Not everything needs to be automated. Not every process is better because it’s faster. We have to be brave enough to ask: is this what good work looks like? And, is this what we want progress to feel like?
That kind of reflection is not a soft skill. It’s a leadership skill. And it’s what will set resilient organisations apart in the next decade.
Our wisdom about technology has never come solely from Silicon Valley. It has emerged from kampungs and callejones, from night markets and gaming cafés, from shared family phones and gig economy hacks. We already know how to remix, adapt, question, and make things our own.
So as AI reshapes what work looks like, maybe our goal isn’t to pick a side—to work with or without it—but to hold space for complexity. To recognise that we may need to do both, or neither, depending on the situation.
A region in flux, and not just digitally
We’re used to navigating multiple truths at once. A GoJek rider in Jakarta might stream TikToks between gigs, using the same phone to track his mother’s blood pressure remotely via an AI-powered app. A sari-sari store owner in Cebu might use a chatbot to reorder stock, while still tracking sales manually in a notebook. In Phnom Penh, factory workers are now operating alongside semi-automated conveyor belts, even as their wages remain flat.
This is a region that moves fluidly between high-tech and low-tech, tradition and reinvention. So why would our response to AI be any different?
To ask “should we train for jobs AI can’t do?” or “should we learn to work alongside it?” implies a clear line between human and machine. But in practice, that line is often blurred.
Human jobs? Or human judgment?
There are jobs AI can’t do—at least not well. Emotional care work, creative direction, conflict mediation. A machine can write a poem, but can it feel the pulse of a nation in protest? It can generate a sympathy message, but can it sit beside a grieving mother and know when to stay silent?
These are deeply human tasks. But let’s not idealise them.
Not every job left behind by AI will be meaningful or well-paying. A lot of what remains will still be hard, under-appreciated labor. In many cases, the more “human” the work, the less valued it tends to be—especially in lower-income parts of our region. Are we ready to address that?
At the same time, learning to “work with AI” isn’t as simple as handing out prompt engineering guides. Real collaboration requires something deeper: judgment.
Can a teacher tell when an AI-generated test has biases built in? Can a logistics manager see when the optimisation algorithm is shortchanging rural routes because it doesn’t see their worth? Can a startup founder ask: who trained this model, and in whose language? These are skills of interpretation, of contextual reading—of power, not just productivity.
The most important skill might be asking better questions
Up-skilling shouldn’t just mean learning Python or how to use Midjourney. It should mean asking: “What’s at stake in how this AI tool is used?”
For people leaders, HR professionals, policymakers, and educators in Southeast Asia, this means rethinking how we talk about readiness. It’s about seeing systems: to understand where power lies in algorithmic decisions, to recognise how AI might amplify inequality if left unchecked, to bring lived experience into technology design.
What we need is not just skills to work with AI or outside of it. We need a mindset that is:
Curious about how AI works,
Skeptical about where it fails,
Empowered to push back when it doesn’t serve people,
And imaginative about how to build better tools that reflect our values and cultures.
This is not an easy thing to teach. But it may be the most essential thing to learn.
Because the future of work won’t be written only in code. It will be written in culture. And culture, thankfully, is something Southeast Asia knows how to build.
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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.
As generative AI continues its rapid integration into the business landscape, leaders face a fundamental question: Does effective AI implementation mean we’ll need fewer human workers? The answer isn’t as straightforward as many might expect.
While certain routine tasks will undoubtedly be automated, the relationship between AI and human work is proving to be more complementary than competitive, particularly at the executive level.
For Chief Marketing Officers and Chief Executive Officers, this technological revolution isn’t simply about adaptation; it’s about transformation. The skills that made these leaders successful in the past may not be sufficient for navigating the AI-augmented future. This article explores how the executive skillset must evolve to thrive in this new landscape.
The shifting work paradigm
Before diving into specific leadership skills, it’s important to understand the broader context of how AI is reshaping work. Several key dynamics are emerging:
Complementary roles are expanding: As AI takes over routine tasks, humans are increasingly focused on oversight, customisation, ethical considerations, and managing complex edge cases.
Productivity gains are creating new opportunities: Organisations effectively implementing AI often become more productive and expand operations, potentially creating new positions even as they automate others.
New value categories are emerging: Much like previous technological revolutions, AI is creating entirely new industries and job categories that weren’t previously imaginable.
Human capabilities remain essential: Areas requiring emotional intelligence, ethical judgment, creative thinking, and interpersonal skills continue to need human workers, though increasingly augmented by AI.
Adoption varies significantly: AI implementation differs across sectors, regions, and organisational types, creating a mixed landscape rather than uniform reduction in workforce needs.
In this environment, the question isn’t whether we need fewer workers overall, but rather how the composition of work is changing—and what that means for those in leadership positions.
The evolving CMO: From campaign manager to AI-human orchestra conductor
The Chief Marketing Officer’s role is perhaps experiencing the most immediate disruption from generative AI. As marketing becomes increasingly data-driven and content creation becomes AI-assisted, CMOs must develop several critical skills:
AI literacy and strategic integration
Today’s CMOs need more than a surface-level understanding of AI. They must comprehend how various AI technologies can be strategically deployed across the marketing stack—from content generation and customer segmentation to predictive analytics and campaign optimisation. The most effective CMOs can distinguish between genuine AI capabilities and vendor hype, making informed decisions about which technologies truly serve their brand’s objectives.
Data governance expertise
As AI systems depend on vast amounts of data, CMOs must become stewards of responsible data practices. This means developing frameworks for ethical data collection, usage, and management that balance marketing effectiveness with consumer privacy and regulatory compliance. CMOs who excel in this area understand that data quality directly impacts AI performance, making governance not just an ethical consideration but a business imperative.
Human-AI collaboration design
Perhaps the most nuanced skill for modern CMOs is designing workflows where human creativity and AI capabilities complement rather than compete with each other. This requires identifying which aspects of marketing benefit from human intuition, emotional intelligence, and creative spark, versus which elements can be enhanced or accelerated through AI assistance.
Agile experimentation mindset
As AI tools evolve at breakneck speed, CMOs must foster a culture of continuous experimentation while maintaining brand safety. This means implementing frameworks for quickly testing new AI applications, measuring results, and scaling successful implementations—all while ensuring alignment with brand values and guardrails.
Personalisation ethics
AI enables unprecedented personalisation capabilities, but with this power comes significant responsibility. Forward-thinking CMOs are developing ethical frameworks for balancing hyper-personalisation with privacy concerns, avoiding algorithmic bias, and ensuring that personalisation enhances rather than manipulates the customer experience.
Adaptive content strategy
With AI-generated content becoming increasingly sophisticated, CMOs need to develop new approaches to content strategy. This includes creating clear guidelines for maintaining brand voice across AI-assisted content, establishing quality control processes, and building frameworks that allow for both scale and authenticity.
The transformed CEO: From decision-maker to AI transformation architect
While CEOs have always needed to navigate technological change, the scale and pace of AI transformation requires an evolved skillset:
AI transformation leadership
Rather than viewing AI as a series of isolated projects, successful CEOs approach it as an organisation-wide transformation. This requires developing a comprehensive vision for how AI will reshape the business model, customer experience, and operational processes—then orchestrating the cultural and structural changes needed to realise that vision. I.e. CEOs need to own the narrative and drive that vision forward, with AI as a subset of their digital strategy.
Talent reconfiguration
As AI reshapes job functions across the organisation, CEOs must become adept at reconfiguring their talent strategy. This includes identifying which roles may be automated, which new positions need to be created, and most importantly, how to reskill and redeploy existing talent to create maximum value in an AI-augmented environment.
Algorithmic accountability
As organisations increasingly rely on algorithmic and agentic AI decision-making, CEOs must establish governance structures that ensure responsible AI deployment. This means creating frameworks for algorithmic transparency, regular auditing for bias or unintended consequences, and clear policies for when human judgment should override algorithmic recommendations.
Strategic disruption analysis
The most forward-thinking CEOs are constantly analysing how AI might disrupt their industry’s value chain and competitive dynamics. This requires looking beyond immediate efficiency gains to identify potential new business models, unexpected competitors, and fundamental shifts in customer expectations that AI might enable.
Ethical AI decision frameworks
CEOs must establish clear principles for when and how to apply AI versus human judgment. This includes developing organisational values around AI usage that address ethical considerations like transparency, fairness, privacy, and the appropriate balance of automation and human touch in customer-facing processes.
Complexity management
Perhaps most fundamentally, CEOs must become adept at navigating the profound complexity that AI introduces. This includes managing the ambiguity of a business landscape where AI simultaneously creates and solves challenges, where competitive advantages can shift rapidly, and where the human implications of technological decisions are increasingly significant.
Finding the balance: Human leadership in an AI world
For both CMOs and CEOs, perhaps the most crucial skill is finding the right balance between embracing AI’s extraordinary capabilities while preserving the human elements that differentiate their organisations. The most successful leaders will be those who can:
Leverage AI to handle routine tasks while freeing humans to focus on higher-value creative and strategic work
Use technology to scale personalisation while maintaining authentic human connection with customers and employees
Enhance decision-making with data and algorithms while applying human wisdom to questions of purpose, ethics, and meaning
Drive efficiency through automation while investing in human capabilities that AI cannot replicate
In the final analysis, the future of work isn’t about choosing between AI and human workers—it’s about creating organisations where both can contribute their unique strengths.
For CMOs and CEOs, success in this new era won’t be defined by how effectively they replace humans with AI, but by how skilfully they integrate these powerful technologies while elevating the distinctly human contributions that will ultimately drive sustainable competitive advantage.
“The leaders who thrive won’t just be those who understand AI—they’ll be those who understand humanity in an age of intelligent machines.”
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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.
I came across this TED talk a while back called What Makes Us Human in the Age of AI by Brian Lowry, and there was this one line that really stuck with me.
The speaker said that as technology gets more predictable, our spontaneity, gut instincts, and emotional depth become what truly distinguish us. I can’t shake that thought as it keeps coming back, especially when I think about the people I work with now.
The real MVPs of the workplace
The teammates who really make a difference are the ones who can roll with uncertainty, pick up on subtle cues when something feels wrong, and read the room during tense team discussions. They ask questions that completely flip our perspective and stay cool when everything’s falling apart.
The inner stability they exude and quiet influence become the human traits I find myself turning to. AI has definitely sped things up for us, handling drafts, keeping us organised, crunching numbers, and even helping us brainstorm. Yet the person who actually changes the game brings something entirely different to the table.
One question that changed everything
There’s this moment from a hiring process last year that really drove this home for me. We had this one candidate who asked something near the end of our chat that caught me off guard: “What does success actually feel like for this team once we’ve reached our goals?”
The question showed me they were thinking in layers; they’re actually wondering and considering people, timing, ripple effects, and relationships. That question has stayed with me. We hired them, and it turned out that kind of layered thinking and emotional intelligence was exactly what we needed, even though I have stepped down from that company and she left not long after, we keep in touch to make sure we’re both still human.
This person just had this natural way of moving through our team with genuine empathy. They stayed steady when the pressure was on. When our tools crashed or we had to pivot plans, they were the one making sure everyone felt grounded through their presence. When we’d hit creative walls, they’d pause, ask something thoughtful, and gently guide us in a new direction. It shifted our whole dynamic in ways no project management tool ever could.
I’ve started noticing these moments more now. When someone creates space for the quiet person in the meeting. When they sense a teammate is struggling and check in because they genuinely care. When they instinctively know whether to push ahead or take a step back. These qualities are hard to capture on a job posting, yet I find myself looking for them constantly.
The long game
The technology will keep changing and improving. What I’m focused on now is building that ability to be a steady presence in all the chaos. I want to work with people who understand their own emotions and can support others while still moving things forward.
I want teammates who recognise what actually matters beyond just what’s urgent. In a world that’s always rushing, it’s easy to miss the long-term value of things like trust, subtlety, and genuine care. These are exactly what make work meaningful and keep teams healthy and creative.
So, what makes us human?
What I’m prioritising these days centres on thinking with integrity and interacting thoughtfully. I’m drawn to that kind of emotional intelligence that doesn’t need to be the loudest voice to create the most impact. So much of our future work will involve partnering with technology. The real challenge lies in preserving what makes working with actual humans so valuable.
So here’s what I’ve been wondering and I’m curious about your take:
How do you think about what makes us human, and what keeps you and your team genuinely human in this AI-driven world?
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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.
The post-pandemic era didn’t kill office culture. In fact, it rewrote what was once known as the “standard working culture”.The world is now introduced to a “remote-first” office culture.
Especially in Southeast Asia (SEA), where cost and growth pressures converge, a remote-first culture is a deliberate growth strategy.
But what does “remote-first” truly mean now, and what can businesses learn from SEA’s nimblest startups?
How SEA startups embraced remote culture as a strategy
SEA office culture has been a legacy of traditions where punctuality and presence often outweighed output.
But remote-first flipped the script.
Driven by the pandemic and accelerated by digital infrastructure, SEA startups are rewriting the rules – embracing remote-first not just as a necessity, but as a strategic model for agility, access, and retention.
From Manila to Ho Chi Minh City, the shift isn’t just about where people work – it’s about how and why they work.
COVID-19 sparked remote – Strategy made it stick
The pandemic created a sudden need for business continuity, forcing companies like Grab, Gojek, and Carousell to adopt remote operations virtually overnight.
But this shift wasn’t just a crisis response – SEA startups quickly embraced remote-first as a long-term model to boost flexibility and reduce operational risk.
In 2020, 74 per cent of CFOs globally reported plans to permanently move at least five per cent of their workforce to remote roles – a clear sign that remote work had evolved from emergency measure to strategic choice.
At the same time, governments in countries like Malaysia and Singapore began formally supporting flexible work arrangements (FWAs), signalling that remote-first was not a short-term fix, but a structural shift in how work gets done.
Why “remote-first”?
Now, let’s take a look at what’s bad from the old “office culture”
In major urban hubs like Singapore and Jakarta, high commercial rents made maintaining physical offices a financial strain. Beyond real estate, businesses faced growing overheads – from utilities to employee commuting costs.
By shifting to remote-first, startups reported saving 15–30 per cent in operational expenses – freeing up budget for what really matters: product, hiring, and growth.
A Gallup study in 2020 revealed that 76 per cent of employees experience burnout, with 28 per cent feeling burned out “very often” or “always”. Worse, 42 per cent of employees exposed to frequent office politics are actively disengaged from their work.
The result?
Burnout drives up sick days by 63 per cent and makes employees 2.6× more likely to quit.
And comes the solution – controversialat first, but it still works wonders: Remote-first working culture.
SEA startups think bigger than borders
SEA startups are no longer limited by geography – they’re hiring across 50 per cent of the region’s population.
Nomad List 2023 shows Vietnam, Thailand, and Indonesia leading global rankings for remote work appeal. SEA isn’t just exporting tech talent – it’s becoming a magnet for it.
Without needing a physical office, startups gained access to high-quality talent trained in global stacks and fluent in async culture – especially from Vietnam, Indonesia, and the Philippines. These resilient teams are intentionally built to be smarter, leaner, and more human-centred.
Redesigning work culture – How SEA startups embrace changes
SEA startups didn’t try to “replicate” the office – they reimagined how teams connect, collaborate, and build trust. Instead of relying on Zoom fatigue and physical proximity, they built digital-first rituals that scale.
A Singapore-based fintech replaced Zoom calls with a simple 3-question Slack check-in: What did I do yesterday? What’s today’s focus? Any blockers? This lightweight ritual freed up valuable focus time and increased employees output.
Remote culture in SEA startups works because it’s intentional – it’s backed by tools (Slack, Notion, ClickUp), async updates, and outcome-based management. This alignment builds morale and makes collaboration feel effortless, not forced.
Doing “remote-first” the right way in 2025
Remote-first is A mindset
It’s async, autonomy, and outcome
Remote-first isn’t just a work-from-home perk. It’s a new operating system for how modern teams work.
SEA startups aren’t just adopting remote tools – they’re building async-first systems that cut delays, reduce meetings, and speed up execution.
Tools like Notion, ClickUp, Miro, and Google Workspace aren’t used just for task management. They’re used to eliminate bottlenecks, boost clarity, and enable small teams to move globally at speed.
Because remote-first isn’t about flexibility. It’s about autonomy and outcomes.
Timezone isn’t a blocker – It’s a blueprint
Remote-first SEA teams don’t see time zones as obstacles. They design around them. That’s the mindset shift.
Instead of relying on live meetings, they build systems for clarity and autonomy: Everything from roadmaps, feedback, deadlines – is documented to create alignment without needing live meetings.
For example, distributed teams across Singapore and Indonesia use async updates, auto-synced task lists, and shared OKR dashboards to stay aligned.
From screen-watching to trust-building
Traditional office cultures reward presence – who’s online, who’s at their desk.
Remote-first flips that mindset. It rewards accountability over activity.
Today’s managers don’t track “active” statuses – they set clear, measurable goals, trusting team members to deliver results on their own terms. Leaders are shifting from managing hours to managing outcomes. Instead of micromanagement, they’re using KPIs and OKRs to guide performance.
But remote-first only works if trust is designed into the system.
That’s why SEA startups invest early in outcome-driven structures – not as a quick fix, but as a strategy for scale. Everything from tools to rituals to documentation is built around one goal: empowering people to own their work – without waiting for permission or presence.
Designing culture without a physical office
Work culture is architected
Remote-first culture doesn’t happen by accident. High-performing SEA startups build it with tools, rituals, and habits that foster connection and clarity.
Companies like Carousell and Gojek didn’t wait for “organic culture” to emerge. They designed it – with structured onboarding, celebration rituals, and consistent feedback systems.
In distributed teams, rituals replace physical presence. Weekly “wins” on Slack, async shoutouts, quarterly reflection calls, and remote buddy systems all strengthen team unity – even across time zones.
As SEA startups grow more diverse, especially with the rise of digital nomads, cultural intentionality becomes non-negotiable. Designing inclusive norms is no longer just an HR initiative – it’s a foundational part of remote-first scale.
Clarity + communication = culture
Remote teams must communicate with intent. Culture is how we align, not just how we vibe.
How you write is how you lead. Tone in messages, clarity in feedback, and responsiveness all signal what your company truly values.
Traditionally, SEA companies leaned on hierarchical, top-down communication. But remote work shifted that – flattening structures and pushing for clearer, more direct exchanges.
To build trust without a physical office, shared agreements beat shared tools. Set async norms (like reply windows, meeting etiquette), team agreements, and follow-up expectations then document them.
When communication is intentional, alignment follows. SEA startups that implemented transparent weekly updates saw 20–30 per cent increases in team satisfaction. Sharing OKRs, product roadmaps, and customer feedback publicly helped boost engagement and keep everyone rowing in the same direction.
The payoff?
Companies that invested in visibility and flexibility reported 25 per cent higher productivity and retention – proof that culture lives in communication.
How to start building remote culture now?
Remote culture doesn’t happen by accident – it’s designed with intention and consistency. Here’s how forward-thinking teams are making it real:
Pilot async standups: Replace daily calls with Slack check-ins using prompts like “What did I do yesterday? What’s today’s focus? Any blockers?”
Test no-meeting mornings: Kensington Grey introduced Thoughtful Thursdays to give teams focus time and reduce meeting fatigue.
Invest in digital-first onboarding: Create structured, warm welcomes with video intros, Notion welcome kits, and “buddy” pairings for new hires.
Redirect office budget into connection: Instead of long-term leases, startups could use tools like Flexday or allocate funds for micro-retreats and team travel to build in-person trust – without sacrificing flexibility.
Create team agreements, not assumptions: Establish working style norms to reduce misalignment across time zones.
Build micro-communities: Encourage cross-functional bonding through local meetups, client visits, or casual virtual rituals like “wins of the week.”
Why it works? Culture in remote teams isn’t passive – it’s built through rituals, visibility, and shared intention. Even without walls, trust can scale.
Remote-first is how the best teams scale today
SEA startups didn’t “go remote” because they wanted to. They did it because they had to.
Now, global founders and business owners are taking notes.
The lesson? Remote-first is not the end of company culture – it’s a new blueprint for scale, speed, and sustainability.
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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.
In an ever-changing business world, relevance and adaptability are critical for entrepreneurs. Starting and growing a business today is about more than generating profit; it’s about creating meaningful impact, fostering resilience, and positioning for long-term success. The broader societal shift towards a purpose-driven approach is a growing trend I have observed amongst entrepreneurs and startups: a dedication to purpose, strategic thinking, and continuous adaptation.
Purpose, responsibility, and impact
Purpose-driven businesses have a unique advantage. Businesses with a clear purpose that transcends mere profit-making tend to attract the right people to their teams and inspire them. They also tend to build a loyal customer following and secure a higher level of stakeholder support because of their impact on their industry and on society.
Defining your core values early on guides your decisions and builds a solid culture that tells people what your business stands for. It is not just a buzzword; it’s the social glue that pulls people together in their attitudes and beliefs and creates a unique culture of behaviour that endures, even when the going gets tough. This is perhaps one of the most important factors that create your branding that stands out against the competition.
Modern consumers and investors, especially millennials, are increasingly demanding responsible business practices. Sustainability and corporate responsibility are now business imperatives rather than optional extras. Entrepreneurs must consider how their operations align with environmental, social, and governance (ESG) principles.
Companies that prioritise sustainability not only future-proof their operations but also build trust and long-term loyalty. In today’s world, authenticity and responsible practices can differentiate your brand and make a significant impact. As they say, you should aim to “do good to do well.”
Now that we know “what” entrepreneurial businesses and startups should be like to thrive today, we shall explore “how” they must be managed for initial and long-term success in a rapidly evolving business landscape.
Drawing from years of working with and observing businesses, I’ve distilled three key principles to guide entrepreneurs and startups.
Launch fast, learn faster
One of the biggest challenges for startups is knowing when to launch. While the desire for a perfect product or service is understandable, waiting too long can be costly. Instead, I advise entrepreneurs to start with a minimally viable product (MVP) and get it into the hands of users as soon as possible. The objective is to collect feedback quickly and learn what truly resonates with your target audience. Early, real-world insights are far more valuable than assumptions made in isolation.
Consider preselling your concept to gauge demand and secure initial funding. By engaging early adopters willing to invest in your idea before it’s fully developed, you validate your business concept and generate revenue to support further growth. This approach minimises risk and accelerates your learning curve, allowing you to make meaningful improvements and adapt in real-time. Being agile and responsive can give you a significant edge in a competitive market.
As your business grows, it’s easy to feel tempted to diversify and chase multiple opportunities. However, spreading resources too thin can dilute your brand and hinder your progress. Instead, focus on one niche and being the best in it before even thinking of expanding. Becoming the go-to specialist in your particular niche will set you apart from those who try to “do everything” and build a loyal customer base. When you excel in one area, you establish authority, gain credibility, and make your brand memorable in the eyes of your audience.
Narrow specialisation is a powerful differentiator. A business known for doing one thing exceptionally well often attracts more dedicated customers and develops a more substantial reputation. Once you’ve dominated your niche, you can consider expanding into other areas—but not at the expense of diluting your branding in your niche area. This approach might be a bit tricky at first, but it will provide a solid foundation for sustainable growth, ensuring that your resources are used effectively and your brand remains strong.
However, even as you explore new opportunities, never lose sight of the core strength that brought you success. Growth should be strategic and well-paced, allowing you to adapt and maintain quality as you scale. Mastering your niche first creates a resilient platform from which your business can thrive.
Stay strategic amid success
Success, while exciting, can be a double-edged sword. When businesses begin to thrive, it’s easy to become overly focused on daily operations and short-term gains – because that’s where the money rolls in. But to stay in the game and achieve long-term success, thinking more strategically is paramount. Regularly assess your business model, evaluate your offerings, and ensure they remain relevant to your market. Managing your business strategically in this way prevents stagnation and keeps your business agile in a constantly evolving environment.
Being strategic isn’t just about reacting to trends; it’s about being proactive – anticipating shifts and putting yourself in a position to exploit the opportunities, and mitigate the threats, that they present. Ask yourself regularly: ‘Are we aligned with the market’s future direction?’ Keeping an eye on the world you operate in and how it is evolving will ensure that your proactive response is always timely, setting yourself up for sustained success. Businesses that remain reactive only will not stand the test of time.
The market is volatile and uncertain. Navigating it successfully and staying ahead requires a willingness to innovate and think long-term. Businesses that can effectively balance operations, innovation, and growth are usually the ones that not only survive but lead their industries. Ensure your company’s vision and strategy for the future are aligned and that they make sense in the context of the future market and business landscape. And don’t be afraid to pivot when necessary to maintain momentum.
Final reflections: Building a resilient, purpose-driven business
Entrepreneurship is a journey of constant learning and adaptation. Success is rarely linear, but staying grounded in purpose can guide you through the highs and lows. Launching fast, mastering your niche, and maintaining a strategic mindset are principles that can help you navigate the complexities of running a modern business. Purpose and impact should be at your venture’s core, driving every decision and inspiring those around you.
As we look towards 2025 and beyond, the entrepreneurial landscape will continue to evolve, but the fundamentals remain the same. Focus on what you can control: your commitment to adaptability, strategic thinking, and sustainable practices. By doing so, your business won’t just aim for financial success but will leave a lasting, meaningful mark on the world.
Lead with intention, stay agile, and never lose sight of the positive change you want to create. This approach will transform your startup from a short-lived venture into a resilient, impactful enterprise.
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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.
Singapore-based blockchain startup Startale Group has closed a US$63 million Series A funding round, led by a US$50 million injection from financial powerhouse SBI Group, with an additional US$13 million from Sony Innovation Fund.
The capital raise marks a significant leap for Startale’s ambitions to transform Asia’s on-chain capital markets and push the boundaries of blockchain adoption beyond niche use cases.
At its core, Startale builds infrastructure and applications that bring traditional financial assets and services onto the blockchain, creating seamless tokenised securities trading, stablecoin payments, and consumer-facing blockchain solutions. The company is co-developing Strium, a Layer 1 blockchain platform tailored for institutional investors to trade tokenised securities and real-world assets (RWA) around the clock.
Meanwhile, Startale’s native stablecoins—JPYSC, pegged to the Japanese yen, and USDSC, tied to the US dollar—are central to providing smooth fiat-to-crypto gateways alongside innovative features such as onchain dividend and yield distribution.
The latest funding round solidifies Startale’s strategy to vertically integrate blockchain infrastructure, financial ecosystems, and consumer applications into a comprehensive stack. This is particularly critical in Asia, where the complexity of legacy systems and regulatory fragmentation have hindered blockchain’s broader adoption in finance.
SBI Group’s involvement is not new; it has been a strategic partner since 2025, working alongside Startale to co-create core products, including Strium and JPYSC. With over 80 million customers across securities, banking, and insurance, SBI’s confidence in Startale reflects the startup’s ability to deliver institutional-grade financial products on-chain at scale, promising a radical overhaul of how banking and securities operate in the digital era.
Yoshitaka Kitao, SBI Group’s Chairman and CEO, summarised the partnership’s potential succinctly: “By joining the SBI Group’s digital space ecosystem, I am confident we can accelerate the on-chain transformation of society and demonstrate a strong competitive advantage by driving a vertical integration strategy in the digital finance sector.”
The growing adoption of stablecoins in Japan provides fertile ground for Startale’s ambitions. Japan’s regulatory environment has evolved to accommodate stablecoins, with growing institutional interest and consumer adoption driven by the need for faster, cheaper, and more transparent cross-border payments and settlements. The trust bank-backed JPYSC stablecoin is Japan’s first of its kind, offering greater legal certainty and security than many other stablecoins. This regulatory clarity, combined with the burgeoning demand for digital financial products, is rapidly accelerating Japan’s stablecoin ecosystem.
Startale intends to expand the adoption of JPYSC and USDSC across retail, enterprise, and institutional users. Their utility extends beyond simple payment instruments, providing functionalities such as automatic distribution of on-chain dividends and yields, integrating traditional finance’s value propositions with blockchain’s efficiencies.
In parallel, Startale is scaling Strium as an institutional-grade settlement and exchange framework for Asia’s trading of tokenised securities and real-world assets (RWA). This platform promises to enable 24/7 trading and real-time settlements, significantly enhancing liquidity and transparency compared to traditional markets tethered to business hours and manual reconciliation processes.
On the consumer front, Startale’s SuperApp platform is designed to abstract blockchain complexity behind a sleek interface that combines asset management, social features, payments, and “mini apps.” This unified experience aims to onboard millions of users to on-chain finance and the broader blockchain economy, further accelerating mainstream adoption.
This Series A round is also a testament to the growing convergence between finance, entertainment, and blockchain technology in Asia. Startale is building on partnerships with Sony that explore novel ways to integrate entertainment content and blockchain applications, carving out new user experiences and monetisation models.
For Southeast Asia, a region ramping up blockchain adoption amid diverse regulatory frameworks and vibrant fintech ecosystems, the rise of companies like Startale signals a maturing market infrastructure. Providing scalable, compliant blockchain solutions that bridge traditional finance and on-chain systems will be crucial to driving regional digital economy growth.
By weaving together infrastructure, stablecoins, institutional offerings, and consumer applications, Startale is strategically positioning itself as a cornerstone in the emerging on-chain financial landscape. The Series A funding not only validates this approach but also injects the firepower needed to execute aggressive growth plans.
In short, Startale’s ability to deliver on-chain financial products at an institutional scale could redefine banking, securities, and financial services in Asia. The move towards tokenisation and stablecoin-driven ecosystems has the potential to drastically cut costs, speed up transactions, and open new avenues for investment and consumer engagement—ushering in a new era of digital finance.
Supply chain cyberattacks are no longer a niche concern reserved for multinationals with sprawling vendor networks. They are becoming a routine business risk, and Southeast Asia is entering that reality while still short of security talent, uneven in basic cyber hygiene and heavily dependent on third-party technology providers.
That is the clearest takeaway from a new Kaspersky-commissioned survey of 1,714 enterprise IT and security decision-makers across 16 countries, including Singapore, Vietnam, India, Indonesia, and China.
The headline finding is stark: one in three organisations globally said they had been hit by a supply chain attack in the past year. Yet many still lack the people, internal discipline, and contractual leverage needed to deal with the problem.
Talent shortages and operational overload are compounding risk
Globally, 42 per cent of respondents said the shortage of qualified IT security workers was a major barrier to reducing supply chain and trusted relationship risks. The same share said organisations are struggling to prioritise among too many security tasks, leaving third-party risk management exposed.
That lands uncomfortably well in Southeast Asia, where businesses have spent the past decade digitising operations, moving workloads into the cloud, integrating payments and logistics systems, and stitching together regional expansion plans with software from dozens of external partners. Every API, contractor platform, cloud dashboard, and outsourced IT function expands the attack surface. And in many companies, especially those scaling quickly, vendor risk management has not kept up.
The Kaspersky data shows just how uneven the region has become. In APAC markets covered by the study, the share of organisations citing a lack of qualified IT security staff ranged from 34 per cent in Singapore to 57 per cent in Vietnam. Those figures suggest the issue is not limited to less mature digital economies. Even Singapore, Southeast Asia’s most developed technology and regulatory hub, is still wrestling with capacity constraints.
The difference is that in places such as Vietnam, the talent gap appears more acute, while in Singapore the problem is increasingly one of overload. Nearly half of respondents in Singapore, or 47 per cent, said they were juggling multiple cybersecurity priorities. In Vietnam, that figure stood at 48 per cent. India was even higher at 54 per cent.
That matters because supply chain security is rarely urgent until something breaks. Security teams tend to focus first on patching internal systems, responding to active incidents, dealing with audits and meeting compliance demands. The slower, messier work of assessing vendors, reviewing contractor access, updating third-party clauses and validating partners’ controls often gets pushed down the list. Attackers count on exactly that.
Weak governance and trust-based relationships create hidden vulnerabilities
This pattern has been visible in major breaches over the past few years. The SolarWinds compromise showed how malicious code inserted upstream can cascade across customer networks. The MOVEit attacks demonstrated how a single exploited third-party tool can expose multiple downstream victims.
Southeast Asian firms were not always named as primary targets in those cases, but the region’s businesses are deeply embedded in the same global software and services supply chains. They do not need to be the original target to suffer the fallout.
What makes the current moment especially risky for Southeast Asia is the region’s uneven cyber maturity. Large enterprises and regulated sectors such as banking and telecoms have generally improved their internal controls. But supply chain security depends on the weakest link across a broader ecosystem that includes software vendors, contractors, managed service providers, logistics partners, outsourced development teams and small suppliers.
The survey suggests many of those relationships are still governed too loosely. Across APAC markets, between 30 per cent and 61 per cent of respondents said their contracts did not include IT security obligations for contractors. Between 25 per cent and 38 per cent said non-IT staff did not fully understand supply chain and trusted relationship risks.
Those are not small operational gaps. They point to a deeper governance problem: cybersecurity remains too often confined to technical teams, while procurement, legal, finance and operations continue to sign or manage vendor relationships without strong, enforceable security baselines. In high-growth companies, especially across Southeast Asia’s startup and mid-market segments, that is a familiar weakness. Vendor onboarding is usually optimised for speed, cost and functionality — not for resilience.
Malaysia offers a useful illustration of the structural challenge. The country is trying to strengthen its cyber capability under the Malaysia Cyber Security Strategy 2025-2030, but the labour pipeline remains under pressure. The Ministry of Digital has projected that Malaysia will need 28,068 cybersecurity professionals by 2026, while earlier estimates placed the existing workforce at roughly 16,765. That gap helps explain why many organisations struggle to continuously monitor third-party exposures even when they know the risks are real.
Even basic cybersecurity practices remain inconsistent
The confidence problem is just as telling. Globally, 85 per cent of businesses said they need to improve protection against supply chain and trusted relationship risks. Only 15 per cent considered their current measures effective.
In APAC, confidence varied sharply. India, Indonesia and Singapore reported low confidence levels of 11 per cent, 14 per cent and 14 per cent respectively. Vietnam came in at 21 per cent, while China stood out at 34 per cent. That spread may reflect real differences in preparedness, but it may also reflect differences in perception. Either way, low confidence in Singapore and Indonesia is significant. These are markets with growing digital economies, dense vendor ecosystems and rising exposure to cloud and software dependencies.
One especially revealing finding concerns two-factor authentication. It was the most common protective measure identified in the survey, yet adoption remained patchy. Singapore stood out for the wrong reason, with an adoption rate of just 28 per cent. Other APAC markets reported rates above 35 per cent, but still below the global average.
For a region that often presents itself as digitally ambitious, weak uptake of such a basic safeguard is hard to ignore. Two-factor authentication is not a silver bullet, but low adoption suggests that even foundational controls are not being applied consistently across partner relationships. That is often where attackers find room to manoeuvre: not through sophisticated zero-day exploits alone, but through ordinary lapses in identity management, access control and vendor oversight.
Sergey Soldatov, Head of Security Operations Centre at Kaspersky, put the problem plainly: “When security teams are overstretched, understaffed and have to prioritise urgent tasks over long-term resilience priorities, organisations are left exposed to threats that can move silently through their provider ecosystem.”
A fast-growing digital economy built on fragile foundations
That assessment lines up with how many security incidents now unfold. Rather than battering down the front door, attackers compromise a supplier, abuse a trusted connection, hijack credentials or exploit neglected third-party software. The result is the same: businesses inherit risk from partners they depend on but do not fully control.
There is one encouraging signal in the survey, though it comes with a catch. Companies that had already experienced supply chain or trusted relationship attacks were more likely to adopt stronger security practices afterwards. Victims of supply chain incidents were more likely to request penetration test results from suppliers, while organisations hit by trusted relationship breaches more often checked for compliance with industry standards and their contractors’ own supply chain policies.
In other words, some firms are learning — but mostly after taking a hit.
That is a costly way to mature, particularly in Southeast Asia, where digital trust is becoming a competitive issue as much as a technical one. Financial services, healthcare, logistics, e-commerce and manufacturing all depend on interconnected systems and outsourced capabilities. A weak vendor risk posture no longer threatens only internal operations; it can disrupt customer experience, trigger regulatory scrutiny and damage expansion plans across borders.
For startups and growth-stage companies, the message is even sharper. Supply chain security is not just a big-enterprise compliance chore. The moment a company plugs into payment gateways, cloud infrastructure, SaaS tools, outsourced developers or regional fulfilment networks, it becomes part of someone else’s attack path.
The survey itself should be read with the usual caution attached to vendor-sponsored research. But its core finding is difficult to dismiss. Southeast Asia’s supply chain cyber problem is not simply about technology gaps. It is about a region moving fast on digital transformation while still underinvested in cyber talent, inconsistent in basic controls and too willing to trust third parties without demanding proof.
That combination is exactly what attackers prefer: fast growth, fragmented oversight and plenty of invisible dependencies.
Deep learning, a part of machine learning, simulates the processes of the human brain to solve complex tasks with neural networks. Though it drives everything from fraud detection to supply chain prediction, implementing deep learning in enterprise environments is a game altogether.
Unlike research or laboratory settings, companies must deal with operational constraints, regulatory concerns, and the demand for ROI. That’s where the real challenge begins.
Some of the challenges of deep learning are:
Data quality and quantity
Deep learning is fuelled by huge, high-quality data sets. Enterprise data, however, whether customer files and transaction logs or sensor data and email, is dirty, siloed, and in short supply. Thus, enterprise data rarely amounts to AI-ready.
Labelling data at scale is also slow and expensive. When you throw in data privacy laws (like GDPR or HIPAA), it’s easy to see why getting the best training data is a significant obstacle.
Model interpretability and transparency
Once again, deep learning models are black boxes that provide the answers without explaining how they arrive at them. This is not ideal for regulated industries like healthcare, finance, or manufacturing.
Executives and decision-makers will require authority and audit trails, compliance-ready output, and, as they will be cognisant of escalation in tech debt, standardisation, reliability, and usability. Explainable AI (XAI) is increasingly becoming popular, but the maturity of the XAI domain with deep learning models is slow.
Scalability and infrastructure needs
Deep learning models require higher-powered GPUs, more memory, and more compute time, along with ongoing deployment costs to stream. After deployment, maintaining low latency and responsiveness across enterprise-sized systems can be a costly engineering challenge.
Companies must consider what their cloud/on-prem/hybrid platform will do for these requirements and, importantly, whether they expect real-time inference for mission-critical situations.
Legacy system integration
Most companies still have many legacy systems, such as ERP suites, mainframes, and software developed decades ago. There are no plug-and-play deep learning libraries for these old systems.
It usually means significant customisation, middleware, or even re-architecting parts of the systems. Going from predictive insight to actions within legacy processes is time-consuming and expensive.
Cross-team collaboration and talent
Deploying deep learning isn’t hiring a data scientist. It’s a close interaction between domain experts, software engineers, data engineers, and DevOps teams.
Misalignment between these stakeholders is a typical reason for failed projects or models that aren’t created. Deep learning projects require good communication loops and joint responsibility between departments.
Model drift and continual learning
The only constant in life is change. A model trained on data collected twelve months ago will be unable to locate anomalies or patterns that are present today. In commercial applications like e-commerce, fraud detection or prevention, and transport planning, even the slightest drift pattern in the data can dramatically affect the business.
Businesses require systems that can track performance, recognise model drift, and launch retraining pipelines. Without lifecycle management, even the best models will fade quickly.
Best practices to overcome these challenges
To fully realise the benefits that deep learning can provide, companies need to have an approach based on technical maturity and target the industry.
Develop MLOps pipelines that deploy models, monitor, and retrain automatically – all are important to manage accuracy in fast-changing domains such as patient care or diagnostics.
In the design phase of any AI application, make data lineage and governance a priority for HIPAA compliance, auditability, and compliant use of AI, particularly for sensitive patient health records and medical images.
Include domain knowledge from clinicians and other medical experts in the model development process to increase the relevance and acceptance of AI models in healthcare.
Design scalable with hybrid capabilities using one pipeline for hospital/health systems networks, remote-monitoring systems/devices with AI hosted in the cloud.
Integrate explainability into the life cycle of an AI model, as stakeholders in the healthcare industry need to understand what the AI recommends and why.
Conclusion
Deep learning has the potential to be a great solution, but fulfilling that potential in the enterprise space requires much more than simply neural networks.
It requires clean data, interpretable models, scalable platforms, and a business strategy. Getting there isn’t easy, but the advantages of automating, customising, predicting, and uniquely differentiating your business are worth it.
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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.
As billions in investment pour into Southeast Asia’s data centre sector, US$6.3 billion to be specific, a rising tide of public scepticism over energy and land consumption has been raised at the Singapore-Johor-Riau (SIJORI) dialogue.
This, in turn, could create a critical public relations challenge – for digital infrastructure investors, operators and players, this could create a wider Public Relations problem on how they engage meaningfully with regulators.
Southeast Asia is aggressively building the engine rooms of the digital economy. With a staggering US$6.3 billion invested in the sector in 2024 alone, the race to power AI, cloud computing, and digital banking is undeniable. Hotspots like Johor in Malaysia are booming, absorbing demand from constrained neighbours, while Thailand and the Philippines are rolling out the red carpet for hyperscale operators. Malaysia, in particular, is taking a leading role. Its digital investments surged 125 per cent quarter on quarter in the second quarter of 2025, per the Malaysian Digital Economic Corporation.
But beneath the headline figures lies a potential disconnect. As government and industry leaders conceded at the recent SIJORI dialogue, immense strains on energy grids, water resources, and land availability – with a lack of viable solutions – could create friction, breaking momentum. This is also, in part, fuelling a perception gap where communities see only resource-intensive black boxes, not strategic assets. This disconnect is fast becoming a significant business risk, escalating into a looming public relations crisis for the industry.
According to industry analysts, this perception problem is largely self-inflicted. The historical model of development prioritised speed and discretion over public dialogue, creating a communications vacuum. This is a reactive situation that a specialised PR agency that works closely with media and other stakeholders are brought in to carefully manage, rather than a proactive strategy to build trust from the outset.
From technical problem to PR solution
The tough questions about sustainability are now driving policy. In Singapore, where data centres strain the power grid, the government’s post-moratorium criteria heavily favour green efficiency, a direct response to public and environmental pressure. For operators, navigating this complex landscape now requires more than just engineering excellence; it demands sophisticated communications, often leading them to seek specialist PR experts to help articulate their value proposition.
Forward-thinking developers argue that the solution to these challenges is a new, holistic development model, built around sustainability. We talk to technology leaders – from hybrid cooling systems to quantum computing innovators; water treatment providers; renewable energy providers – all focused and committed towards sustainable, responsible growth.
This strategy transforms an infrastructure project into a positive PR story. New development models, for instance, are integrating vast green spaces, contributing to local community funds, and sharing network capacity to boost rural connectivity. In the process these infrastructure operators and partners are creating jobs, and becoming a visible community partner.
The next wave demands a new narrative
The need for a better public relations strategy is being amplified by the arrival of next-generation technology. The immense power and stability required by AI and quantum computing render the old development model obsolete.
This future is already here: For instance, BDx Data Centres recently announced the launch of Singapore’s first commercial use of quantum computing within its facilities, with the potential to drive further advancements in technology innovation and sustainability. This highlights the region’s technological ambition, but also underscores the urgent need for a public mandate to support such powerful infrastructure.
Ultimately, the entire region requires a more cohesive communications strategy. The scale and cross-border nature of the industry suggest a growing need for a strategic PR across Southeast Asia that can tailor a compelling narrative to the unique cultural and political nuances of each market.
Data centre operators, governments and developers must urgently reframe the conversation. They must proactively explain not just what data centres are, but what they do for society. If the industry continues to treat community engagement as an afterthought, it will find its path to growth blocked not by a lack of capital, but by a lack of trust. The race for Southeast Asia’s digital future will be won not just by building infrastructure, but by building understanding.
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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.
Environmental, Social, and Governance (ESG) issues have moved from the periphery of corporate strategy to the centre of boardroom attention. Yet in Asia, many boards still treat ESG primarily as a reporting obligation or a compliance checkbox — not as a strategic lever for long-term resilience and value creation.
As independent and non-executive directors, we must recognise that boards need to advance their perspective. ESG has moved beyond being a mere obligation; it now represents a driver of competitive advantage, a safeguard against risk, and a foundation for stakeholder confidence. Boards that embed ESG into governance and strategy are positioned to surpass their peers in sustainable growth, reputation, and long-term resilience.
Why ESG is now a board-level imperative
Several forces are converging to make ESG a core board responsibility:
Regulatory pressure: Governments across Asia are introducing ESG disclosure requirements, carbon reduction mandates, and reporting standards aligned with TCFD (Task Force on Climate-related Financial Disclosures).
Investor expectations: Institutional investors increasingly link capital allocation to ESG performance. Firms with poor ESG records face higher cost of capital.
Stakeholder scrutiny: Customers, employees, and communities are demanding ethical practices, sustainability, and transparency.
Operational risk: Climate-related events, supply chain disruptions, and labour issues directly impact financial performance.
Boards can no longer delegate ESG oversight to management; it has become a fiduciary responsibility. Ignoring ESG is a governance failure.
The danger of treating ESG as “cosmetic compliance”
Too often, boards focus on what is easy to measure: carbon reporting, policy statements, and social initiatives. While necessary, these activities do not create meaningful value unless linked to strategy.
The pitfalls of cosmetic ESG include:
Misalignment between ESG reporting and business priorities
Tokenistic initiatives that fail to influence culture or operations
Reputation risk if stakeholders perceive ESG as performative
Missed opportunities to embed ESG into product innovation, market positioning, and long-term planning
Asian boards must recognise that ESG is not a moral add-on – it is a strategic lever that drives growth and reduces risk.
To embed ESG into governance effectively, boards should:
Conduct ESG capability assessments: Identify gaps in expertise, particularly around climate science, sustainable finance, and social impact.
Upskill directors and management: Offer workshops, briefings, and scenario planning exercises.
Integrate ESG into strategy sessions: ESG should be part of the discussion in every strategic review, not a standalone agenda item.
Link ESG metrics to executive accountability: Align compensation with measurable ESG outcomes.
Use ESG as a risk lens: Consider climate, social, and governance risks in capital allocation, M&A, and operational planning.
The future board: ESG-embedded and forward-looking
By 2030, the most successful boards in Asia will not be the ones that simply report ESG metrics. They will be the boards that:
Anticipate regulatory and societal shifts
Integrate ESG into strategy, risk, and culture
Drive innovation while reducing negative environmental and social impacts
Communicate openly with investors, employees, and communities
For aspiring independent directors, understanding ESG deeply is no longer optional. It is a core competency, a strategic differentiator, and a sign of governance maturity.
Boards that embrace ESG as strategic value creation, not just disclosure, will position their organisations for resilience, trust, and long-term success.
Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.
The post-pandemic era didn’t kill office culture. In fact, it rewrote what was once known as the “standard working culture”.The world is now introduced to a “remote-first” office culture.
