In an era where artificial intelligence, automation, and advanced analytics are rapidly transforming the world of work, the conversation in Southeast Asia must shift from “what technology can do” to “how humans can use technology to solve real problems.”

The rise of AI has created both excitement and anxiety. But at its core, AI is a tool—an incredibly powerful one—but still a tool. It is not a new master to bow to.

Our region must not fall into the trap of glorifying technology for its own sake. Instead, we must focus on cultivating human skills that harness and direct technology meaningfully, especially in ways that serve the real challenges of our communities, businesses, and governments.

Across Southeast Asia, countries are investing in digital transformation, smart cities, fintech, and e-government platforms. Yet, many organisations are still hiring for technical know-how without emphasising critical thinking, creativity, empathy, collaboration, and ethical judgment.

These are the very human skills that cannot be easily replicated by machines—and they are essential for ensuring technology serves society, not the other way around.

AI without purpose creates friction

AI is often seen as the latest shiny object. But without a clear use case, it becomes a solution looking for a problem. For example, many Southeast Asian SMEs adopt AI chatbots, only to frustrate customers with rigid, robotic interactions. Why? Because they focus on the technology, not the user experience.

Contrast this with a successful example from Indonesia, where AI-powered mobile apps are helping rural farmers forecast crop yields and access micro-loans. The difference lies in the application: tech that solves a real-world problem, guided by human insight.

To truly leverage AI and other emerging technologies, we need to train our workforce differently. The traditional education system in much of Southeast Asia emphasises rote learning and technical proficiency. While these are important, they must be complemented with project-based learning, interdisciplinary problem-solving, and industry immersion.

Programs that connect students with real business challenges—such as digital marketing for SMEs, or logistics optimisation for rural supply chains—help young people see tech as a means, not an end.

Also Read: The resume is dead: Why 80 per cent of companies fail to hire based on real skills

Singapore, for instance, is beginning to model this shift. Initiatives like SkillsFuture and AI Singapore promote continuous learning and applied AI research that involves industry partnerships. But there is still a long way to go in ensuring these skills reach beyond the tech elite. In Malaysia and the Philippines, where talent is abundant but access to high-quality training is uneven, public-private partnerships can help democratise AI literacy while reinforcing problem-solving skills as the core of any tech deployment.

AI needs human direction

Human-centric hiring means looking beyond the resume. Southeast Asian employers must begin to value traits like adaptability, curiosity, empathy, and storytelling—especially when paired with basic tech fluency.

A developer who can explain the societal impact of their algorithm is more valuable than one who can only write clean code. A healthcare worker who uses digital tools to track patient outcomes while listening compassionately can bridge the human-tech divide in meaningful ways.

So, should we fear AI? Not if we remember that it works best when directed by people who understand the problem, care about the outcome, and ask the right questions. AI can scale our ideas, but it cannot generate purpose. It can detect patterns, but not set values. It can optimise, but not empathise.

The real promise of technology

In conclusion, Southeast Asia’s future does not depend on how many coders we produce, but how many problem-solvers we empower.

Let us shift our focus from hiring for tech, to hiring for human potential in a tech-heavy world. Let us build a workforce that sees AI not as an authority, but as a collaborator in crafting better services, stronger economies, and more inclusive societies.

That is the real promise of technology—and the leadership challenge of our time.

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There has been a growing debate about putting AI data centres into space.

AI needs enormous amounts of power. Space has constant sunlight for solar power. And if launch costs keep falling, maybe it will finally make sense to move the data centres into orbit.

Until recently, this could be dismissed as science fiction. Today, it deserves to be taken seriously — but only if we follow the economics all the way through.

When you do, the answer turns out to be very clear, and very different to what is being discussed.

Why is this question being asked now

This conversation is not driven by AI. It is driven by launch costs.

For most of the space age, lifting large amounts of mass into orbit was prohibitively expensive. That constraint has changed dramatically in the last decade.

Launch costs to low Earth orbit have followed a steep and dramatic decline: from more than US$40,000/kg historically to US$2500–3000/kg today and targeting US$100–300/kg in SpaceX’s new Starship

To stay conservative, this analysis assumes US$150/kg to LEO — not a promise, but no longer a fantasy.

That single shift turns space from an exotic environment into something closer to infrastructure.

The data centre energy stack

To ground this discussion in reality, consider a facility like xAI’s Colossus, operating at roughly 300 MW of continuous power.

The current “best possible” energy stack is a mix of onsite gas turbines, grid connections, a small amount of solar and a few batteries for smoothing

Some of that power is delivered via the grid, some via on-site generation. For a true cost comparison, we can treat the energy stack as if it were fully dedicated to the site.

The cost of building the energy stack is around US$550–1050M

Plus annual maintenance and fuel costs of US$100–180M a year

Gas is not a backup in this model. It is structural.

Also Read: Breaking into the data centre sector: Beyond technical expertise

Why look to space at all?

Because AI needs power at scale, and it needs it to be stable, and we need a route there that doesn’t depend on extracting and burning ever more fossil fuels.

Solar is an obvious solution; however, on Earth, even excellent solar installations deliver only 25–30 per cent of their theoretical output over a year. Solar in orbit benefits from constant sunlight 40 per cent stronger than on the surface of the earth and is effectively firm by default. There is no night, no weather, and no seasonal variation. Once built, it can be 100per cent solar without fuel or large storage.

That single difference is what makes space interesting.

What does a 300 MW space-based solar energy stack weigh?

The cost to get a solar plant in space is the cost per kg we discussed before times the number of kgs it weighs. Modern space-solar designs use ultralight photovoltaic membranes rather than glass-and-steel terrestrial panels. With no wind or gravity, structures can be far lighter.

Consensus estimates a conservative near-term figure of 0.8 kW per kilogram of photovoltaic material is plausible.

At that density, 300 MW requires ~375 tons of panels.

Even in space, you still need structural support, wiring, power electronics, and control systems. These add mass, though far less than on Earth.

Using optimistic but defensible assumptions, non-panel components add roughly one to two times the panel mass.

That puts the total mass required to generate 300 MW in orbit at approximately 750–1,100 tonnes.

At US$150/kg to LEO, and another 15–20 per cent to raise to GEO, it is expensive, but single-time — and crucially, it buys something Earth-based solar cannot: firm power without fuel.

These figures reflect a post-industrialised SBSP cost regime; today, a kind of 300 MW GEO system would cost over a billion dollars, but with repeat builds and learning-curve effects, these ranges are plausibly achievable within ~10–25 years.

Annual operating costs are minimal:

Annual cost of operations and maintenance: US$3–6M / year

No fuel. No price volatility.

Also Read: The AI age is changing the data centre industry – Here’s how Singapore can pivot

What about the data centre?

At this point, now that we know that moving the energy stack to space is feasible, we can look at moving the data centre itself.

This is when the numbers break.

A data centre is not just chips. It also comprises power electronics, cooling systems, structural containment, cabling, and radiation shielding. Even reducing the weight of the structure for zero gravity, we’re looking at a 300 MW AI data centre of 13,000–15,000 tons.

Plugging in our conservative near-term launch costs of ~US$150/kg to LEO, that implies:

• US$1.95–2.25 billion to launch the data centre, before orbital transfer.

And a second factor has to be added: unlike the solar infrastructure, this cost is not one-time.

Chips are replaced every three to five years. That means most of the compute mass would need to be relaunched on that cadence.

No plausible launch-cost trajectory fixes this asymmetry.

That is why putting compute in orbit fails economically — even in a world where space-based energy begins to make sense.

The pivot the numbers force

Once it becomes clear that data centres are too heavy and too short-lived to move economically, the problem reframes itself.

The thing that should move to space is the energy stack.

The thing that should stay on Earth is the computer.

Beaming power is real technology: The basic architecture is straightforward: collect sunlight in space, convert it to microwaves, beam it at low intensity, below that of radar, to a large “rectenna” on Earth, which is a simple large mesh and convert it back to electricity. No exotic physics or speculative materials are required; power beaming has been demonstrated terrestrially and at a small scale in space.

End-to-end efficiency is not 100 per cent. A reasonable near-term assumption is that only about two-thirds of generated power reaches the data centre, which means the orbital solar array must be oversized by roughly 1.5×.

For a 300 MW continuous data-centre load on Earth, that implies ~450 MW of space solar generation, plus transmission hardware.

Also Read: Is Southeast Asia’s data centre boom headed for a PR crisis?

Adding transmission capabilities and increasing the capacity to 450MW changes our costs: (again, after price optimisation, not first of a kind today, which would be two to three times the cost for a prototype)

The logical conclusion

Although the upfront cost of space-based solar is higher, the difference in annual fuel and operating cost is large enough to repay that in a handful of years.

And with no future fuel cost risk.

Why isn’t everyone doing this? Because launch costs only crossed the threshold very recently. Even a 2024 NASA study still assumed Falcon 9–era economics.

And politically, it’s easier to talk about “AI in space” than “power beamed from orbit.”

But narratives follow incentives.

As launch becomes cheap and power demand explodes, the industry will pivot.

Not to data centres in space.

But to something far more powerful: Data centres on Earth, powered by cheap, stable, solar energy from space.

That’s the real solution hiding in plain sight.

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In late November 2025, Soulpower Acquisition Corporation and SWB LLC, the company behind SOUL WORLD BANK, announced a merger agreement that would bring the business public on the NYSE at an estimated $8.1 billion valuation, backed by $5 billion in committed funding, pending shareholder and regulatory approval.  

Soul World Bank was formed in response to a financial system that remains fragmented, border-dependent, and difficult to access for many individuals and businesses operating across markets. The company intends to offer a range of international financial services, built around newer technologies such as artificial intelligence, stablecoins, and tokenization. To make this happen, the company lists technology partners that are designed to make financial services more accessible and efficient for everyday users, rather than only large institutions.

Through this collaboration — alongside partners such as Animoca Brands — NewCampus brings its community and systems building experience into finance, extending the same mission into a larger and more complex arena.

Justin Lafazan, CEO of Soulpower and founder and managing member of SWB, underscored the importance of that partnership, saying, “We are all in on Will Fan and the NewCampus team and could not imagine building SOUL WORLD BANK without them. Our partnership with NewCampus means we are starting with a proven team and in-place network across Southeast Asia.”

NewCampus, an innovation firm based in Singapore, focuses on community building and operational infrastructure for emerging institutions. Its involvement in Soul World Bank reflects a broader recognition that technology alone is no longer sufficient to build complex financial systems. This article examines how ecosystem-building principles developed in one sector can translate effectively across others.

A decade of building communities, now building for finance

NewCampus’ core mission focused on rethinking how leaders in Asia learn, grow, and work together. NewCampus has built over a decade of experience as one of the top “challenger universities in Asia” –  an alternative model to traditional universities that focuses less on formal degrees and more on practical learning, community, and real-world outcomes. Working with over 500 companies worldwide and reaching more than 130,000 learners, NewCampus continues their mission that real progress begins when people are seen fully, not just as account holders, but as workers, parents, builders, and dreamers. 

That experience is now being applied in a new context in an unusual pairing between education and banking. NewCampus has repeatedly built institution-like systems from scratch where participation, trust, and empathy support leadership pipelines and more efficient operational structures, including its partnership with Open Campus to invest in more than 140 edtech companies, impacting over 20 million learners globally.

Their multi-country, stakeholder approach has built a systems-first legacy that applies to old industries that need disruption. While core expertise lies in learning infrastructure and leadership development, NewCampus also boasts an impressive track record building ecosystems that scale.

Soul World Bank is built on the premise that the next chapter of global banking must be built with the communities it serves. These same capabilities – building engaged communities, creating operational infrastructure, and enabling peer networks – are exactly what new financial institutions need.

As CEO Will Fan has shared publicly, “The past decade, I’ve been building a challenger university to reimagine how leaders in Asia learn, grow, and build. Today, I’m bringing those lessons into a new arena: launching a challenger world bank.” He is excited about joining forces with the Lafazan Brothers and Animoca Brands to help build SOUL WORLD BANK calling it the “same mission, bigger playground (and) reshaping access to opportunity.”

More is expected to come as NewCampus helps shape this next chapter of global finance, specifically, one rooted in technology, humanity, and the courage to reimagine what’s possible through new economy banking for frontier markets.

Also read: Bring your most authentic self to the table whether at home or work: Will Fan of NewCampus

An $8.1 billion bet on new economy banking

An $8.1 billion valuation is notable for an Asia-linked institution listing in the United States. Historically, most companies from the region debut on the New York Stock Exchange at significantly smaller sizes, often well below the $1–3 billion range (compared to Singapore Carro’s predicted $3bn valuation last August). In this context, the scale of Soul World Bank’s proposed listing stands out, particularly as it enters the public markets with substantial capital commitments already in place.

The transaction follows a SPAC merger designed to form a new economy financial services group with a global footprint. Based on publicly disclosed information, the venture combines an $8.1 billion valuation with a $5 billion committed equity facility, an uncommon pairing at the point of listing. The structure also includes a partnership with Animoca Brands to support stablecoin development, as well as plans to acquire a British Virgin Islands banking license, subject to regulatory approval. Its portfolio spans a range of real-world assets, including land and mineral resources, and is built around an AI-native banking model with stablecoin denomination.

Within this structure, NewCampus is engaged as an independent contractor providing what it describes as operational infrastructure. Rather than functioning as a traditional vendor, NewCampus is positioned as a longer-term partner, contributing to how the organization is set up to operate as it develops. The collaboration reflects a broader approach to building new financial institutions—one that pairs capital and technology with operational systems designed to support scale from the outset.

Beyond vendor relationships: The ecosystem builder approach

Most financial institutions operate through a network of vendors such as technology providers, and service firms, with each being responsible for a defined function. In that model, tools are delivered, frameworks are recommended, and implementation is often left to the organization itself. 

NewCampus’ role differs in scope to traditional models. Rather than delivering short term advisory and execution, NewCampus partners with organizations at the operational level, focusing on how people, systems, and processes are designed to function as institutions scale.

One area of focus is community infrastructure. For financial institutions—particularly challenger banks serving underserved or cross-border markets—growth depends on trust and sustained participation, not just customer acquisition. NewCampus designs systems that support long-term engagement, peer networks, and leadership pathways, 

For newer or challenger banks, trust and participation cannot be assumed. It needs to be deliberately designed. NewCampus brings experience in building community infrastructure that encourages long-term engagement, supports peer networks, and moves relationships beyond purely transactional interactions. This approach treats users as participants in a broader ecosystem—an important distinction for financial institutions operating across markets where trust, inclusion, and sustained engagement are critical.

A second focus is operational systems for innovation. As institutions combine traditional financial services with newer technologies such as blockchain and tokenization, NewCampus helps design internal processes that allow legacy systems and new infrastructure to coexist. The emphasis is on enabling teams to move quickly while remaining within regulatory constraints.

With experience operating across Asia and multiple regulatory environments, the company brings a cross-border perspective to expansion, shaped by building distributed communities and organizations. The underlying insight is straightforward: the skills required to build and scale a learning ecosystem—coordination, trust and adaptability—translate directly to building a financial ecosystem.

Also read: Southeast Asia’s marketing renaissance: How up-and-coming marketers are leading the charge

Building for what comes next: what this partnership signals for fintech and enterprise partners

The NewCampus–Soul World Bank collaboration reflects a broader convergence between sectors that were once treated as separate. 

For fintech partners, it points to collaboration models that extend beyond pure SaaS offerings, where technology is paired with partners focused on operations, governance, and community design. 

For enterprise solution providers, it highlights an opportunity to move upstream—from selling tools to helping shape how institutions are structured and operated. Soul World Bank’s partnership with Chainstarters, an AI and real-world asset firm based in Connecticut, reinforces this trend toward complex ventures being built through multiple specialized partners working in concert.

Looking ahead, the Soul World Bank transaction is expected to close in the first quarter of 2026, with all milestones subject to regulatory approval. Beyond the timeline, the partnership raises a larger question about the types of partners new economy institutions will require as they take shape.

NewCampus’ positioning reflects a track record of building operational infrastructure for complex ventures, first in education and now applied to finance, offering a collaboration model that may become increasingly relevant at the intersection of finance, technology, and community. Overall, NewCampus is expected to navigate cross border complexity with the same defensible formula: community creates the system that scales. 

The transferable skill: Building ecosystems that last

The same skills that enabled NewCampus to build a challenger university are now being applied in a new context: the formation of a challenger bank. At its core, ecosystem-building is a transferable competency—one rooted in designing systems where participation is intentional, trust can form, and operations are able to scale without breaking.

As finance continues to evolve, the partnerships that shape the next generation of institutions may be defined less by technology alone and more by the ability to build durable communities and operational infrastructure. In that sense, the NewCampus–Soul World Bank collaboration offers a glimpse into how complex, multi-stakeholder ventures may increasingly be built—through collaboration, specialization, and shared institutional design.

Technology partners interested in exploring operational infrastructure collaborations for new economy ventures can reach out to NewCampus to discuss potential partnerships.

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The question isn’t whether your board understands today’s risks — it’s whether you’re governing for a future that hasn’t arrived yet.

As board members and executives navigating Asia’s dynamic markets, we face a distinct challenge: the very velocity of change in our region makes historical precedent an increasingly unreliable guide. What worked in governance terms even three years ago may be inadequate for the complexities emerging now. The regulatory shifts in China, the technological leapfrogging across Southeast Asia, the geopolitical realignments reshaping supply chains — these aren’t incremental changes requiring incremental responses. They demand boards that can anticipate, not just react.

Why futurist thinking belongs in the boardroom

Traditional governance frameworks ask boards to exercise oversight, ensure compliance, and manage known risks. This remains necessary but insufficient. Forward-looking governance recognises that the board’s fiduciary duty extends beyond protecting today’s enterprise value to stewarding the organisation’s relevance and resilience across multiple possible futures.

Consider the practical implications. When your board reviews a five-year strategic plan, are you stress-testing it against scenarios where digital currencies reshape treasury management, where carbon border adjustments fundamentally alter your cost structure, or where AI transforms not just operations but the very nature of competitive advantage in your sector? If these conversations feel speculative rather than essential, that’s precisely the gap forward-looking governance must close.

Also Read: How biotech is changing the global agriculture game for investors

The Asian context demands it

Our region presents specific imperatives. Family-controlled enterprises navigating generational transitions must balance legacy preservation with radical adaptation. State-linked entities face the complexity of commercial imperatives intersecting with policy objectives that themselves are evolving. High-growth companies in technology and manufacturing confront the reality that regulatory frameworks are being written in real-time, often in response to the very innovations they’re pursuing.

Moreover, stakeholder expectations in Asia are shifting with particular intensity. ESG is no longer a Western import but increasingly embedded in local capital allocation decisions, talent acquisition, and social license to operate. Boards that treat this as a compliance exercise rather than a strategic and operational imperative are already behind.

What forward-looking governance requires

This isn’t about crystal balls or abandoning governance fundamentals. It’s about augmenting traditional board competencies with three capabilities:

• Structured foresight: Building systematic processes to identify emerging risks and opportunities beyond the typical planning horizon. This means engaging with weak signals — the regulatory proposal still in consultation, the technology still in labs, the social trend visible in adjacent markets — before they become urgent crises or missed opportunities.
• Adaptive oversight mechanisms: Ensuring your governance architecture itself can evolve. When disruption accelerates, the cadence of board meetings, the composition of committees, and the information flows that boards rely upon may all need reassessment. Does your board’s calendar reflect the actual velocity of change in your business environment?
• Strategic courage informed by rigorous analysis: Perhaps most critically, forward-looking governance means cultivating the board’s capacity to make decisions under deep uncertainty. This requires both intellectual rigour — scenario planning, red-teaming assumptions, diverse expert input — and the institutional courage to act on convictions about the future even when consensus is elusive.

Also Read: Funding for good: Why investors should bet on tech with measurable social impact

An invitation to dialogue

Having worked across financial services, airlines, e-commerce, government, telcos, and more — from agile startups to sprawling, highly matrixed multinationals spanning Asian and global markets, I’ve watched boards grapple with these questions. The best ones aren’t just asking these questions. They’re embedding foresight into strategy reviews, bringing future-relevant expertise into the boardroom, and carving out real time to debate where they’ll be in five years, not just next quarter.

The boards that will distinguish themselves in the coming decade won’t be those that governed the past most efficiently, but those that prepared their organisations most effectively for futures that few could clearly see. This is the essence of forward-looking governance — and it’s not optional in Asia’s rapidly evolving landscape.

The question for your board: When you look at your agenda for the next meeting, what percentage addresses what has already happened versus what should happen next? The answer to that question may reveal how ready you are for the governance challenges ahead.

This article was first published on The Boardroom Edge.

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Southeast Asia’s startup ecosystem has entered a more sober phase. Capital is harder to access, growth expectations are sharper, and teams are being asked to deliver more with fewer resources. In this environment, hiring has quietly become one of the most critical and expensive decisions a company makes.

Yet, recruitment methods across the region have barely evolved. Many organisations still rely on manual resume screening, subjective interviews, and long coordination cycles. These approaches may have worked when teams were small and timelines forgiving, but they struggle when companies hire across countries, functions, and time zones. This growing mismatch between how companies hire and how fast they need to operate is where AI is beginning to play a meaningful role.

The real cost of slow and inconsistent hiring

In a tighter market, hiring mistakes show up quickly. A delayed hire slows execution. A poor hire drains management time and morale. For early- and growth-stage startups, these costs compound fast. Across Southeast Asia, several issues are common:

• Recruiters are overwhelmed by application volume
• Interview quality varies from one interviewer to the next
• Scheduling stretches hiring cycles unnecessarily
• Early-stage bias filters out capable candidates
• Candidates disengage due to slow or unclear processes

These issues directly affect a company’s ability to execute, particularly when operating with lean teams and limited runway.

Why precision hiring matters more than ever

In today’s market, hiring is no longer just about filling roles quickly. It is about making fewer mistakes and getting more value out of every hire. This is where precision hiring becomes critical.

Precision hiring means reducing guesswork at every stage of the recruitment process and clearly defining what a role actually requires, evaluating candidates against consistent criteria, and making decisions based on evidence rather than intuition alone. As startups operate with tighter budgets and leaner teams, the margin for hiring error has narrowed significantly.

In Southeast Asia, this need is amplified. Talent markets are diverse, career paths are often non-linear, and resumes do not always reflect true capability. Relying solely on unstructured human judgment increases the risk of bias, inconsistency, and missed potential. Two interviewers can walk away from the same conversation with very different conclusions. Multiply this across teams and countries, and hiring outcomes become unpredictable. As organisations scale, this inconsistency turns into a real operational risk.

Also Read: The future of recruitment in Web3 era

AI enables precision by introducing structure where human effort struggles to scale. It helps clarify job requirements, standardise early evaluations, and surface clearer signals about candidate capability. The result is not automated decision-making, but better-informed human judgment.

A shift toward structure and skills

Many startups are rethinking how they evaluate talent, and three shifts stand out.

First, there is a move toward skills-based hiring. Capability is increasingly valued over pedigree, which better reflects how talent develops in emerging markets.

Second, companies are recognising the need for standardisation. As teams grow, hiring can no longer depend solely on individual interview styles. Shared evaluation criteria are becoming essential to ensure consistency.

Third, AI is being introduced in areas where human effort does not scale well—particularly in screening and early-stage interviews.

Where AI actually helps

The most practical use of AI in recruitment today is not decision-making, but consistency. AI-led or AI-assisted interviews help standardise early-stage conversations. Questions are structured, follow-ups are consistent, and candidates are assessed against the same dimensions.

For startups, the impact is tangible. Hiring cycles shorten. Candidate drop-off reduces. Feedback becomes more reliable. Recruiters spend less time coordinating and more time evaluating. AI manages volume; humans retain judgment.

AI also addresses long-standing challenges such as high application volumes, subjective interviews, slow scheduling, delayed feedback, and unconscious bias—issues that have historically weakened decision-making and damaged candidate experience.

From gut feel to clearer signals

Hiring will always involve intuition, but intuition works best when supported by clear signals. AI tools increasingly provide structured input such as interview transcripts, skill alignment, communication clarity, and problem-solving indicators.

These insights do not replace human judgment. Instead, they make it more grounded. Some platforms apply this model by structuring interviews and evaluations while leaving final decisions with hiring managers. When used thoughtfully, this approach improves consistency without removing human context.

Also Read: AI-powered recruitment: Revolutionising hiring in Southeast Asia

AI-enabled recruitment systems also help standardise job requirements, accelerate resume screening, automate scheduling, and capture feedback in a comparable, data-backed format. Together, these capabilities enable faster hiring cycles, fairer evaluations, and smarter decisions—without proportionally increasing recruiter workload.

What this means for startups

As Southeast Asia’s startup ecosystem matures, execution quality will matter more than speed alone. Talent decisions sit at the heart of execution.

Over the next decade, hiring is likely to become faster but more deliberate; more structured yet still human-led; focused on capability rather than credentials; and increasingly transparent and accountable. Startups that adapt their hiring practices early will make fewer costly mistakes as they scale.

AI is not here to replace recruiters or founders. Culture, leadership potential, and team dynamics cannot be automated. What AI can do is remove friction — long delays, inconsistent screening, and avoidable bias, so humans can focus on decisions that truly require judgment.

In today’s startup environment, hiring is a strategic function. AI is not changing hiring by making it impersonal; it is changing hiring by making it more precise. For startups in Southeast Asia, precision hiring may prove to be one of the most important advantages they build in the years ahead.

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Singapore’s modern workforce is an intricate tapestry woven not only from diverse cultures and skills but also from distinct generational experiences and expectations. Today, the office is commonly composed of Gen X, Millennials, and Gen Z, each shaped by unique social contexts and world events that influence their personalities, working attitudes, and career goals.

As of 2024, Millennials make up the largest share of the workforce at 43 per cent, followed by Gen X at 32 per cent, and Gen Z at 15 per cent. While Gen Z currently represents a smaller proportion, their presence is expected to grow rapidly. Projections suggest they will make up around 25 per cent of the workforce by 2030, largely shaping the trajectories of the employment landscape.

Gen X professionals have matured during turbulent times such as the Asian Financial Crisis, the Cold War, and the dawn of the internet era. They are often known for their resilience and work ethic. The economic uncertainty and rapid technological advancements they faced influenced their reputation as steadfast grinders, keen on climbing the professional ladder.

Millennials, known as the “sandwich generation,” bridge Gen X’s steadfast grinders and Gen Z’s vocalists. Launching careers amid globalisation and digital growth, they adapted quickly to evolving technologies and became agile hustlers. While tech-savvy, their skills are often surpassed by Gen Z’s native fluency, and they have adjusted their work styles as Gen Z shifted workplace culture toward new values and priorities.

Gen Z are true digital natives, shaped profoundly by the acceleration of Gen AI technologies such as ChatGPT. This generation champions flexibility, balance, mental health, and purposeful work, marking a clear contrast to older cohorts. Distinctively, Gen Z are vocalists in the workplace— unafraid to speak their minds.

The blend of these generations brings both vibrancy and complexity to Singapore’s workplaces. Employers face challenges in harmonising diverse mindsets, skillsets, and expectations across age groups. An employer may themselves embody a different generational perspective than their team, making “one size fits all” management strategies ineffective. Understanding these nuanced differences is essential to building inclusive, resilient, and innovative workplaces that leverage generational strengths.

Generational differences in career aspirations

Generational differences in career priorities are evident across Singapore’s workplaces. It shapes not just what individuals value, but also how employers must engage and retain talent.

For Gen X, the digital and automation era has intensified concerns about job stability and security. This generation remains attentive to practical needs—competitive compensation, healthcare benefits, retirement savings (such as CPF), and supporting children’s education—reflecting a focus on security and tangible rewards as they navigate the risk of technological displacement.

Millennials, by contrast, are driven by aspirations for career progression and development opportunities. They seek clear advancement pathways, leadership roles, and continuous learning, wanting to work for organisations that offer purposeful missions and tangible social impacts alongside professional growth. For these workers, personal fulfilment and societal contribution increasingly intersect with traditional ambitions.

Gen Z, meanwhile, diverge even further—valuing flexibility and autonomy above all. For them, hybrid work options, flexible hours, and freedom in how tasks are approached are not added perks, but basic expectations in the modern job landscape. Just as importantly, Gen Z highly prioritises work-life balance and the ability to pursue interests beyond work, placing strong emphasis on mental health and personal well-being. They expect employers to support this ethos, making the pursuit of balance and autonomy integral to their choice of workplace.

Also Read: Are you a human resource?

Rising costs of living and salary transparency have driven Gen Z fresh graduates to enter the workforce with significantly higher salary expectations compared to previous generations. According to the 2024 Graduate Employment Survey, the median gross monthly salary for fresh graduates in full-time permanent employment rose to SG$4,500 (US$3,492), up from SG$4,317 (US$3,350) in 2023. This shift reflects heightened salary demands by the younger cohort, leading some employers to hesitate in hiring fresh graduates. Some opt for candidates with industry experience or replace roles with technology due to cost considerations.

Given such diverse priorities and evolving salary expectations, employers can no longer rely on traditional offerings like salary, annual leave, or medical benefits alone to attract, motivate, and retain talent. Instead, organisations must adopt a more holistic, flexible approach—empowering line managers to work closely with team members.

Embracing digital diversity for workplace cohesion  

Technological disparity among Gen X, Millennials, and Gen Z is a defining feature of today’s multigenerational workplace, requiring thoughtful attention from employers before introducing new processes or systems.

Gen X entered the workforce amid typewriters, fax machines, and the earliest computers. For many, digital adoption occurred mid-career, where they picked up productivity tools like Word, Excel, and email. However, they may be less comfortable with advanced cloud collaboration, data analytics tools, or AI-driven software unless they have upskilled through training. Their strengths often lie in institutional knowledge and business acumen rather than digital agility, making rapid adoption of new tech platforms a greater challenge.

Millennials, whose formative years coincided with the rise of Windows computers, Internet connectivity, and mobile phones, have a natural ease with digital tools and communications. Most are proficient in enterprise platforms, social media, and online research, adept at adopting new digital workflows, and flexible with evolving work technologies. However, they may still feel less “native” than Gen Z when it comes to cutting-edge trends like AI prompt engineering, advanced data visualisation, or blockchain solutions.

Gen Z, on the other hand, are truly digital natives—raised in an environment dominated by smartphones, high-speed internet, and cloud-based platforms. Their exposure to coding, digital creation tools, and seamless multitasking across devices means they possess unparalleled digital agility and confidence in picking up new apps or software. They are quick to adopt new tools but may lack depth in legacy enterprise systems and soft skills needed.

Also Read: Anchanto CEO on why human resource is essential for a growth stage startup

For employers, the difference in the pace of technology adoption across generations cannot be overlooked. Gen X may show resistance when new systems are introduced, requiring more support and reassurance. Educating older workers on the use and benefits of technology is beneficial, giving them time to adapt and creating opportunities to build new capabilities, such as AI adoption. By recognising these varying paces and adopting inclusive strategies, organisations can harness the strengths of all generational cohorts and achieve cohesive progress in an increasingly digital business environment.

Navigating generational communication styles at work  

Different generations in the workplace exhibit distinct communication styles shaped by their formative experiences and technology exposure.

Gen X professionals, accustomed to traditional modes of communication and with a preference for direct, concise communication, typically prefer face-to-face interactions and formal channels like email. For most of their careers, remote work was uncommon, and many relied on direct, official communication methods for clarity and efficiency.

Millennials began their careers similarly but adapted to more digital communication tools with the rise of remote work, especially during the COVID-19 pandemic. They value frequent feedback and are versatile, comfortably switching between emails, instant messaging, and video conferencing based on the context, showing adaptability in communication preferences.

Gen Z entered the workforce post-pandemic, with remote and hybrid work norms firmly established. They prefer informal, casual, quick communication through platforms like WhatsApp, Microsoft Teams, or Zoom.

Also Read: Scaling is hard: Here are 7 things Human Resources can do to manage it

While many Gen Zs are vocal about workplace matters, this tends to be the case only when they feel engaged — disengaged individuals are often less outspoken. Employers should actively demonstrate that feedback is heard and acted upon to better manage and retain this cohort.

With these generational differences, communication gaps can arise if no understanding is established, potentially leading to miscommunication. Employers must foster awareness and create environments where diverse communication preferences are respected and bridged effectively, ensuring that message delivery remains consistent and inclusive across all generations.

Leading across generations: A call for flexibility and inclusion

In today’s diverse workforce, differences exist not only among employees but also within leadership and management teams, as individuals come from varying generations. These generational differences can significantly impact working relationships, team dynamics, and overall performance.

Employers must recognise that a one-size-fits-all approach will not work. As Gen X and Millennials increasingly find themselves managing Gen Z, it is vital to recognise that this younger cohort brings a distinct set of expectations and perspectives on work. Leaders must step beyond their comfort zones to communicate, engage, and include Gen Z in meaningful ways. When properly engaged and their energy channelled, Gen Z can be a powerful asset. They can leverage their digital agility to challenge the status quo, driving innovation and strengthening the business landscape.

Acknowledgement: Bahvaani A, Assistant Research Manager, IndSights Research.

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I have always believed that a voice does not expire. It grows, shifts and sometimes hides, but it never disappears.

As a coach, I encourage people to share their stories. On stage. Online. In classrooms and in life. Some tell their stories with trembling voices. Some cannot speak them at all.

Now with AI, a new kind of storytelling is possible.

When the story is true, it finds a way

I often tell my learners, AI can help you tell your story, but it cannot feel it for you. You can use AI to help with your script, your visuals or even your voiceover. But the story still needs to come from your truth, your thoughts, your emotions, your experiences.

AI can generate words, but it is your meaning that gives them heartbeat. AI can sing your song, but it is your story that gives it soul.

When I created my first AI song, I put pieces of my own story into it. It was fun, simple and a little silly, but it felt alive. Because even when a digital voice sang it, the story behind it was mine. Our voices evolve, they do not end.

From stage to screen to AI storytelling

Not everyone dares to speak on stage. Some struggle to record videos because they do not like their voice or fear judgment.

Now with AI narration, you can still tell your stories. You can write your thoughts and let AI speak them for you. You can create a video, an animation or even a song that carries your message.

AI gives us another way to share what matters. It does not replace us. It supports us. It is like having a digital friend whispering, you can do this.

The important thing is not how you tell the story. It is what you do.

Also Read: AI, authenticity and the future of founder storytelling

Stories that evolve, not fade

The most beautiful part of AI storytelling is that it preserves stories that might otherwise be lost. You can record your wisdom, your memories, your ideas and let them travel further than your lifetime. You can turn reflections into AI videos, podcasts or songs. You can even animate your story so your grandchildren will one day see and understand who you were.

That is legacy, not fame, but remembrance.

Our stories evolve. From notebooks to microphones. From live stages to digital screens. And now, through AI voices that echo our own truths.

The creative inside me

The creative inside me is enjoying every new AI feature and trying everything I can. Calling all the crazy, creative people out there, get those juices spilling out. No right or wrong. Art is a rebel. So create. Experiment. Play.

Let the tools help you discover new ways to express who you are because creation is not about control. It is about freedom.

The gentle reminder

You do not need to sound perfect to be powerful. You just need to be honest.

AI can help shape your story, sing it or even speak it for you. But what matters most is that it is still your story. Your thoughts. Your ideas. Your voice.

So whether you share it on stage, online or through AI storytelling, remember this. Your voice does not expire. It evolves.

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JP Morgan Chase (JPMC), the world’s largest bank by market capitalisation, has acquired Sri Lankan fintech startup WealthOS for an undisclosed sum.

The deal — first reported by The Examiner — is described as a buyout of all existing shareholders, enabling both investors and employees to cash out.

Also Read: From civil war to innovation: nVentures’s Chalinda on the rise of Sri Lanka’s entrepreneurship

While the price tag has not been made public, a source familiar with the transaction told The Examiner that the deal is larger than the London Stock Exchange Group’s acquisition of MillenniumIT, which was valued at US$30 million in 2009. If accurate, that puts WealthOS in the mid-eight-figure-plus exit range, marking one of the most significant outcomes in Sri Lanka’s modern startup ecosystem.

What WealthOS does

Founded in late 2019 by Anton Padmasiri and Chamat Arambewela, UK-incorporated WealthOS builds software that helps financial institutions run wealth management digitally. Rather than being a consumer investing app, it is closer to “infrastructure”: the kind of platform a bank or wealth manager uses behind the scenes to onboard clients, manage portfolios and products, automate workflows, and integrate with other systems via APIs. It enables a wealth business to operate at scale without constantly patching legacy technology.

The fintech currently employs over 50 people in Sri Lanka and four in the UK. Barclays and Singapore- and Sri Lanka-based nVentures are also its investors.

“This is the fund’s [nVentures] second successful exit. From the start, our focus has been on identifying exceptional founders early, supporting them closely, and staying engaged as they build. Outcomes like this reinforce our approach to early-stage investing and the kind of long-term value we aim to build as a fund,” said nVentures’s Managing Partner Chalinda Abeykoon in a LinkedIn post.

Why JP Morgan Chase is acquiring WealthOS

For JPMC, the strategic logic is straightforward: banks increasingly compete on the quality and speed of their digital wealth experiences, and modernising wealth infrastructure internally can take years. Acquiring a platform like WealthOS can deliver three immediate advantages.

1. Speed: Buying a functioning product and a delivery team shortens timelines for upgrading or launching digital wealth capabilities.
2. Architecture: A platform built in the past few years is typically more API-friendly and easier to integrate than older, monolithic wealth stacks.
3. Talent and execution: Sri Lanka has a reputation for strong engineering, and an established Colombo-based team can accelerate delivery while reducing build risk.

How big a deal is this for Sri Lanka’s exit track record?

Sri Lanka is rich in technical talent and respected tech companies, but large, clean, venture-style exits remain uncommon.

Also Read: Small market, big dreams: Meet the 30 Sri Lankan startups that are punching above their weight

The Examiner report notes that WealthOS is the “fourth major exit” following MillenniumIT, WSO2, PickMe, and Ncinga. One clearer Sri Lanka-linked fintech acquisition in recent years is Kaiju Labs, which was acquired by KAST Finance in November 2024. Against that backdrop, a JPMC acquisition of WealthOS would stand out not only for size but also for the buyer: a global-tier financial institution, not a regional consolidator.

Sri Lanka’s startup scene and fintech’s evolution over the past 4-5 years

Sri Lanka’s startup ecosystem is best characterised as small but technically strong, with a concentration in software and product engineering, enterprise IT, and fintech-adjacent categories such as commerce enablement. The country has hundreds of active startups, supported by hubs and industry bodies such as Hatch and SLASSCOM-linked programmes, alongside public-sector-linked initiatives that have aimed to catalyse entrepreneurship and digital adoption.

Fintech in particular has evolved rapidly since roughly 2020, driven by three forces: COVID-era digitisation, the push for more efficient payment and commerce infrastructure, and the behavioural shift accelerated by the economic crisis, which encouraged merchants and consumers to adopt more trackable, cash-light options.

Who are the top fintech players to watch in Sri Lanka?

Sri Lanka’s fintech landscape spans payments, merchant enablement, lending/BNPL, and wallet ecosystems. Notable names frequently cited by market watchers include:

• PayHere (online payments and SME merchant tooling)
• Koko (consumer credit/BNPL-style product)
• Mintpay (BNPL pioneer, now part of Atome Financial)
• Genie (a major wallet/super-app product backed by an incumbent; influential even if not a classic VC startup)
• LankaPay (not a startup, but critical national payments infrastructure that many fintechs build atop)

What the WealthOS deal could change

If the reported details hold, it could be a confidence event for Sri Lanka’s startup ecosystem. Employee and early-investor liquidity can seed a “second generation” of founders and angels, strengthening the local capital and mentorship layer. It also reinforces the country’s positioning as a place that can produce globally relevant financial infrastructure products, not just engineering services.

Also Read: Re-awakening Sri Lanka’s legacy of innovation: The story of TRACE

In practical terms, the deal signals that the path from Colombo-based product development to global outcomes is real, and that may be the most important datapoint for founders and investors watching Sri Lanka’s next wave.

“JPMorganChase’s acquisition of a company entirely powered by Sri Lankan talent is a strong signal of our island’s ingenuity. It raises confidence across the ecosystem and sets a higher bar for founders building globally from emerging markets,” added Abeykoon.

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January 22 delivered a compelling narrative of a global financial landscape in flux, where traditional equities soared on the wings of diplomatic optimism while the volatile realm of digital assets cooled significantly. The day was marked by a second consecutive session of gains for major US stock indices, a direct consequence of easing geopolitical tensions and a corresponding retreat of the US dollar. This confluence of factors painted a complex picture for investors everywhere, highlighting a clear rotation of capital back into regional markets and safe-haven commodities.

My view is that these events highlight a fragile market sentiment, heavily influenced by headline news and the immediate unwinding of risk positions. The market’s sharp positive reaction to President Trump’s reported “framework” deal over Greenland, which ostensibly cooled global tensions and averted a looming trade war with new European tariffs, reveals a nervous system quick to price in relief. This optimism was evident in the performance of the S&P 500, which advanced 0.55 per cent to close at 6,913.35, the Dow Jones Industrial Average, which rose 0.63 per cent (306.78 points) to 49,384.01, and the Nasdaq Composite, which gained 0.91 per cent to settle at 23,436.02. This movement was not without specific stock stories, as tech giants such as Nvidia, Microsoft, and Meta Platforms all ended higher, and Intel shares rose slightly ahead of their quarterly results. Conversely, Abbott Laboratories shares fell sharply, reminding us that company-specific fundamentals, such as the impact of higher prices on sales growth, always matter, even amid broader market rallies.

The easing of global tensions also had a palpable effect on commodities and currencies. The US dollar index was 0.5 per cent lower at 98.30, marking its biggest single-day fall in a month. This decline acted as a potent catalyst for gold, the traditional safe-haven metal, which soared to an all-time high, climbing above US$4,960 an ounce in the spot market. It is a classic market reaction: a weakening dollar and reduced global risk perception often see a surge in the appeal of the yellow metal. Concurrently, WTI crude futures fell below US$60 a barrel, declining more than two per cent to US$59.35, as the geopolitical risk premium that often elevates oil prices evaporated with news of the diplomatic breakthrough. The bond market remained relatively stable throughout, with the 10-year Treasury yield at approximately 4.25 per cent, little changed from the previous day’s close.

Also Read: JP Morgan acquires WealthOS in landmark Sri Lanka startup exit

However, a different, more cautious mood permeated the digital asset ecosystem. While traditional assets rallied, the crypto market fell 0.64 per cent over the last 24 hours, extending a seven-day decline of 6.5 per cent. This divergence suggests a distinct risk-off environment within the crypto space, driven by specific structural concerns rather than immediate global headlines. My take is that the crypto market is currently grappling with a crisis of conviction, primarily stemming from large institutional players. The data is clear: spot Bitcoin ETFs recorded US$1.58 billion in net outflows this week, a powerful signal of institutional profit taking and reduced exposure. This consistent selling pressure is outweighing retail buying, creating a market that lacks a necessary institutional bid to support prices.

The lack of institutional support is compounded by a significant plunge in trading activity. Total 24-hour trading volume fell 32.8 per cent to US$98.43 billion, with derivatives volume down 37 per cent. This sharp drop indicates low trader conviction and reduced liquidity, making prices prone to slippage even on modest sell orders. In thin markets, downward moves are often amplified. Technically, the market is testing a critical support level at the 78.6 per cent Fibonacci retracement level of US$3.01 trillion global market cap. The RSI sits at 43.74, neutral but weak. The conclusion I draw is that this is not a broad market panic but a targeted period of consolidation rooted in institutional caution and evaporating volumes.

For holders, the immediate future hinges on whether these ETF outflows persist and if that crucial US$3.01 trillion support level can hold firm over the next 48 hours. The contrasting performance of traditional and digital markets on this day provides a fascinating study of how different asset classes react to unique combinations of macro and microeconomic pressures.

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The lead image of this article is generated by AI.

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Singapore has launched a new Model AI Governance Framework for Agentic AI, positioning itself at the forefront of global efforts to regulate the responsible deployment of advanced AI systems, including AI agents.

Announced on January 22 at the World Economic Forum, the framework was introduced by Minister for Digital Development and Information Josephine Teo. Developed by the Infocomm Media Development Authority, the framework is the first in the world to provide a comprehensive, practical guide for organisations deploying agentic AI responsibly.

The framework builds on Singapore’s original Model AI Governance Framework for AI, introduced in 2020, and reflects the country’s balanced approach to AI governance. It seeks to put guardrails in place to manage risks while leaving room for innovation, ensuring that the benefits of AI agents can be realised in a trusted and safe manner.

Unlike traditional or generative AI, AI agents can reason, plan across multiple steps and take actions on behalf of users to achieve specific objectives. These capabilities allow organisations to automate repetitive tasks in areas such as customer service and enterprise productivity, freeing up employees to focus on higher-value work and supporting broader sectoral transformation.

However, the increased autonomy of AI agents also introduces new risks. These systems may have access to sensitive data and the ability to make changes to their environment, such as updating databases or executing payments. This raises the risk of unauthorised or erroneous actions, as well as challenges around human accountability. One concern highlighted is automation bias, where users may over-trust AI agents that have performed reliably in the past.

Also Read: Voice does not expire: How AI helps us keep our stories alive

To address these issues, the new framework emphasises that humans remain ultimately accountable for the actions of AI agents. It stresses the importance of maintaining meaningful human control and oversight throughout the deployment and use of agentic AI.

Targeted at organisations deploying AI agents either in-house or through third-party solutions, the framework offers a structured overview of key risks and emerging best practices. It provides guidance across four main dimensions: assessing and bounding risks upfront by selecting appropriate use cases and limiting agent autonomy and access; ensuring human accountability through clearly defined approval checkpoints; implementing technical controls throughout the AI agent lifecycle, including baseline testing and controlled access to approved services; and enabling end-user responsibility through transparency, education and training.

The framework was developed with input from both government agencies and private sector organisations. April Chin, co-chief executive officer of Resaro, said the framework fills a critical gap in policy guidance by addressing the specific risks associated with agentic AI. She noted that it helps organisations define agent boundaries, identify risks and implement mitigations such as agentic guardrails.

IMDA described the framework as a living document and said it welcomes feedback from interested parties, as well as case studies demonstrating responsible deployments of AI agents. Building on its existing starter kit for testing large language model-based applications, the authority is also developing additional guidelines focused on testing agentic AI applications.

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