read: The agent as customer: Jensen Huang’s trillion-dollar bet on AI’s next era

The minimum viable AI-native stack

Customer understanding

• ChatGPT or
• Perplexity

Content and creative

• ChatGPT
• Claude
• Nano Banana
• HeyGen

Measurement

• Google Analytics 4
• PostHog

CRM & lifecycle

• HubSpot

Automation

• n8n

The goal is to ensure every tool contributes to a clearer understanding of customers and a better customer journey.

The real question founders should be asking

When evaluating AI, most companies ask: “What tools should we use?” The better question is: “What is currently preventing growth?”

If activation is weak, no content tool will solve it. If customers are churning, another automation platform won’t fix it. If pricing is wrong, more traffic won’t help. If reporting is fragmented, additional dashboards will only create more confusion.

AI amplifies whatever system already exists. Strong systems become faster. Weak systems become harder to diagnose. That’s why the companies creating sustainable growth in the AI era are not necessarily those with the most sophisticated technology stacks.

They’re the ones that have built systems capable of turning customer data into decisions, decisions into action, and action into measurable business outcomes.

The future of marketing isn’t more AI tools. It’s a better system. This is where many businesses get stuck.

Identifying that growth has slowed is relatively easy. Identifying why it has slowed is significantly harder.

A company may assume it has an acquisition problem when the real issue is activation. Others invest heavily in new channels when customer retention is actually the bottleneck. In some cases, the issue isn’t growth at all, but measurement, where different teams are making decisions using conflicting data.

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The post The AI stack trap: Why more AI tools aren’t translating into more growth appeared first on e27.

Mid-2026 has been a turning point for marketing. Technology, commerce and creative craft are jostling for equal billing, and the conversation has shifted from “what’s possible” to “what actually moves the business.” Below are the trends that are reshaping how brands plan, produce and prove marketing impact this year.

AI moved from theory to practice

Generative AI is transitioning from an experimental gimmick to an operational tool. Teams are using models to prototype concepts, produce rapid creative variants for A/B testing, automate localisation, and generate personalised assets at scale. Successful organisations treat AI as part of a workflow that increases testing velocity. New processes now pair human curators with machine outputs and tighter measurement so that speed doesn’t come at the cost of brand risk or relevance.

At the Marketing Leadership Summit at Cannes Lions, Melody Lee of Mercedes-Benz USA and Nicole Guess from Perion held a measured discussion on storytelling and creativity amid the rise of AI. They highlighted a common industry dilemma: AI speeds up production and enables mass personalization, yet it can’t substitute for the human creative judgment that gives luxury brand communications their depth.

Shoppable digital formats are now a creative imperative in e-commerce

Commerce-first creative is now table stakes. Short-form video with embedded checkout, virtual try-ons linked to instant purchase, and livestream commerce are proliferating across platforms, forcing creative briefs to include distribution and conversion mechanics from day one.

TikTok Shop remains the leader in viral discovery and impulse buying — the 2025 Sprout Social Index found TikTok is Gen Z’s primary product discovery destination (49 per cent go there first) and that 55 per cent of Gen Z engage with brand content there at least once a day. That behaviour changes how campaigns are engineered: creative work is increasingly judged on whether it can translate attention directly into measurable transactions.

Also Read: The future of marketing isn’t about AI, it’s about judgment

Brand management and sustained loyalty remain central

Despite the noise around new technologies, brand management and customer retention remain foundational. Building and protecting brand equity and turning customer acquisition into retention are central priorities.

Leandro Barreto, Global CMO for Unilever Beauty & Wellbeing, and Harry Kargman, Founder & CEO of Kargo, discussed a simple but powerful idea at the Marketing Leadership Summit at the Cannes Lions Festival 2026: that meaningful growth comes from brands that stay true to their values while creating ideas that travel and endure.

Practically, marketers are investing in customer loyalty and subscription offers that prove an impact on repeat behaviour and lifetime value. The recurring insight: purpose and values matter only when embedded in systems and operations that produce measurable customer outcomes, not just campaign headlines.

The creator economy — enthusiasm meets scrutiny

The creator economy remains influential but is under growing scrutiny. While creator-led formats and talent-driven activations continue to reach audiences, several senior marketing leaders told me they are scaling back influencer spend after mixed results. In a private exchange with a C-level marketing executive at a long-established global brand, candid feedback was blunt: recent collaborations with creators produced uneven outcomes, with several projects failing to meet expectations and a noticeable decline in effectiveness from social media bloggers. The executive traced this to shifting audience behaviours, platform algorithm changes, measurement blind spots, and an over-reliance on one-off activations.

Also Read: The playbook for going global: What C-dramas teach us about market entry

External data echoes the caution. Kantar’s research finds that fewer than one in 15 pieces of creator content delivers both strong audience engagement and ROI, which helps explain why brands are recalibrating toward longer partnerships, clearer KPIs, and closer integration of creators into distribution and commerce plans. In short: creators still matter, but their place in marketing strategies — and the metrics — needs rethinking.

A final observation

This is less a moment of disruption and more a period of consolidation. Tools and platforms are maturing; the premium now is on disciplined use of technology, clearer lines between creative idea and commercial outcome, and measurement that ties marketing to business results. Brands that balance digital agility with careful stewardship of their identity, translate experimental wins into repeatable systems, and build creator and commerce strategies around measurable outcomes will lead the next phase of growth.

The post How creativity, commerce and AI collide in mid-2026 marketing mix appeared first on e27.

It was a Sunday afternoon. A founder I know, running a company with 100 employees, revenue above US$50 million, was mid-pickleball when a message arrived: “Can you speak at our conference Tuesday morning?”

He agreed. The conference was two flights away.

What followed was two and a half hours across six browser tabs. Flight aggregators. An airline app. Hotel comparison sites. His loyalty portal. Google Maps for the airport transfer. A WhatsApp message to a friend asking which hotel was actually good near the venue.

By the time he’d confirmed everything, he’d made fourteen booking decisions, compared forty-seven options, and completed a job that neither his role nor his Sunday afternoon were designed for.

That’s not a story about bad travel tools. It’s a story about a category that was designed, from its inception, to serve someone else.

We assumed the problem was price, we were wrong

When we started Bliink, the working thesis was simple: the economics of corporate travel management were broken. Legacy TMCs like Amex GBT, CWT, and BCD require minimum annual travel spend of US$500,000 to access managed services. That threshold eliminates virtually every SME in Southeast Asia before the conversation begins.

So we built for the SME tier. And then we started listening.

After working directly with companies across Indonesia and Singapore, the answer that kept surfacing wasn’t price. It was time. Convenience. And fragmentation.

Companies weren’t failing to book travel because they couldn’t afford a TMC. They were losing hours every week because no product had ever actually taken the job away from them.

Also Read: Why the US tech rebound matters for SEA’s AI and venture ecosystem

Three solutions, three failures

The corporate travel industry has had thirty years to solve this and has produced three categories of response. Each one fails differently.

• Legacy TMCs price you out.  Amex GBT runs an 80 per cent opex ratio, US$479 million in operating costs against US$597 million in revenue, managed by 19,000 people. That cost structure doesn’t support SME pricing. It never will. For Southeast Asia’s 60 million-plus SMEs, these platforms are structurally inaccessible.
• Self-serve tools still make you do the work.  TravelPerk, Navan, and SAP Concur gave companies a better interface and called it a solution. But a faster booking tool is still a booking tool. You still search, filter, compare, approve, reconcile, and report. The friction moved from phone to screen. The labour did not move at all.
• The SME market was never the target.  This is the one the industry has never said out loud: no travel management company was ever designed for companies with 20 to 500 employees booking in rupiah, using Lion Air, needing WhatsApp approvals, and managing travel across multiple time zones and currencies. Southeast Asia’s SMEs weren’t underserved. They were structurally excluded. There is a difference.

Why the window just opened

Three things have converged that have not converged before.

AI has made fully managed travel economically viable at SME scale for the first time. The 1:120 service ratio that legacy TMCs achieved by employing thousands of agents can now be delivered by a single AI system. What required a US$500,000 minimum spend in 2022 can be delivered at the 50-employee level in 2026.

Also Read: The future of marketing isn’t about AI, it’s about judgment

The legacy players are collapsing under their own weight. CWT filed for bankruptcy. Amex GBT is being taken private in a US$6.3 billion deal, which is a cost restructuring play, not a growth strategy. The managed travel market for SMEs is, for the first time, structurally undefended.

Southeast Asia’s SMEs have already digitised their behaviour. WhatsApp penetration exceeds 90 per cent in Indonesia. Mobile corporate expense adoption has tripled since 2022. The behavioural foundation that makes AI-native corporate travel workable exists in the market right now. It didn’t three years ago.

What the data reveals

We built Bliink to test this thesis. Eight months in, the metric that surprises people most isn’t revenue. It’s retention.

We’ve had 100 per cent client retention since the beta launch. We’ve never run a marketing campaign. Every client arrived through a referral.

I’m careful about what conclusions to draw from early data. But 100 per cent retention across eight months of operation is not a product metric. It’s a signal about what category you’re actually in.

There’s a difference between software that people use and a service that people keep. Corporate SaaS benchmarks 5-10 per cent monthly churn as normal. The gap isn’t in features. It’s whether the job belongs to the product or to the person.

When a platform handles the trip, preferences recalled, policy applied, itinerary sent, receipts filed, the work is no longer the traveller’s. That’s not a UX improvement. It’s a category shift. And it turns out that when you actually complete the job for someone, they stop looking for alternatives.

The actual opportunity

The opportunity in corporate travel intelligence for Southeast Asia is not better booking software. It’s institutional memory.

Every trip a company takes encodes information: traveller preferences, policy boundaries, pricing benchmarks, vendor performance, patterns across teams and time. That data doesn’t exist in any structured form for the 60 million-plus SMEs in this region. It’s scattered across email threads, WhatsApp chats, and booking confirmation PDFs that nobody reads twice.

The company that captures and structures that data, not for MNCs, not for Fortune 500 procurement teams, but for the mid-tier Indonesian consultancy and the Singapore regional distributor and the Jakarta family office, builds a moat that no generalist AI model or offshore OTA can replicate.

The Internet gave companies infinite choices and left them flying blind. AI is finally giving them back the trusted advisor the Internet took away.

The question for Southeast Asia is who builds it first, and whether they build it from here.

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Singapore’s mass affluent and high-net-worth investors are using artificial intelligence (AI) for finance and investment at a higher rate than their global peers, but most still want a human adviser involved before they act.

A new HSBC study conducted by Ipsos found that 76 per cent of Singapore investors surveyed use AI for finance and investment, compared with a global average of 72 per cent. The findings are based on responses from 609 Singapore investors collected in January and February 2026, as part of a broader survey of 9,993 mass affluent and high-net-worth individuals across ten markets.

Also Read: The AI stack trap: Why more AI tools aren’t translating into more growth

The headline number is less interesting than the behaviour behind it. Singapore investors are not simply outsourcing decisions to chatbots or portfolio tools. They are using AI to research markets, compare ideas and stress-test assumptions, then taking those conclusions to advisers for validation.

Only 8 per cent of Singapore respondents said AI was the single most influential source in their most recent major investment decision, below the global figure of 12 per cent. That suggests a market that has adopted AI quickly but remains cautious about treating it as a final authority.

A hybrid model takes shape

HSBC’s research points to a hybrid advisory model becoming more entrenched in Singapore’s wealth market. Some 69 per cent of Singapore respondents use AI to research and analyse investments, 44 per cent use it for strategy support, and 34 per cent use it to test their own ideas.

Yet 79 per cent still look to professional advisers for reassurance, while 71 per cent value advisers for strategic expertise. More than half of Singapore respondents, or 57 per cent, said they preferred AI and advisers working together, ahead of the global average of 50 per cent.

This is notable because Singapore is one of Asia’s most mature wealth management centres. The city-state had SGD5.4 trillion in assets under management in 2023, approximately US$4 trillion, according to the Monetary Authority of Singapore. A large share of that money is managed on behalf of regional and international clients, making Singapore a test bed for how private banks, wealth platforms and relationship managers adapt to AI-assisted investing.

The generational spread is also significant. AI use in finance among Singapore’s Gen X investors stood at 72 per cent, compared with 65 per cent globally. Among Baby Boomers, the gap was wider: 72 per cent in Singapore versus 59 per cent globally.

That challenges the assumption that AI-led wealth tools are mainly a younger investor phenomenon. In Singapore, older and wealthier clients appear comfortable using AI as part of the discovery process, provided the final judgement remains anchored in professional advice.

Banks are arming advisers, not replacing them

The survey lands as HSBC Singapore accelerates its own adviser-facing AI rollout. The bank launched Wealth Intelligence in Singapore and Hong Kong in September 2025. The platform gives relationship managers access to insights and research drawn from more than 10,000 sources, including HSBC Chief Investment Office material and external data.

In May 2026, HSBC introduced AI Prepare, a tool designed to generate client engagement packs by pulling together a client’s financial overview, investment insights and tailored talking points before meetings. The bank says the aim is to reduce manual preparation time for relationship managers and allow them to focus more on advice.

Also Read: A step-by-step framework to build your AI adoption roadmap for B2C service businesses

HSBC has also widened its AI ambitions through a multi-year partnership with Google Cloud announced on 17 June 2026. Hyper-personalised wealth management support is one of the first three focus areas. The bank expects the partnership to support more than 200 AI use cases across its global operations within two years.

Ashmita Acharya, Head of International Wealth and Premier Banking at HSBC Singapore, framed the shift as a change in expectations rather than a threat to advisers.

“Singapore’s investors are using AI in their financial decision-making with discipline. They are doing more of their own analysis, arriving at conversations better prepared, and expecting more of the professional advisers who help them as a result,” she said.

That is the central tension for banks. AI makes clients more informed, but it also raises the bar for relationship managers. Generic market commentary and templated portfolio reviews become harder to defend when clients can generate their own summaries and comparisons in minutes.

High-net-worth clients are moving faster

Among Singapore high-net-worth investors, defined by HSBC as those with at least US$2 million in investable assets, AI adoption rises to 90 per cent. That compares with 82 per cent globally.

This group also appears more willing to quantify AI’s role in investment outcomes. Singapore’s high-net-worth respondents attributed an average of 40 per cent of their investment returns over the past 12 months to AI influence, above the 31 per cent average across all Singapore respondents. Two-thirds, or 65 per cent, said AI made them feel more in control.

Banks will treat that as both opportunity and warning. Wealthy clients are not waiting for financial institutions to introduce them to AI. Many are already using external tools, research platforms and model-driven analysis. The bank’s challenge is to make its advisory relationship relevant in a world where clients can arrive with their own data-backed conclusions.

Competitive pressure in Southeast Asia

HSBC is not alone. Singapore’s large domestic banks, including DBS, OCBC and UOB, have been investing heavily in data analytics, personalisation and AI-enabled wealth tools. Global private banks such as UBS, Citi, Standard Chartered and Julius Baer are also trying to make relationship managers more productive through AI-assisted research, client segmentation and portfolio monitoring.

At the same time, digital wealth platforms such as Endowus, Syfe and StashAway have normalised lower-cost, technology-led investing for affluent and mass affluent clients in Singapore and parts of Southeast Asia. While these platforms do not compete directly with private banks across all client segments, they have changed expectations around transparency, access and digital experience.

Also Read: The next phase of business: We are moving to AI crews

For Southeast Asia, the implications extend beyond Singapore. The region has a growing affluent class, but wealth advisory remains uneven across markets. Singapore and Hong Kong dominate private banking, while countries such as Indonesia, Thailand, Malaysia and Vietnam continue to deepen their wealth ecosystems. AI could help advisers serve more clients more efficiently, but it also raises regulatory and suitability questions, particularly around explainability, bias and accountability.

Singapore’s regulatory environment gives it an advantage here. MAS has spent years pushing financial institutions to adopt responsible AI practices, including fairness, ethics, accountability and transparency principles. That matters in wealth management, where unsuitable recommendations can carry significant financial consequences.

The HSBC study ultimately shows that AI adoption does not automatically mean adviser displacement. In Singapore, the wealthiest clients are embracing AI, but not surrendering judgement to it. They want faster research, sharper conversations and more personalised advice.

For banks, that means the real competition is not simply between humans and machines. It is between advisers who can use AI to improve the quality of advice, and those who cannot.

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RedDoorz’z planned 2027 SGX mainboard listing marks a notable milestone for Southeast Asia’s budget hospitality sector, and its strategy deserves attention for its unconventional approach: using IPO proceeds primarily to fund acquisitions rather than organic growth.

This M&A-first playbook, targeting profitable but tech-lagging hospitality businesses across Australia, India, and Southeast Asia, reflects a pragmatic bet that buying market position is less risky than building it from scratch, especially in fragmented, capital-intensive hospitality markets.

The timing also signals confidence in Singapore’s equity market revival, as SGX has struggled with thin listing pipelines in recent years. RedDoorz choosing SGX as its primary venue, despite generating most revenue outside Singapore, reinforces the exchange’s appeal to tech-enabled firms headquartered there, even as Saberwal keeps a Nasdaq dual-listing option open for deeper tech-investor liquidity.

Equally significant is RedDoorz’s profitability turnaround in 2024, driven by AI-enabled automation across software development and operations, a template increasingly common among tech firms seeking to scale without proportional headcount growth.

With Indonesia’s 24% growth anchoring performance amid regional softness, RedDoorz’s resilience stems from its focus on value-conscious domestic travelers, a segment less exposed to geopolitical shocks than international tourism. Still, execution risk around integrating diverse acquisitions across multiple markets and regulatory regimes remains the key variable determining whether this ambitious roll-up strategy delivers sustainable returns for public investors.

REGIONAL

RedDoorz eyes 2027 IPO in Singapore: Budget hospitality platform RedDoorz is targeting a Singapore IPO in 2027, as the company looks to capitalise on a recovery in regional travel and position itself for public markets after years of restructuring.

Nium acquires Cypher as fiat and stablecoin payments converge: Singapore-based Nium has acquired Cypher, a stablecoin infrastructure firm, to build a unified payment rail spanning fiat and stablecoin transactions, a signal that cross-border payment firms in SEA are repositioning ahead of the stablecoin regulatory wave.

Atome’s US$88M AUB facility tests Philippine BNPL’s next phase: Atome has secured an US$88M credit facility from Asia United Bank, its largest debt raise in the Philippines, to scale buy-now-pay-later lending as the market matures beyond early adopters into mainstream credit access.

Shopee expands fast grocery delivery across Indonesia: Shopee is scaling its rapid grocery delivery service across more Indonesian cities, intensifying competition with Grab and GoTo in the country’s quick-commerce segment, which remains one of the region’s most contested battlegrounds.

B Capital closes oversubscribed Ascent Fund III at US$500M: B Capital, co-founded by Facebook’s Eduardo Saverin, has closed its Southeast Asia-focused Ascent Fund III at its US$500M hard cap, oversubscribed, signalling sustained LP appetite for SEA venture despite a cautious global funding environment.

Temasek targets 10-15% AI allocation in portfolio by 2031: Singapore’s Temasek is planning to raise its AI-related investments to 10–15% of its total portfolio within five years, one of the most concrete AI allocation targets announced by a major sovereign investor in the region.

QAI Ventures backs four startups in Singapore quantum accelerator: QAI Ventures has selected four startups for Singapore’s first quantum-focused accelerator cohort, backing early-stage companies at the intersection of quantum computing and AI as the city-state moves to anchor the sector.

Choco Up moves deeper into supply chain finance for SMEs: Hong Kong-based Choco Up is expanding into supply chain finance to help SEA SMEs manage delayed payments, a structural pain point that has grown more acute as global trade uncertainty squeezes working capital cycles.

LINE MAN Ride targets 3,000 EV drivers in Thailand: LINE MAN Wongnai’s ride-hailing arm is recruiting 3,000 EV drivers in Thailand, a move that tests whether EV unit economics can make ride-hailing margins viable as fuel costs continue to pressure the sector.

Thailand to invest US$1.99B in AI, clean energy, and aviation: The Thai government has announced a US$1.99B investment plan spanning AI, electronics, aviation, and clean energy as it tries to attract supply chain investment shifting out of China.

Stanford-born Spark enters SEA via health innovation hub: Spark, a health innovation programme with Stanford roots, has entered Southeast Asia through a health innovation hub partnership, adding institutional weight to the region’s health-tech and medical innovation pipeline.

Sprouts AI raises US$9M for enterprise sales agents: Singapore-based Sprouts AI has raised US$9M to develop AI revenue agents that automate enterprise sales workflows, targeting B2B companies across Southeast Asia and beyond.

TurtleTree raises new capital to scale lactoferrin output: Singapore precision fermentation startup TurtleTree has raised a new funding round to scale production of lactoferrin, a high-value milk protein, as it moves from lab to commercial scale amid growing demand from infant nutrition markets.

Maybank: SEA e-commerce growth stays strong; ride-hailing under pressure: A Maybank research note finds SEA e-commerce continuing to grow robustly while ride-hailing platforms face mounting fuel-cost pressure, with Singapore operators particularly exposed.

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INTERVIEWS & FEATURES

Carousell’s recommerce pivot: the quiet death of classifieds: As recommerce hits 50% of Carousell’s revenue mix, this deep-dive examines how the platform has gradually deprioritised its classifieds roots in favour of a commerce model with stronger monetisation potential.

MiracleFeet: a US$500 fix closing Asia’s clubfoot gap: MiracleFeet is using a low-cost brace to treat clubfoot across Asia, a condition that can be fully corrected for under US$500 but remains largely untreated due to access and awareness gaps.

Food delivery’s consolidation model is cracking in East Asia: A structural analysis of how East Asia’s food delivery market is fracturing as super-app economics weaken, regulatory pressure grows, and niche players challenge dominant platforms on unit economics.

AI is reshaping Singapore wealth management, not replacing advisers: Wealth managers in Singapore are deploying AI for data analysis and client profiling, but human advisers remain centralto relationship management, a nuanced finding that complicates both the AI-doom and AI-hype narratives.

Singapore’s Gen Z handles money differently; here’s what it means: Gen Z in Singapore are saving earlier, investing via apps, and avoiding debt more than prior generations, with significant implications for fintech product design and financial services marketing strategies.

Corporate travel in SEA was never built and that’s the opportunity: A feature arguing that Southeast Asia’s corporate travel infrastructure was never properly developed, making the sector ripe for tech-native solutions rather than fixes to legacy systems.

Fundamentum launches US$231M Fund III for Indian startups: Indian VC firm Fundamentum has launched its third fund at US$231M, targeting growth-stage Indian startups, a signal that India’s VC market is staging a strong recovery from the 2023-24 funding winter.

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INTERNATIONAL

Tencent in talks to become Manus AI’s largest shareholder: Tencent is in advanced talks to take a major stake in Manus, the viral autonomous AI agent startup, in a deal that would mark one of China’s most significant AI investments and has direct implications for how Chinese AI platforms compete globally.

OpenAI launches GPT-5.6 in new model family: OpenAI has released GPT-5.6 as part of a new model family, continuing its rapid release cadence. The launch raises the competitive bar for AI developers across SEA building on foundation model APIs.

Fidji Simo steps down from OpenAI’s No. 2 role: Fidji Simo has resigned as OpenAI’s CEO of Applications, the second-highest role at the company, in a leadership shake-up that signals internal restructuring as the firm navigates its commercial expansion.

NYT says OpenAI hid evidence in ChatGPT copyright trial: The New York Times has alleged in court filings that OpenAI concealed evidence during the ongoing copyright lawsuit, a development that could reshape how AI training data practices are scrutinised globally, including in SEA markets.

Nandan Nilekani exits GP role as his VC firm launches US$200M Fund III: India’s Nandan Nilekani, architect of Aadhaar, has stepped down as a general partner at Fundamentum as the firm launches its US$200M third fund, a transition worth watching given his influence over India’s digital infrastructure thinking.

US tech rebound and what it means for SEA’s AI ecosystem: An analysis of how the recovery in US tech valuations is filtering into SEA’s AI and venture landscape, with implications for fundraising sentiment, LP allocations, and founder confidence across the region.

AI boom drives Taiwan exports up 40.3% in June: Taiwan’s exports surged 40.3% year-on-year in June, driven almost entirely by AI-related semiconductor demand, a data point with direct implications for SEA’s own AI infrastructure buildout costs and supply chain dependencies.

Vivo JV marks new phase in India’s smartphone manufacturing boom: Following Apple’s shift to India, Vivo has entered a joint venture to manufacture smartphones locally, further consolidating India as the world’s next major electronics production hub and a competitive alternative to SEA manufacturing bases.

Hong Kong AI startup GIM raises US$20M Series A: GIM, a Hong Kong-based AI startup, has raised a US$20M Series A, expanding the Greater China AI funding scene at a time when regional investors are closely watching how Hong Kong positions itself as an AI hub relative to Singapore.

Truecaller clashes with India’s telecom regulator over anti-spam rules: Truecaller is in a public dispute with India’s TRAI over new anti-spam regulations that could undermine its core caller-ID product, a regulatory conflict with lessons for SEA telecom and identity-tech firms.

Malaysia PM to debut an AI double: Malaysia’s Prime Minister is set to launch an AI-generated digital double for public communications, a move that makes Malaysia one of the first governments in the region to deploy AI avatars at the head-of-state level.

Bitcoin’s move to US$63K linked to Iran tensions, not crypto fundamentals: An analysis arguing that Bitcoin’s recent price surge was driven by geopolitical risk hedging around Iran rather than on-chain or crypto-native demand signals, relevant context for SEA’s growing retail crypto investor base.

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CYBERSECURITY

Massive breach exposes millions of drivers’ licence numbers: A major data breach has leaked millions of drivers’ licence records, adding to a growing global pattern of identity-document exposures that SEA regulators and digital ID advocates are closely monitoring.

Fraud officer in Yogyakarta won’t catch the AI wave — and ASEAN banks know it: A sharp examination of how ASEAN’s financial institutions are dangerously under-prepared for AI-enabled fraud, with frontline compliance staff lacking the tools, training, and mandates to respond effectively.

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SEMICONDUCTOR

Rebellion’s IPO puts South Korea’s AI chip ambitions on trial: South Korean AI chip firm Rebellion is preparing for an IPO that will test whether Korea’s homegrown semiconductor sector can credibly challenge Nvidia with implications for how SEA governments assess domestic chip development strategies.

Apple tests CXMT chips for China-sold devices: Apple has begun testing memory chips from China’s CXMT for devices sold in the Chinese market, a significant supply chain shift that signals deepening chip bifurcation between US and China ecosystems.

Meta’s new AI chips begin production in September: Meta’s custom AI inference chips are entering mass production in September, a move that will reduce the company’s dependence on Nvidia and reshape the competitive dynamics of AI infrastructure globally.

Nvidia is a victim of the compute marketplace it created: An analysis arguing that Nvidia’s dominant position is being undermined by the very ecosystem of cloud and marketplace compute it enabled with direct read-across for how SEA’s AI infrastructure buyers evaluate GPU procurement.

Korea’s Rebellions raises stakes ahead of chip IPO: South Korea’s Rebellion chip firm is making final preparations for its stock market listing, with the IPO expected to be a bellwether for investor appetite in non-US AI semiconductor plays.

SEA’s AI buildout races toward a power wall: Southeast Asia’s rapid AI infrastructure expansion is running into hard energy capacity constraints, with power availability emerging as the binding constraint on data centre growth across the region.

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AI

Agentic AI ambitions in Singapore run into legacy systems: Singapore enterprises are struggling to deploy agentic AI at scale due to legacy system fragmentation and data quality gaps, revealing a structural readiness problem beneath the city-state’s AI ambitions.

Singapore’s AI adoption problem is weak execution, not worker resistance: A new assessment finds that Singapore’s AI rollout is stalling not because employees resist the technology but because organisations lack the implementation discipline to embed it effectively.

Why most enterprise AI in APAC is stuck in the proof-of-concept room: An industry analysis finds that the majority of APAC enterprise AI projects never advance beyond pilot stage, with procurement inertia, integration costs, and unclear ROI metrics cited as the primary blockers.

Patient intake is becoming healthcare’s most important AI use case: A detailed examination of why AI-driven patient intake systems are gaining traction in healthcare, reducing admin burden, cutting wait times, and improving data quality at the point of care.

Vision-based AI is transforming construction site safety: AI-powered vision systems are being deployed across construction sites to detect safety violations in real time, a fast-growing use case in SEA where construction remains a high-fatality industry.

AI-quantum collision creates 2026 infrastructure inflection point: An analysis of how converging AI and quantum computing developments are forcing enterprise infrastructure teams to make bet-the-firm decisions on technology architecture in 2026.

Why Asia already knows how the AI economy ends: A pointed argument that Asia’s historical experience with technology-led economic disruption gives the region a clearer-eyed view of AI’s endgame than Western commentators, who tend to oscillate between utopia and dystopia.

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THOUGHT LEADERSHIP

Why traditional hiring won’t work for APAC’s AI roles: Conventional recruitment processes are ill-suited for sourcing AI talent in APAC, where the skills are non-traditional, the candidate pool is thin, and speed-to-hire is a competitive disadvantage most companies haven’t addressed.

The AI stack trap: more tools, less growth: Enterprise teams across SEA are adding AI tools at pace but seeing diminishing returns, as tool sprawl without integration strategy creates complexity rather than productivity.

‘It works, don’t touch it’ is tech’s most dangerous sentence: A sharp argument that legacy system complacency, the instinct to leave functioning but outdated infrastructure alone, is now a critical enterprise risk in an era of fast-moving AI and security threats.

From ESG dashboards to delivery: where SEA sustainability startups should build: An essay arguing that SEA’s sustainability startups have over-invested in reporting tools and must shift to building operational infrastructure that delivers measurable environmental outcomes.

Most SEA startups sound the same, and that’s not an accident: A critique of how founder communication in Southeast Asia has converged on a set of generic narratives — mission-led, impact-driven, category-defining — that obscure differentiation and weaken investor conviction.

When startups fail, should VCs go to jail?: A provocative examination of VC accountability and legal liability when portfolio companies collapse, particularly in markets where founder-investor power dynamics are opaque and governance frameworks are weak.

Founding a company is not a career move: A candid essay challenging the notion that entrepreneurship is a rational career-optimisation decision, arguing that treating it as one is precisely why so many ventures fail to achieve the ambition they claim.

The future of marketing isn’t AI; it’s judgement: A counterintuitive argument that as AI automates execution, the scarcest marketing skill is not technical fluency but editorial judgement, knowing what to say, to whom, and why.

Singapore has the ingredients for world-class founders — just not the culture: An essay arguing that Singapore’s infrastructure, capital, and talent base are sufficient to produce globally competitive founders, but that a risk-averse, consensus-driven culture remains the decisive constraint.

Delaware C-Corp, Cayman, or Singapore Pte Ltd: a tax adviser’s view: A practical breakdown of the tax and fundraising implications of the three most common incorporation structures used by SEA startups raising venture capital, told from a tax adviser’s perspective.

We are moving to AI crews, the next phase of business: A forward-looking argument that the shift from individual AI tools to coordinated AI crews, multi-agent systems working in concert, represents the next step-change in how businesses will operate.

Every job in your GBS needs an upgrade, so does every person in it: An essay on why Global Business Services functions in APAC must reskill their entire workforce for an AI-augmented operating model, not just retrain isolated teams.

How creativity, commerce, and AI collide in mid-2026’s marketing mix: A mid-year assessment of how AI is reshaping the marketing stack — compressing creative cycles, enabling hyper-personalisation, and forcing brands to rethink the role of human creativity in campaigns.

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Startup ecosystems teach founders what progress looks like. The question is whether they teach founders to become better at navigating the ecosystem, or better at building companies that can survive outside it.

Few countries illustrate this more clearly than South Korea.

Over the past two decades, Korea has built an extensive, publicly backed startup support system. For 2026, the Ministry of SMEs and Startups received approval for a record 16.5 trillion won (US$11.3 billion) budget, spanning startup support, SME development, venture investment, R&D, and programs for small businesses.

Also Read: South Korea’s top 30 VC deals of 2024: A year of shifts and surprises

The country also runs initiatives such as TIPS and K-Startup Grand Challenge, which show two sides of Korea’s startup strategy: supporting domestic founders through public-private acceleration and inviting global startups to use Korea as a platform for growth. TIPS uses selected private accelerators to identify and support promising startups, while K-Startup Grand Challenge is designed to help international startups enter, establish, and scale in Korea.

I have watched that development closely since first arriving in Korea in 2006. During that time, I have seen the ecosystem from several positions: as a founder of a Korean startup, as an executive at a Korean unicorn, and through running accelerator and innovation programs for Korean founders. That perspective has made me appreciate how much Korea has done right. It has also made one point increasingly clear: startup ecosystems do not only support founders. They train them.

Support systems create incentives

This is not an argument against government support. Korea’s investment has lowered the barriers to entrepreneurship, expanded access to resources, and made startups a more visible and credible career path. Many founders have benefited from programs, grants, mentors, networks, and overseas opportunities that would have been much harder to access two decades ago.

But every support system creates incentives.

If grant applications are repeatedly rewarded, founders learn how to write better grant applications. If pitch competitions are rewarded, founders allocate more time to presentations. If overseas participation is treated as progress, founders attend more international events. If awards and media exposure are treated as evidence of success, founders will rationally devote more attention to visibility.

Also Read: 5 Seoul startups made their Southeast Asia debut at Echelon Singapore 2026 under the SBA pavilion

None of these activities is inherently wrong. Grants can extend runway. Pitch competitions can improve communication. Awards can create credibility. Overseas exhibitions can open doors. Public-private programs can give founders access to networks, corporate partners, investors, and global markets that would otherwise be difficult to reach.

The risk begins when these activities start to substitute for company-building.

Activity is not the same as progress

A startup can look active from the outside while still being far from the market. It may have attended conferences, met investors, and won awards, while still not knowing whether enough customers have the problem it claims to solve, whether those customers will pay, or whether the team can repeatedly sell beyond its home market.

In accelerator programs, I have encountered founders who could explain their government support history, competition results, and international exhibition schedule in detail, but struggled to identify the purchasing decision-maker inside their target customer, estimate the sales cycle, or explain how a pilot would become a recurring contract. The issue was not a lack of effort. In many cases, participation milestones were more visible and measurable within the ecosystem than customer learning or commercial progress.

This is why Korea is such a useful example for other startup ecosystems. Korea has gone further than many markets in answering the first question: how do we create more startup activity? Its infrastructure, funding, and institutional support have helped make entrepreneurship more visible and accessible. The next question is more difficult: how do we make sure that all this activity produces commercially stronger companies?

That requires looking beyond easy-to-count metrics. It is natural for programs to track the number of startups supported, mentoring hours delivered, investor meetings arranged, demo days held, countries visited, or MOUs signed. These figures are useful because they measure activity. They do not necessarily measure progress.

The better questions are more demanding. Did the startup understand its customers better after the program? Did a pilot convert into a paid contract? Did an investor meeting produce serious follow-up or a sharper fundraising strategy? Did an overseas visit produce qualified leads, local partners, regulatory insight, or a clear decision not to enter that market? Did the founder become better at selling, hiring, adapting, and making hard decisions?

The next stage of ecosystem development

This distinction matters because government-backed ecosystems influence founder habits at scale. When public money funds startup support, it is not only buying workshops, mentoring sessions, booths, or demo days. It is shaping what thousands of founders believe progress should look like.

For Korea, this should be seen as an opportunity. The country has already built much of the infrastructure of a serious startup ecosystem. The next stage is refinement: designing programs, incentives, and evaluation metrics that push founders toward customer validation, commercial capability, and global readiness.

For other ecosystems watching Korea, the lesson is equally important. Across Southeast Asia and beyond, governments are increasingly using grants, accelerators, corporate partnerships, international missions, and startup hubs to strengthen entrepreneurship. These interventions can expand access and accelerate ecosystem development, but only if they are designed around the right outcomes. Startup support should not simply make founders better at participating in the ecosystem. It should make them better at succeeding beyond it.

Also Read: From Korea to ASEAN: 10 startups building bridges at Echelon Singapore 2026

That may be Korea’s most valuable lesson for global innovation hubs. Ecosystems should not be judged only by the activity they generate, but by the capabilities they develop in founders. Systems that primarily reward participation will tend to develop founders who become skilled at navigating programs. Systems that demand customer evidence and commercial execution are more likely to help founders build companies capable of succeeding beyond them.

The post Korea’s startup ecosystem is training founders, not just funding them appeared first on e27.

For many startups across Asia, international expansion begins with excitement. An overseas exhibition, government-backed delegation, foreign investor meeting, or promising distributor conversation can make global growth feel suddenly within reach.

These opportunities matter. They can open doors that would otherwise take years to access. They help founders meet potential partners, understand unfamiliar markets, and see how their product compares beyond their home country.

Also Read: Why operational readiness is key to successful international expansion for SMEs

But global exposure is not the same as global readiness.

A startup is not ready for a new market simply because it attended an event there, pitched to international investors, or received positive feedback from potential partners. These are useful signals, but they are only the beginning. Real market entry requires evidence that the company can repeatedly sell, deliver, support, and grow in that market.

Having worked with founders preparing to expand beyond their home markets, especially Korean startups entering overseas markets, I have found that the strongest teams do not treat international expansion as a milestone. They treat it as a new validation process.

Before committing significant resources, startups should test their readiness across five areas.

1. A clearly defined buyer

Market entry begins before the founder boards a plane. It starts with a clear understanding of who will buy the product and why.

Founders should be able to identify the actual buyer, the people who influence the decision, and the problem urgent enough for the customer to pay to solve. They should also understand how customers currently address that problem and what evidence buyers require before approving a purchase.

Many startups know the estimated size of a market but not the procurement process within their target customer organizations. They may have several partner meetings scheduled but no clear definition of the partner they need. They may describe demand broadly without having spoken to enough customers who experience the problem directly.

This does not mean the company is weak. It means the company is still learning. The risk comes when founders mistake international activity for customer evidence.

2. A viable route to market

Interest is not the same as a sales channel.

Before entering a market, startups need a credible view of how customers will discover, evaluate, purchase, and adopt the product. In some markets, direct sales may be practical. In others, a distributor, system integrator, enterprise partner, or local representative may be necessary.

A potential partner should not be judged only by enthusiasm or reputation. Founders should assess whether the partner reaches the right customers, has incentives to prioritize the product, understands the buying process, and can support the relationship after the initial introduction.

Also Read: How to get hired as an International Expansion Executive

A full meeting calendar can create the appearance of momentum. What matters is whether those meetings reveal a repeatable route to revenue.

3. A localized commercial model

Localization is often interpreted too narrowly. Translating a website, pitch deck, or product interface may be necessary, but it is not enough.

Localization can include pricing, packaging, product expectations, sales processes, regulation, payment behavior, customer support, partner incentives, and proof requirements. The core product may solve the same broad problem across markets, but customers may buy it for different reasons.

A feature valued in Korea may matter less elsewhere. A pricing model that works in Singapore may not work in Indonesia. A sales message that feels credible in one market may be unconvincing in another.

This is why founders should avoid treating Southeast Asia as a single market. A company does not enter Southeast Asia in the abstract. It enters a specific country, industry, and customer segment under specific regulatory and commercial conditions.

4. The ability to deliver and support

Winning the first customer is only one part of market entry. The company must also be able to onboard, serve, and retain that customer.

Founders should ask whether the product can be deployed locally, whether support can be provided across languages and time zones, whether regulatory requirements can be met, and whether the company can maintain service quality as demand grows.

Trust is part of this operating capability. Customers may like the product but hesitate because the company has no local references. Partners may express interest but wait to see whether the startup is committed to the market or only visiting for a program.

For an early-stage company, trust is built through fast follow-up, credible commitments, local relationships, and consistent support. A startup does not always need a full local team, but it needs access to people who understand the market from the inside.

5. Evidence of demand

Every overseas program, exhibition, delegation, or market visit should be tied to a specific learning objective.

Is the startup testing customer demand, pricing, partner quality, regulatory feasibility, sales-cycle length, or local competition? Each activity should produce evidence.

A productive market visit should lead to more than photographs, meetings, and social media posts. It should produce qualified leads, customer insights, partner assessments, agreed next steps, or a clear conclusion that the market is not currently suitable.

Sometimes the most valuable outcome is learning where not to expand.

The goal of international expansion is not to be present in as many countries as possible. It is to build repeatable traction in the right markets.

More Asian startups now have access to overseas programs, accelerators, investor networks, and cross-border partnerships. That access is valuable, but access alone does not create global companies.

Also Read: Ready for expansion? Here’s how to decide where to take your business

Global companies are built when founders convert exposure into evidence: a defined buyer, a viable route to market, a localized commercial model, the ability to deliver, and credible proof of demand.

Market entry should not be treated as a badge of progress. It should be treated as a test. The startups that understand this will be better prepared not only to enter new markets, but to remain, compete, and grow in them.

The post Global exposure isn’t global readiness: What Asian startups must prove before expanding appeared first on e27.