Part of my work as an international market expansion specialist, supporting government and companies in the process of promoting and attracting opportunities, is reading a market’s readiness not just through headlines, but through the infrastructure underneath: banking systems, regulatory friction, and the everyday experience of the people actually trying to operate there. That’s what pulled my attention to the Maybank announcement, earlier this year, and to a pattern I keep seeing repeatedly across the expat communities I’m active in.

Maybank plans to deploy MYR 10 billion (US$2.5 billion) over the next five years, with one core target tied to its CASA ratio, Current Accounts and Savings Accounts as a share of total deposits. In plain terms: the more everyday accounts a bank opens, the less it needs to rely on expensive funding sources like fixed deposits.

When global mobility is the hidden gem

One growth lever behind this is Malaysia’s still-sizable unbanked population. The other, less discussed, is global mobility. Malaysia currently ranks third globally for expat-friendliness in several credible global ranks. On paper, that’s a strong signal for banks: more people relocating should mean more accounts opened.

But the on-the-ground reality tells a different story. Across the expat groups I follow closely, one complaint comes up consistently: opening a bank account as a foreigner in Malaysia remains genuinely difficult, regardless of employment status or intent to stay. There’s a visible gap between government ambition to attract global talent and the private banking sector’s operational readiness to onboard them. That gap is exactly the kind of friction I look for when assessing underlying opportunities: the typical market inefficiencies that hide strong potential.

Also Read: Malaysia’s digital economy’s second wave looks nothing like the first

This is where Brazil enters the picture, not as a random comparison, but as a useful counter-case from my own expansion work. Brazil is a market I know from the inside, and it’s a useful stress test for Maybank’s targets: not because the two markets are comparable in maturity, but because they sit at opposite ends of the same infrastructure question, which both markets could learn from each other.

Maybank’s long-term targets (figure 1), ROE of 13 to 14 per cent, cost-to-income at 47 per cent or lower, net interest margin above 2.05 per cent (already achieved), are healthy, competitive numbers within Malaysia’s banking environment. Though, once applied to Brazil’s benchmarks to that same structure, it would collapse.

Take for instance one of Brazil’s largest banks, Itaú Unibanco, which posts an ROE of 24.3 to 25.7 per cent, a cost-to-income ratio of 35.5 to 37.3 per cent, and a NIM of 6.2 to 6.7 per cent. A margin that looks solid in Kuala Lumpur wouldn’t keep a Brazilian bank alive for one cycle.

Also Read: Malaysia fines, Singapore funds: How two governments are forcing SEA’s second digital wave

Is banking infrastructure telling us a different story about market readiness?

The difference is less about performance and more about infrastructure maturity. Brazil’s Pix, Open Finance, and heavy automation have compressed operational costs to a degree Malaysia’s banking sector is pursuing it as we speak although it hasn’t reached yet. That’s precisely the kind of variable I flag in market readiness: two very different playbooks telling different stories for the same objective: governments fulfilling their needs, companies growing abroad in a healthy structure.

Zoom out to market capitalisation (figure 2), and the layering continues: Nubank (~US$77B) and Itaú Unibanco (~US$73B) each dwarf Maybank’s ~US$34.5B, while Maybank still edges out Banco do Brasil and Bradesco. None of these figures are directly transferable between markets, and that’s the point.

For any business, or institution, eyeing expansion into global markets, the lesson is the same: rankings signal potential, infrastructure determines execution. Closing that gap isn’t a footnote, it’s the actual opportunity.

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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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Waymo is preparing to bring its driverless ride-hailing service to Singapore in 2028, marking one of the most closely watched tests yet of whether fully autonomous mobility can work in a dense, highly regulated Southeast Asian city.

The Alphabet-owned autonomous vehicle company said it is working with Singapore’s Ministry of Transport and Land Transport Authority to lay the groundwork for a public commercial launch through the Waymo app. Its initial fleet of all-electric Jaguar I-PACE vehicles will arrive in the city-state in the coming months, before a readiness phase begins in 2027.

Also Read: Singapore greenlights expanded AV testing as WeRide and Grab prepare for public rollout in 2026

During that phase, trained autonomous specialists will manually drive the vehicles around Singapore to help adapt Waymo’s technology to local road layouts, traffic behaviour, rain conditions and operating rules. If regulatory approvals and testing milestones are met, the service is expected to open to riders in 2028.

The move adds Singapore to a growing list of overseas markets in Waymo’s expansion plan, alongside Tokyo, London and Munich. It also places the city-state in the middle of a global race to commercialise autonomous vehicles beyond carefully controlled pilots.

For Singapore, the partnership fits into a broader transport strategy: fewer privately owned cars, better first- and last-mile links to public transport, lower emissions, and more efficient use of limited urban space. For Waymo, it is a chance to prove that a service built and scaled first in US cities can be translated into one of Asia’s most demanding road environments.

A cautious route to driverless deployment

Waymo is not promising an overnight rollout. Its Singapore roadmap is deliberately phased, reflecting how sensitive autonomous mobility remains for regulators and the public.

The company said its vehicles will first be used to establish local operations. In 2027, autonomous specialists will begin manual driving to map and understand Singapore’s roads, including local geometry, traffic patterns and monsoon weather. Only after that process will Waymo seek to open a fully autonomous commercial ride-hailing service in 2028.

That sequencing matters. Singapore’s roads are orderly by regional standards, but they are also complex. The country has high traffic density, frequent construction diversions, heavy rain, multi-storey road networks, cyclists, pedestrians, buses, private-hire cars, taxis and delivery riders sharing tight urban corridors. A robotaxi that works on wide roads in parts of the US still has to demonstrate it can handle the more compressed, mixed-use nature of Asian city driving.

Also Read: Grab makes strategic bet on WeRide to drive autonomous mobility in SEA

Waymo enters with a substantial operating record. The company says it has served more than 20 million fully autonomous rides and driven more than 300 million fully autonomous kilometres. It also cites a 94 per cent reduction in injury-causing crashes compared with human drivers in the US cities where it operates fully autonomously.

Those numbers will help its case with regulators, but Singapore will still need local evidence. The city-state has long been open to autonomous vehicle testing, including earlier trials involving companies such as nuTonomy, Aptiv and Motional. Yet it has also been careful not to let the technology run ahead of safety frameworks, insurance models and public acceptance.

Why Singapore matters

Singapore is a small market by population, but it is strategically useful for mobility companies. It has strong public transport, clear regulation, high digital adoption and a government willing to test new urban technologies when they align with national priorities.

That makes it a natural Southeast Asian entry point for Waymo, even if the company’s longer-term regional opportunity may lie elsewhere. Cities such as Jakarta, Bangkok, Manila and Ho Chi Minh City face more acute congestion and transport informality, but their road environments are also less predictable and more difficult to regulate. Singapore offers a controlled but meaningful first step: dense enough to be challenging, structured enough to be feasible.

The company is also positioning its service as a complement to public transport rather than a replacement for it. Waymo said many riders in its current commercial service areas use its vehicles to connect to mass transit. In San Francisco, more than a third of riders are picked up or dropped off near transit stations, according to the company.

That argument is especially relevant in Singapore, where the MRT and bus network already covers much of the island. The question is not whether robotaxis can replace trains, but whether they can fill gaps: late-night trips, short connections from estates to stations, rides for people with mobility constraints, and routes where private car ownership is inefficient.

Waymo’s all-electric fleet also gives the launch an environmental angle. The company said its vehicles produce zero direct emissions and support the Singapore Green Plan 2030. At its current scale, Waymo estimates its fleet prevents about 480 metric tonnes of carbon dioxide from road travel every week.

Still, the green case will depend on usage. Electric robotaxis can reduce emissions if they replace private car trips, improve vehicle utilisation and link people to public transport. They are less helpful if they pull riders away from buses and trains or add empty vehicle kilometres while waiting for passengers.

Rivals and the wider robotaxi race

Waymo arrives in Singapore as the global autonomous vehicle sector enters a more selective phase. The early hype around self-driving cars has faded, and investors now care less about futuristic demos than about unit economics, safety records and regulatory durability.

Also Read: Southeast Asia isn’t losing the robotaxi race. It’s running a different one

Globally, Waymo’s most visible rivals include Amazon-owned Zoox, which is developing purpose-built autonomous vehicles; Tesla, which is pursuing a camera-led autonomy strategy; and Chinese players such as Baidu’s Apollo Go, WeRide and Pony.ai, all of which have pushed robotaxi services in parts of China and, in some cases, overseas. General Motors-backed Cruise was once Waymo’s closest US competitor, but its robotaxi ambitions were sharply curtailed after regulatory and safety setbacks.

In Southeast Asia, the competitive landscape is less mature. Singapore has hosted autonomous vehicle trials for years, but no company has yet turned driverless ride-hailing into a mass-market commercial service. Local transport operators, private-hire platforms and public agencies will be watching Waymo’s entry closely, not only as a mobility launch but as a signal of what role foreign autonomous vehicle companies may play in the region.

Jobs, trust and the public test ahead

Waymo and Singapore officials are framing the partnership around capability-building as well as transport. The company said it intends to create high-skilled local operational jobs, while the government sees the entry of a major autonomous vehicle operator as a way to strengthen the domestic ecosystem.

“Singapore welcomes Waymo’s entry as our newest autonomous vehicle operator,” said Jeffrey Siow, Minister for Transport and Second Minister for Finance. “Waymo brings world-class technology and operational expertise to Singapore, and will move us towards our vision of creating new transport options for Singaporeans.”

Waymo co-CEO Tekedra Mawakana said the company would work with national leaders to complement Singapore’s public transport network while bringing its commercial safety record to the city.

The harder task begins after the announcement. Autonomous mobility depends on trust built slowly: uneventful rides, transparent safety reporting, clear accountability when things go wrong, and a service that solves real transport problems rather than simply showcasing technology.

Singapore gives Waymo one of the best possible urban laboratories in Asia. It also gives the company little room for error. In a city where transport is expected to be safe, reliable and tightly managed, the robotaxi promise will be judged less by novelty than by whether it can quietly become useful.

The post Waymo’s Singapore entry raises the stakes for autonomous mobility in Asia appeared first on e27.

On September 18, 2026, global markets rose together. Asian stocks and bonds gained as oil extended its decline. European equities climbed. The STOXX 600 rose 0.9 per cent to 642.6 points. Mining and automotive sectors led those gains. The FTSE index gained 1.2 per cent. That marked its best one-day performance in over two months.

The Bank of England halted sales of long-dated gilts. That decision supported UK assets. The crypto market joined the rally. It rose 0.59 per cent to US$2.62T in 24 hours. The Federal Reserve had raised rates by 25 basis points on September 17, 2026. That was the first hike since 2023. Markets had fully priced in the move. The reaction became a relief rally. Investors focused on the end of the tightening cycle rather than the hike itself. That shift in sentiment lifted nearly every risk asset.

The economic backdrop aided risk assets. West Texas Intermediate crude fell 0.7 per cent to US$101.20 a barrel. Cheaper oil reduces inflationary pressure. US 10-year Treasury yields retreated from recent multi-year highs. Lower yields ease pressure on global equities. They also reduce the opportunity cost of holding non-yielding assets such as digital assets and gold. Spot gold remained steady following earlier weekly fluctuations. This combination of cheaper oil and steady bond yields created a helpful climate for digital assets. This macro mix gave traders a reason to add exposure.

The asset class traded as a rates-sensitive instrument on that day. Its correlation with the S&P 500 was 0.43. That is a moderate positive reading. It is lower than the 71 per cent figure that appeared in May of this year. The Bitcoin-gold tie was above 50 per cent at the start of this month. Some short-term gauges reached 0.8. That still shows a meaningful tie, but it is not 79 per cent. These figures indicate a looser connection than some earlier reports suggested. That matters for how investors interpret the advance. It does not mean digital assets ignore macro. It means the link varies with the news cycle. On this occasion, the Fed decision and the oil move mattered more than the usual internal drivers.

Also Read: The CLARITY Act vote could send crypto to US$2.73T or crash it to US$2.6T

Group rotation amplified the market-wide move. The AI Applications category gained 5.83 per cent. The Privacy group rose 3.98 per cent. Independent verification did not directly confirm that exact figure. The broader privacy space has surged 213 per cent since October 2025.

Zcash drove almost all of that rise. Zcash posted a 13 per cent daily advance on September 16. It jumped another 15 per cent on September 17 following the Fed decision. Protocol upgrades and institutional interest fuelled that move. These movements indicate that market appetite extends beyond Bitcoin. Funds are seeking alpha in specialised narratives with strong fundamentals. That broadening of strength across asset classes is a healthy sign. It suggests the advance has a base value greater than one coin.

The near-term path for digital assets hinges on key technical marks. The current market cap sits just above the 50 per cent Fibonacci retracement level at US$2.6T. That mark now acts as support. The immediate trigger for the advance is past. The focus shifts to whether the advance can sustain. A close above the 23.6 per cent Fib threshold at US$2.67T could pave the way for a retest of the yearly high at US$2.73T. Failure to hold US$2.6T risks a pullback toward the US$2.57T to US$2.53T base zone. The 61.8 per cent Fib sits at US$2.57T. A break below that mark could signal a return to range trading.

My point of view is cautiously bullish. The combination of a digested rate increase and strong group rotation points to underlying strength. The market passed its immediate test. It absorbed a rate hike without collapsing. That is a significant signal. I still want to see confirmation.

Bitcoin needs to stabilise. The breadth of smaller coins needs to continue. The advance cannot rely on one group or a single economic event. The Privacy and AI Applications groups show leadership. That is encouraging. They remain relatively small parts of the overall capitalisation. For the advance to challenge US$2.73T, funds need to flow more broadly. I would like to see a weekly close above that pivot before turning more constructive.

Also Read: The Fed is the real crypto story, Bitcoin and Ethereum are just following

I also watch the Ethereum Foundation AMA on September 16 for further sentiment cues. That event could provide insight into developer activity and network upgrades. It may not move prices on its own, but it adds to the narrative mosaic. The digital asset space is increasingly responsive to fundamental developments. That is a maturation story.

The worldwide economic backdrop remains the dominant driver. Cheaper oil and steady bond yields create a supportive climate for speculative assets. The central bank’s increase became a bullish catalyst because markets had already priced it in. The UK central bank’s decision on long-term government bonds added to the calm. Asian equities confirmed the trend. This is a coordinated advance. It is not a digital asset-specific event. That makes it more durable, but also more dependent on economic conditions remaining stable.

If oil continues to decline and yields stay contained, digital assets can test US$2.73T. If oil reverses or yields spike, the US$2.57T floor will come under pressure. The US$2.6T pivot is the line in the sand. Holding above it keeps the positive case alive. Breaking below it shifts the story back to choppy conditions.

In conclusion, the outlook is cautiously bullish momentum. Investors have digested the rate increase. Group rotation is strong. Chart marks are clear. The question now is whether Bitcoin can stabilise and the breadth of smaller coins can continue. Can investors capitalise on this economic clarity to challenge the US$2.73T resistance? I believe they can, but only if the speculative climate remains supportive. The next few sessions will tell us whether this upward move has true staying power or whether it fades into another range phase. I lean toward the former, but I remain watchful.

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

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

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

The post Did the Fed just accidentally kick off the next crypto bull run? Or just a dead cat bounce? appeared first on e27.

Crunchbase’s numbers for the first half of 2026 are the kind that are supposed to make an entire industry feel good. Global venture funding hit US$510 billion, beating the whole of 2025 in six months and smashing the previous half-year record of US$375 billion set in the second half of 2021. Startup capital, by the headline, is back.

Read past the headline and the story curdles. OpenAI and Anthropic alone accounted for US$217 billion of that total — 43 per cent of every venture dollar deployed on the planet in six months. Anthropic’s US$65-billion second-quarter raise by itself was close to a third of all global venture funding for the quarter.

Also Read: Anatomy of a shakeout: what 7K+ deadpooled startups reveal about Southeast Asia’s new tech reality

AI’s share of capital jumped from under 50 per cent a year earlier to more than 70 per cent by Q2. Deal count, meanwhile, barely moved. This was not a broader boom lifting more founders. It was two companies, and a handful of AI-infrastructure bets around them, absorbing a record-breaking pool of capital that the rest of the world’s startups mostly watched pass by.

What Southeast Asia actually got

Set that number against what Southeast Asia raised over the same stretch and the gap stops being abstract. Startups in the region pulled in US$2.81 billion across 98 equity deals in the first quarter of 2026, the lowest quarterly deal count in at least eight years, according to DealStreetAsia. More than 70 per cent of that quarter’s value came from a single transaction: Singapore-based data centre operator DayOne’s US$2-billion Series C. Strip that one round out and the region raised roughly US$800 million in three months.

For the whole of 2025, Southeast Asia’s tally was US$5.37 billion across 461 deals. OpenAI and Anthropic’s combined first-half haul is more than 40 times that entire annual figure, extracted from global markets in half the time.

We wrote e27‘s own retrospective on this drought a few days ago: 7,538 Southeast Asian tech startups have deadpooled since January 2020, with peak closures in 2021 and 2022 and attrition still running through 2025. The instinct in the region has been to read that as a home-grown correction, a hangover from pandemic-era excess, high interest rates, and investors demanding a path to profitability that many grocery-delivery and social-commerce plays never had.

All of that is true, but none of it is the whole story. The bigger truth is that the capital pool available to everyone who is not building a frontier model has been quietly shrinking as a share of the total, even as the total itself hits records.

Concentration is not a US problem you can watch from a distance

It is tempting for Southeast Asian founders and investors to treat this as someone else’s bubble — a Bay Area story about two labs, a handful of hyperscalers, and a debt-financed data centre build-out that has already drawn warnings from the IMF and the Bank of England about opaque leverage. But the region is not a bystander. GIC and Temasek-linked vehicles are direct participants in the AI mega-rounds reshaping the market — Temasek-backed Xora led a US$53-million seed round in Hang Ten earlier this week, and sovereign capital from the region sits inside several of the infrastructure deals now competing for the same limited pool of late-stage dollars that used to flow more evenly across sectors.

When four transactions can account for roughly two-thirds of a quarter’s global venture dollars, as insights4vc’s analysis of Q2 2026 found, every LP with exposure to venture as an asset class is making a portfolio decision about how much of that concentration it wants, whether it says so explicitly or not.

Also Read: Analysis: SEA’s June funding spike masks a narrow recovery in VC funding

Southeast Asia’s own funding data is starting to rhyme with the global pattern, just at a smaller scale. Five megadeals accounted for 93 per cent of June 2026’s US$4.22-billion regional total, a four-year high built almost entirely on DayOne, Supabase, AI startup Acrab, Airwallex, and Vietnam’s Vinpearl.

The region’s headline funding numbers are increasingly a story about a handful of outsized rounds, mostly in data centres, payments infrastructure, and AI, rather than broad-based conviction in the next generation of SEA founders. Concentration, in other words, is not just something happening to the region from outside. It is becoming how the region’s own capital behaves.

The uncomfortable trade-off nobody in SEA wants to name

None of this means Southeast Asia is being deliberately starved. Foundation-model economics are genuinely different: training frontier systems requires sustained, enormous capital in a way that a fintech Series B never did, and some of the money flowing into regional data centres is itself SEA’s cut of the AI infrastructure build-out, not capital diverted away from it.

Malaysia, Indonesia, and Thailand now have 31 planned data centres above 100 megawatts, versus just two a few years ago — real, if capital-intensive, participation in the cycle.

But participation in infrastructure is not the same as participation in venture. A data centre lease is not a Series A term sheet, and the jobs and equity created by hosting compute for someone else’s model are structurally different from the jobs and equity created by building the model, or the application layer, yourself.

If the next decade of technology value accrues overwhelmingly to two or three frontier labs and the infrastructure landlords around them, Southeast Asia’s founders need a funding strategy that does not depend on a rising tide that has, for the first time in venture-capital history, stopped lifting most boats.

What actually needs to change

The honest response is not another op-ed lamenting a “funding winter” as if it were weather. It is building permanent, regionally-controlled capital — sovereign funds, corporate venture arms, and family offices willing to underwrite unfashionable sectors precisely because global LPs have stopped bothering to look at them.

Also Read: The end of Southeast Asia’s unified startup funding story?

It is also being candid with founders that the pitch of “just build something AI-adjacent and the capital will find you” is a bet on scraps from a table two companies are eating alone.

Southeast Asia’s startups do not need to out-raise OpenAI and Anthropic. They need capital that was never going to chase them in the first place, and right now, that capital is nowhere near enough of it.

The post When 43 per cent of the world’s funding goes to two firms, where does that leave SEA? appeared first on e27.

For most of my career, I believed professional value followed a relatively stable equation.

The more capable you became, the more valuable you became.

That assumption shaped how many of us approached work, leadership, and identity itself. We invested years building expertise because expertise carried weight. We learned to execute reliably because reliability created trust. Capability created leverage. Experience accumulated into authority. And for a long time, that model worked.

Organisations rewarded people who could think clearly, solve difficult problems, communicate effectively, and execute consistently under pressure. Intelligence differentiated people. Knowledge created advantage.

I think AI is beginning to destabilise that equation in ways many organisations still do not fully understand.

Most conversations around AI remain focused on productivity. The dominant language revolves around automation, efficiency, operational acceleration, and workforce transformation. Major consulting firms continue to frame AI primarily through the lens of productivity and economic value creation rather than deeper organisational consequences.

I think the deeper disruption is something else entirely.

AI is exposing what organisations actually value about humans.

That distinction matters, because for years, many companies claimed to value creativity, leadership, strategic thinking, and human insight. But operationally, many organisations still rewarded people primarily for speed, responsiveness, optimisation, information processing, and scalable execution.

In other words, many firms were already optimising for machine-compatible behaviour long before machines became capable enough to compete. AI changes the economics of that arrangement.

Over the past year, I have noticed something psychologically significant happening across industries. Work that once signalled expertise is becoming increasingly compressible. Strategic summaries, first-draft ideation, communication scaffolding, structured analysis, and presentation logic can now be generated almost instantly. Even high-skill knowledge work is increasingly being reframed through the lens of AI-assisted productivity.

Most people interpret this as a productivity breakthrough. I think it is actually a value disruption. Because once intelligence becomes abundant, intelligence itself stops being the differentiator. And that forces organisations into a question many are still avoiding:

What exactly remains valuable about human contribution once execution is no longer scarce?

I increasingly believe the answer is judgment. Not intelligence. Judgment.

Also Read: “AI amnesia” is quietly costing Southeast Asian brands their customers

The ability to interpret reality correctly before decisions get made. The ability to navigate ambiguity without collapsing into noise. The ability to preserve trust under pressure. The ability to frame problems clearly enough for coordinated action to happen.

These are not soft skills. They are system-stabilising capabilities. And I think many organisations are dangerously underestimating how important they are becoming.

Most firms are still asking:

“How do we implement AI?”

“How do we increase productivity?”

“How do we automate workflows?”

Far fewer are asking:

“What kind of human judgment becomes more important once intelligence becomes infrastructural?”

That is the more important strategic question. Because the organisations that survive the next decade may not necessarily be the ones with the most AI. They may be the ones that remain capable of coherent judgment while operating inside machine-amplified environments.

That is much harder than automation. Automation is primarily technical. Judgment is cultural. And this is where I think the real leadership challenge begins.

Many organisations are still structurally designed to reward execution more than discernment. They reward responsiveness more than reflection. Optimisation more than interpretation. Speed more than coherence.

AI amplifies all of those tendencies. Which means many companies are unintentionally accelerating toward environments filled with more outputs, more information, more generated intelligence, but weaker human judgment. That is not organisational evolution. That is organisational fragility at scale.

Researchers are already beginning to describe this shift as the rise of a “verification economy,” where human value increasingly moves away from producing information and toward validating, interpreting, and judging machine-generated outputs.

The deeper issue underneath all this is not technological. It is psychological.

For decades, many professionals unconsciously built identity around being knowledgeable, capable, and difficult to replace. Competence became more than economic value. It became legitimacy. Meaning. Self-worth.

AI compresses those signals simultaneously. That is why I think the anxiety emerging across industries is not merely about job displacement. It is about significance.

People are quietly asking:

“If intelligence is no longer rare, what exactly makes me valuable now?”

And organisations are beginning to face the same question at a systems level. What kind of human contribution do they actually want to preserve? Because if firms continue optimising humans primarily for machine-compatible execution, machines will eventually outperform humans under those exact conditions.

Also Read: Nobody gives you time to explain. That’s the real fundraising problem

That leaves leaders with a choice. Either continue building organisations around scalable execution and gradually reduce humans into supervisory infrastructure surrounding increasingly intelligent systems.

Or redesign organisations around the things machines still struggle to do well: judgment, interpretation, trust-building, contextual reasoning, ethical navigation, and coherent decision-making under uncertainty.

Interestingly, many of these same capabilities are now emerging as priority future skills in global workforce research. The World Economic Forum increasingly identifies analytical thinking, resilience, adaptability, leadership, and creative thinking as critical capabilities in AI-shaped economies.

I think this is the real strategic fork emerging beneath the AI economy. Not AI versus humans. But whether organisations continue optimising for execution alone, or begin redesigning themselves around higher-quality human judgment.

The companies that figure this out early may gain something far more valuable than productivity. They may become environments where human intelligence still retains meaning. And I suspect that will become one of the most important competitive advantages of the next decade. Because once intelligence becomes abundant, the real scarcity is no longer intelligence itself. It is the ability to use it wisely.

And I think the leaders who understand that shift early will begin asking a very different kind of question:

Not “How do we use more AI?”

But: “What kind of organisation do humans still meaningfully belong inside after AI?”

—

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

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

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

The post The AI economy is quietly exposing what organisations truly value about humans appeared first on e27.