The enterprise AI story has moved well beyond chatbots and novelty pilots. In large companies, AI agents are now being connected to finance systems, customer databases, internal knowledge bases, payment rails, cloud consoles and software development pipelines. That shift is why “The AI Agent Governance Gap” report by US-based API management company Gravitee lands with the force of a fire alarm, not a polite policy memo.

The report cites findings from Cybersecurity Insiders showing that 71 per cent of large enterprises have already deployed AI agents with direct access to core business systems, yet only 16 per cent effectively govern that access. In other words, the corporate world has handed the keys to the machine before installing the locks.

Also Read: AI agents could become the new OTAs: What it means for Agoda and the future of travel

That framing matters enormously in Southeast Asia, where enterprises are modernising fast but often unevenly. The region’s banks, telcos, insurers, logistics giants, government-linked companies and fast-scaling tech firms are running a dense mix of legacy systems, cloud services, outsourced IT operations, and regional data flows. Add AI agents into that patchwork, and the attack surface does not merely expand. It becomes harder to even describe.

The problem is not adoption. It is architecture

Gravitee’s core argument is that the governance gap is architectural, not procedural. AI agents do not behave like human employees, and they do not fit neatly into identity and access models designed for human beings signing in from laptops. Agents operate at machine speed, can chain actions across multiple systems, inherit permissions quietly and create activity logs that are difficult for security teams to interpret in real time.

The numbers in the report are stark. It says 92 per cent of organisations lack full visibility into their AI identities, while 95 per cent doubt they could detect or contain misuse if it occurred. Nearly half of surveyed CISOs (47 per cent) say they have already seen AI agents exhibit unintended or unauthorised behaviour. That is not a theoretical risk. That is production risk wearing a name badge.

For Southeast Asia, the implications are especially sharp because many businesses operate across multiple jurisdictions with different compliance expectations. A Singapore-headquartered company may have engineering in Vietnam, a customer service operation in the Philippines, merchant relationships in Indonesia and cloud workloads spread across several regions. One poorly scoped AI agent plugged into a CRM, data warehouse, and payment workflow can turn into a compliance and security headache across borders in a matter of seconds.

Regional digitisation has created fertile ground for agent sprawl

There is a reason the region is vulnerable to this problem. Southeast Asia’s digital economy has been built on speed, interoperability and relentless integration. Super apps connect payments, food delivery, transport and lending. E-commerce platforms rely on real-time logistics and fraud tools. Banks are exposing more services through APIs.

Manufacturers are digitising procurement, forecasting and maintenance. Every one of those changes creates more structured workflows for an AI agent to enter.

And once agents arrive, they rarely stay in one lane. A sales operations agent may begin by summarising pipeline data, then request permission to update records, trigger marketing actions, and request access to billing information to answer customer queries. Over time, what began as a productivity tool becomes a semi-autonomous operator within the business.

This is where the report’s warning becomes uncomfortable. Most organisations still govern access as if the main risk is a human clicking the wrong button. But the bigger danger increasingly comes from a non-human identity making a thousand correct calls, in the wrong sequence, at the wrong scale, with the wrong level of access.

Also Read: AI agents are outpacing security: The crisis hiding in plain sight

That problem is not abstract in Southeast Asia. Regional companies often rely on managed service providers, third-party integrators and offshore development teams to stitch systems together. Credentials are shared. Service accounts linger. Documentation ages badly. In that environment, AI agents do not arrive in a pristine architecture. They arrive in a house whose wiring is already creative.

Why visibility is collapsing

The report argues that the first casualty of agentic AI is visibility. Traditional dashboards can tell security teams that an API was called or a database was queried. They are far less effective at expressing why an agent took a particular action, what chain of prompts or tool calls produced it, and whether the access was proportionate to the task.

That matters because AI agents do not simply authenticate once and sit still. They discover tools, call APIs, retrieve documents, invoke external models and sometimes delegate subtasks to other services. Each of those steps creates a miniature trust decision. According to the report, most enterprises are not instrumented to observe that flow in any coherent way.

In Southeast Asia, this visibility gap intersects with another reality: many organisations are using AI to compensate for talent shortages. Teams want automation because they are under pressure to do more with fewer specialists. That business case is real. But it also increases the temptation to grant broad permissions quickly, especially when the alternative is slower manual work.

The result is a pattern security teams know all too well: access first, governance later. Except that later, when the workflow is live, the vendor is embedded,, and the business unit is already dependent on the outcome.

The hidden boardroom risk

There is also a strategic issue here that founders and boards should not ignore. Many executives still view AI risk through the lens of model accuracy, bias or data leakage. Those issues matter, but agent governance is different. It is an operational power risk. It is the risk that software can now do things in enterprise systems, not merely analyse or recommend.

That shifts the conversation from ethics decks to control planes. If an agent can touch ERP, procurement, payroll, code repositories or customer records, then the real question is no longer whether the model is clever. The real question is whether the organisation knows what the agent is allowed to do, when, under what policy and with what audit trail.

For Southeast Asian enterprises racing to prove they are AI-ready, this is where the story gets serious. The most immediate threat may not be a headline-grabbing model failure. It may be a quiet overreach: an agent with too much access, too little monitoring and too many connected systems.

The coming divide

The Gravitee report points towards a coming divide in enterprise AI. On one side will be organisations that treat agents as first-class operational actors requiring identity, authorisation, monitoring and lifecycle management. On the other hand, there arehand, there those who continue to treat agents as convenient add-ons to existing software.
The first group will move more slowly at the beginning and much faster later. The second group will look agile until something breaks.

Also Read: Agentic AI is powerful, but power isn’t product-market fit

In Southeast Asia, where growth markets often reward speed and execution, that distinction could become a competitive fault line. The winners will not simply be the companies with the most AI agents. They will be the ones who know exactly what those agents are doing, what they can touch and how quickly their access can be changed or revoked.

The age of AI agents in the enterprise has already begun. The age of controlling them has barely started. That, as the report makes clear, is the real story.

The post AI agents are already inside your systems, but who’s controlling them? appeared first on e27.

A rat at the end of the rat race is still a rat.

It is an intentionally uncomfortable line, but it captures something important about how we often talk about progress in the digital economy. Too often, the goal is framed as helping more women and marginalised communities enter the system, compete harder, and succeed within structures they did not shape. But participation alone is not equity. If the rules, incentives, and power dynamics remain unequal, then bringing more people into the race does not create fairness. It simply expands the pool of people expected to navigate the same system. That is why equity matters. Not because it helps more people run faster, but because it asks whether the race itself should be redesigned.

This matters especially in Southeast Asia, where the digital economy is growing quickly but not evenly. New platforms, AI tools, financial services, and digital business models are creating real opportunities across the region. But access, mobility, and outcomes are still shaped by gender, income, geography, language, education, and social norms. In this context, equity cannot be treated as a side conversation. It has to be built into how innovation is designed, funded, and scaled.

For a long time, conversations about women in tech have focused on visibility. How many women are in the room? How many are founding companies, writing code, raising capital, or taking on leadership roles? These remain important questions, but they are no longer enough. Representation matters, but it does not tell us whether the systems people are entering are fair, inclusive, or empowering by design.

Technology does not emerge in a vacuum. Every platform, funding process, AI model, and workplace culture reflects the assumptions of the people and institutions behind it. If those assumptions go unexamined, inequality does not disappear in a digital environment. It becomes embedded into it.

Also Read: Ethical implications of using AI in hiring

At a systems level, this becomes visible in four areas.

The first is access. Participation in the digital economy is still unevenly distributed. Access is not only about being connected to the internet or owning a device. It is also about whether people have the tools, literacy, trust, safety, and confidence to engage meaningfully. Many individuals may be technically online but still excluded from the real benefits of the digital economy because products are unaffordable, systems are difficult to navigate, or pathways into jobs, markets, and networks remain out of reach.

The second is capital allocation. Capital does more than fund innovation. It determines which ideas are taken seriously, which founders are seen as credible, and which markets are considered worth building for. These decisions are often shaped by pattern recognition and inherited assumptions about what a promising founder or business should look like. As a result, capital can reinforce familiarity rather than recognise overlooked value. This does not just create unequal funding outcomes. It also shapes the direction of innovation itself.

The third is product design. Even when people can access digital systems and businesses can secure funding, exclusion can still be built into the product itself. Design choices reflect whose experiences are considered normal and whose are treated as exceptions. This can be seen in AI systems trained on narrow datasets, financial tools that overlook informal work realities, or digital services that assume levels of language fluency or digital confidence that many users do not share. When products are not designed with a wider range of lived realities in mind, they do not simply fail to serve some users well. They reproduce exclusion at scale.

The fourth is workplace culture. An equitable digital economy cannot be built by organisations that remain unequal on the inside. Workplace culture shapes who gets hired, who gets heard, who is trusted with responsibility, and who is able to progress into leadership. Too often, inclusion is measured by representation at the entry level while deeper questions of sponsorship, decision-making power, and belonging remain unresolved. If people from underrepresented backgrounds are brought into the system but not supported to shape it, the broader structure does not meaningfully change.

Taken together, these are not separate issues. They are different layers of the same system. A more equitable digital economy will not come from visibility alone. It will come from redesigning the structures that determine participation, validation, experience, and power.

Also Read: A new era of automation: Establishing best practices for intelligent automation and generative AI

Even the language we use deserves scrutiny. There is a quiet contradiction in the word inclusion. It sounds generous, but it also reveals power. To include is to decide who was outside, who belongs, and on what terms. That is why inclusion, on its own, can be insufficient. The deeper goal is not to be admitted into systems built by others, but to reshape the system so belonging is not conditional.

There is a similar tension in the way we celebrate the extraordinary. We usually mean the exceptional, the rare, the remarkable. But taken apart, extraordinary also returns us to the ordinary, the everyday person whose life and labour hold society together. Equity matters because a fair system cannot be designed only for the exceptional few who manage to break through. It must also work for the ordinary person, who should not need to be extraordinary just to be seen, supported, and given a fair chance.

That means asking harder questions. Who gets included in pilot opportunities and industry networks? Who is represented in the datasets behind the tools we build? Who gets trusted with strategic roles or technical leadership? Who finds the application process intuitive, and who finds it alienating? Who remains invisible in the innovation ecosystem, not because they lack talent, but because the system was not designed to recognise them clearly?

These are not abstract concerns. They affect the quality of innovation itself. An ecosystem that excludes is not just unfair. It is less capable. It misses markets, overlooks pain points, narrows the range of solutions being built, and concentrates opportunity in ways that weaken resilience.

For those of us working in innovation ecosystems, this creates a shared responsibility. We are not only supporting what gets built. We are also shaping the conditions under which innovation happens. That includes who gets access to capital, platforms, partnerships, distribution, and legitimacy.

The goal, then, is not simply to help more people enter existing systems. It is to build better systems in the first place. Because the real measure of progress is not how many people we let into the race, but whether we are willing to redesign it.

Otherwise, we risk mistaking movement for change. A rat at the end of the rat race is still a rat. Equity matters because the ambition should never have been to help more people survive the same race. It should be to build a digital economy where dignity, opportunity, and leadership are not conditional on fitting into a system that was never designed for everyone to begin with.

—

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

The post Beyond inclusion: Why equity matters in the digital economy appeared first on e27.

Indonesia’s FMCG e-commerce sector has posted its strongest quarter on record, with total sales exceeding IDR40 trillion (US$2.3 billion) in the first three months of 2026 — a milestone that underscores the country’s accelerating shift to online retail.

Data released by Compas.co.id, Indonesia’s e-commerce intelligence platform, shows that FMCG e-commerce sales from January through mid-March 2026 surpassed the previous record of IDR39.6 trillion set in Q4 2025. The figures span four major platforms — Shopee, ShopTokopedia, Lazada, and Blibli — and span five product categories: Beauty, Food and Beverage, Healthcare, Homecare, and Mother and Baby.

Beauty remained the largest FMCG e-commerce category, generating IDR18.6 trillion — a 33 per cent increase year-on-year. Yet it was Food and Beverage that delivered the quarter’s most striking performance, surging 88 per cent year-on-year to IDR10.3 trillion. The Ramadan and Eid al-Fitr season, which fell in Q1 this year, is widely credited for catalysing a wave of pantry loading, gifting, and mass consumption.

Homecare nearly doubled, rising 96 per cent year-on-year to IDR2 trillion, driven by demand for tissues, insecticides, and cleaning products. Healthcare grew 40 per cent to IDR6 trillion, while Mother and Baby held steady at IDR3.2 trillion, up 20 per cent year-on-year, with relatively flat transaction volume, pointing to strong repeat-buyer behaviour rather than new customer acquisition.

One of the report’s most significant findings is that sales growth has come alongside a contraction in the number of active brands across most categories. In Beauty, active brands declined one per cent even as the category posted double-digit growth. Food and Beverage saw active brands fall eight per cent, yet individual brands posted extraordinary gains: Bimoli grew 907 per cent, Sedaap 688 per cent, and Indocafe 497 per cent. In Healthcare, Metoo surged 768 per cent and Tolak Angin 268 per cent, even as the category’s active brand count dropped four per cent.

Also Read: Capital comes roaring back: Inside SEA’s March funding boom

Homecare was the notable exception. It is the only category where both brand count and sales expanded simultaneously, suggesting the space remains comparatively open to new entrants.

The pattern points to a consolidating market in which growth is increasingly concentrated among brands with disciplined promotional strategies, strong platform presence, and well-calibrated product formats.

Platform polarisation reshapes FMCG strategy

The FMCG e-commerce landscape is also splitting sharply along platform lines. ShopTokopedia recorded the strongest growth across nearly all categories: Beauty up 75 per cent, Food and Beverage up 127 per cent, Healthcare up 79 per cent, and Mother and Baby up 39 per cent. Shopee maintained its position as the highest-volume platform, with Homecare up 118 per cent and Food and Beverage up 83 per cent.

By contrast, Lazada declined between 49 per cent and 66 per cent across categories, and Blibli posted negative results across most segments. For FMCG brands, the implication is direct: a strategy that does not differentiate between Shopee and ShopTokopedia risks forgoing meaningful growth.

The two platforms also demand distinct approaches to discounting. On Shopee, more than 90 per cent of sales occur at discount levels below 20 per cent, reflecting strong organic demand. ShopTokopedia, however, responds more readily to moderate and heavy promotional activity. Bundle formats perform strongly on ShopTokopedia across Food and Beverage, Mother and Baby, and Homecare, while bulk carton formats are better suited to Blibli.

Outlook: Growth expected to hold through Q2

Compas projects FMCG e-commerce sales to reach IDR46.7 trillion in Q2 2026, lower than the Ramadan-boosted Q1 figure, but above every quarter recorded in 2025. The moderation reflects a natural reset from an exceptionally strong seasonal base rather than any structural weakening of demand.

Beauty, Food and Beverage, and ShopTokopedia are forecast to remain the three central drivers of Indonesia’s FMCG e-commerce market for the remainder of the year, anchoring what now appears to be a sustained new phase of growth for the sector.

—

Image Credit: Shutter Speed on Unsplash

The post Indonesia’s FMCG e-commerce market shatters records as beauty, food sales surge appeared first on e27.

Southeast Asia’s technology sector witnessed a remarkable surge in funding activity in March 2026, according to the latest data compiled by Tracxn.

Total disclosed funding hit an impressive US$378 million across 23 rounds, signalling renewed investor confidence and dynamic growth in the region’s tech startup ecosystem. This figure is notable not just for its size but for the sharp increase it represents — a staggering 322.57 per cent jump from February 2026, and a 37.19 per cent rise compared to March 2025.

Also Read: Southeast Asia’s VC winter? Funding dips sharply in February

This sharp uptick is indicative of broader patterns unfolding in the Southeast Asian tech landscape, including sector consolidation, a spate of high-profile deals, and an influx of venture capital from both local and international investors.

Below is an analysis of what drove this surge, the key players involved, and what it means for the future of tech innovation in this fast-evolving region.

March’s explosive Growth: Context and comparisons

The tech funding ecosystem in Southeast Asia has generally been on an upward trajectory, but the scale of growth witnessed in March 2026 is exceptional. To put it in perspective, the US$378 million raised in March dwarfs previous monthly totals, marking a more than threefold increase from the US$89 million raised in February 2026.

Moreover, compared with March 2025’s tally of ~US$275 million, the current figures still show a healthy climb, underscoring not only a rapid recovery but also sustained momentum in the regional tech startup scene. This suggests that investors are increasingly confident in Southeast Asia’s tech market, despite global economic headwinds and evolving geopolitical challenges.

Driving the capital inflow: Sector highlights and major deals

Several startups and sectors stood out in March, dominating both deal volume and value. Notably, Carsome, the automotive e-commerce platform, secured two rounds of funding this month, signalling ongoing investor interest in the automotive tech space, a sector increasingly shaped by digitisation and digital transaction platforms.

Amity Solutions, a provider of digital engagement and collaboration platforms, also made headlines by closing a round, underscoring the steady demand for B2B SaaS solutions amid enterprises’ digital transformation efforts.

Additionally, startups like myFirst and dtcpay each attracted two rounds, while Aonic completed one round, all contributing to the diversity and depth of funded companies.

A Spotlight on investors: Who’s backing Southeast Asia?

The surge was made possible not just by vibrant startups but by a cadre of highly active venture capital (VC) firms operating in Southeast Asia. Among the most notable are Asia Partners, Kairous Capital, EDBI, and Vertex Ventures.

Asia Partners is known for backing disruptive innovations across sectors, while Kairous Capital’s activity underlines growing interest from family offices and independent wealth groups looking to capitalise on regional tech growth.

Also Read: Mozark raises US$40M to test how apps really behave in the wild

EDBI, as a government-linked investor, continues to play a key role in nurturing startups that promise strategic national and regional impact. Meanwhile, Vertex Ventures (part of the Temasek Holdings family) is widely recognised for its aggressive venture investments, shaping Southeast Asia’s tech landscape.

What’s behind the numbers: Market maturity and investor confidence

A 322.57 per cent increase in funding from February to March is not merely a statistical anomaly but a signifier of broader systemic shifts. Analysts note that such spikes often follow periods of market consolidation, regulatory clarity, or the arrival of key funding cycles aligned to quarterly or annual investment timelines.

Furthermore, improvements in startup maturity, with companies advancing from seed and Series A stages to later-stage funding, unlock larger funding tickets as risk profiles improve for investors. Southeast Asia’s growing base of scaleups means more capital-intensive rounds can be successfully closed, driving up monthly totals.

The marked increase over March 2025’s numbers (37.19 per cent higher) reflects a deepening conviction in the region’s economic and technological prospects. Southeast Asia, home to over 700 million people, remains one of the fastest digital adopters globally, with mobile penetration, e-commerce growth, fintech innovation, and cloud adoption all contributing to a fertile environment for venture capital.

Challenges and outlook: Navigating uncertain waters

Despite the upbeat figures, the Southeast Asian tech sector is not without challenges. Regulatory uncertainties, particularly around data privacy and digital payments, as well as geopolitical tensions in the Indo-Pacific region, remain potential headwinds.

Moreover, the heightened pace of investment raises questions about valuation multiples and the sustainability of rapid funding growth. The sector is also experiencing growing pains typical of a maturing ecosystem, including talent shortages and operational scaling challenges.

Yet, industry insiders argue that these are natural growing pains. “The increase in funding is reflective of Southeast Asia’s emerging stature as a global innovation hub,” says a regional venture capital expert. “While caution is necessary, the long-term fundamentals remain robust.”

What this means for startups and entrepreneurs

For founders and entrepreneurs in Southeast Asia, March’s funding surge signals intensified competition but also ample opportunity. With more capital available, startups can accelerate product development, customer acquisition, and regional expansion.

However, it also means that startups must demonstrate clear value propositions and scaling potential to differentiate themselves in an increasingly crowded space. Strategic partnerships with active VCs can provide not only capital but mentorship, market insights, and access to networks needed to thrive.

Conclusion: A region poised for continued tech evolution

In summary, March 2026’s tech funding snapshot delivers a powerful message: Southeast Asia’s technology sector is entering a new phase of growth and investor engagement. The triple-digit monthly funding increase and solid year-on-year gains highlight a robust and improving funding environment.

Also Read: Alibaba backs Singapore fintech MetaComp’s US$35M bet on Web2.5 finance

With active participation from leading VCs and a healthy pipeline of promising startups, the region appears well-positioned to maintain its momentum as a prime destination for tech innovation and venture capital investment. As the market further matures, observers should expect more strategic, later-stage deals alongside early-stage ventures, signalling the rise of sustainable tech champions from Southeast Asia on the global stage.

This evolution warrants close watching, as the interplay of capital, innovation, and regional dynamics will shape not just Southeast Asia’s digital future but, potentially, the global tech landscape in the years ahead.

The post Capital comes roaring back: Inside SEA’s March funding boom appeared first on e27.

In our increasingly interconnected world, geography poses fewer limitations on ingenuity. With pressing concerns surrounding climate change and the imperative for sustainable energy solutions, international collaboration is essential to achieving meaningful and enduring progress.

In a single Sierra Leonean village, a solar grid lighting homes and schools shows what global collaboration can achieve at a local level — real progress powered by shared vision and effort.

From the strides made by energy companies in Southeast Asia, focused on transforming transportation and technology, to youth-led initiatives in Africa combating energy scarcity, a unified vision is taking shape. It’s a vision fuelled by shared objectives, innovative technologies, and the collective efforts of individuals.

In Sierra Leone, where I was involved in establishing Green Sphere Power Company, we’re dedicated to developing solar mini-grids. These grids provide dependable and clean electricity to communities that have often been marginalised, contributing significantly to the global transition towards renewable energy while simultaneously creating opportunities for local education, entrepreneurial ventures, and empowerment.

In one such community, students can now study after dark, and small business owners have extended their operating hours — simple yet powerful changes that show how energy access can transform daily life.

Also Read: Unlocking Asia’s payments potential: The case for unifying fragmented policies

At the same time, across Southeast Asia, innovation hubs and forward-looking communities are bringing together entrepreneurs, investors, and leaders, driving conversations around clean energy, mobility, and technology. These initiatives reflect a shared commitment to build sustainable systems that serve people first, a goal that deeply resonates with our work in West Africa.

Observing these advancements, I recognise a significant opportunity for Africa and Asia to cooperate. Through the exchange of expertise, the initiation of joint projects, and the establishment of partnerships for young people, we can accelerate our collective mission of creating a sustainable and equitable future for all.

Imagine solar startups in Sierra Leone learning from green tech solutions in Singapore, or young engineers from Nairobi collaborating with AI innovators in Bangkok. Such partnerships could redefine what global cooperation looks like in the climate era.

It is now more crucial than ever that we connect – not just through technological means, but through shared aspirations. The challenges we encounter are global in scope, and so too must be the solutions.

Let’s persist in linking regions, ideas, and innovations to make a substantial difference that transcends geographical boundaries. The sun that rises over Africa also lights Asia, and if we choose to share that light, we can illuminate a sustainable future for all.

—

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.

Enjoyed this read? Don’t miss out on the next insight. Join our WhatsApp channel for real-time drops.

Image courtesy: Canva

The post Building a sustainable future, from Sierra Leone to Southeast Asia appeared first on e27.

Companies are spending millions on corporate mental health programmes, yet employee burnout remains at an all-time high. Why? 

Because most strategies fail to address the real problem. Despite increased corporate investment, many workplace mental health initiatives struggle with low engagement, ineffective one-size-fits-all approaches, and a lack of measurable impact. Singapore, for example, has one of the lowest employee engagement rates in the region — just 59 per cent, according to Aon. 

It’s time for a paradigm shift. Traditional wellness programmes tend to intervene only after employees begin struggling — by which point, it may already be too late. Instead, the future lies in combining technology and human care to create mental health strategies that are proactive, personalised, and clinically effective.

Artificial intelligence (AI) isn’t a replacement for professional care, but when used responsibly, it can be a powerful enabler. It can help detect early signs of distress through anonymised sentiment analysis and behavioural patterns, allowing organisations to intervene earlier and more effectively.

Critically, AI-powered tools can also personalise how support is delivered. By analysing real user behaviour and engagement patterns, these platforms can recommend appropriate next steps — whether that’s a therapy session, a mindfulness exercise, or simply a nudge to check in with a licensed professional. This level of personalisation helps lower barriers to access and encourages more consistent engagement.

This is especially important in Singapore’s workplace culture, where mental health stigma remains prevalent. In fact, only 36 per cent of local employers say they’re comfortable talking about mental health at work, according to a survey by SHRM and Oracle. Nudging employees toward care in a way that feels non-intrusive, private, and data-driven can play a vital role in bridging that gap.

AI also plays a valuable role in the feedback loop. It helps HR teams understand evolving employee needs and sentiment in real time, making it easier to track the effectiveness of mental health initiatives and adjust them accordingly. But as with all data-driven tools, privacy and confidentiality must remain non-negotiable. Protecting employee trust means ensuring that all data is anonymised, secure, and handled with clinical sensitivity.

Also Read: A new hip, a new era: Meticuly, a Thai startup, is rewriting the rules of surgery with on-site 3D printing

Beyond personalisation and engagement, platforms that adopt an element of AI also lower the barrier to adoption for businesses. Many companies hesitate to scale mental health programmes due to concerns around cost, resource burden, or cultural resistance. AI-enhanced platforms help overcome these hurdles by offering cost-efficient, scalable tools that integrate seamlessly into existing HR systems — allowing leaders to implement support more quickly and demonstrate ROI through measurable outcomes.

Importantly, AI is not the solution in itself — it’s part of a broader, human-led system of care. Technology can support, scale, and sharpen workplace mental health strategies, but it must always work in tandem with licensed professionals and ethical safeguards.

Companies that integrate both data and empathy will be better positioned to support their people — not just when they’re in crisis, but before they get there. It’s no longer about ticking boxes. It’s about building a workplace culture where mental health is prioritised as a shared responsibility.

The tools are here. The data is clear. Now is the time for business leaders to step up, embrace thoughtful innovation, and create workplaces where employees truly feel seen, supported, and safe.

—

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.

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

We’re building the most useful WA community for founders and enablers. Join here and be part of it.

Image credit: Canva Pro

The post Why corporate mental health fails and how AI can fix it appeared first on e27.

Cooley LLP Partner David He

Southeast Asia’s startup ecosystem has spent the past few years on a rollercoaster; soaring valuations, a brutal funding winter, and now, what some are calling a cautious recovery.

But according to David He, Partner at Silicon Valley law firm Cooley LLP, the real story isn’t about recovery at all. It’s about reset.

“We’re closer to 2019 than we are to 2021,” He tells e27. “And 2019 was a much healthier venture environment.”

Also Read: Funding winter is the best time to build a startup

Drawing on over a decade advising startups and investors and hundreds of venture deals across Asia, He offers a ground-level view of how capital, expectations, and behaviour have fundamentally changed.

From frenzy to fundamentals

To understand today’s market, He breaks the past few years into three phases.

Unprecedented capital inflows defined the boom years of 2021 and 2022. Global crossover funds, which traditionally focused on public markets, entered private markets aggressively, deploying capital at speed and scale.

“It was almost a trader mentality,” He says. “Investors were issuing US$50 million term sheets rapidly, doing limited diligence, and moving on to the next deal.”

For founders, it created a distorted incentive structure. Fundraising became the focus, often at the expense of building sustainable businesses.

That changed abruptly in 2023 and 2024.

As interest rates rose and capital tightened, the ecosystem entered a “funding winter.” Valuations fell, deal terms became more stringent, and many startups were forced into survival mode. “It was a wake-up call,” He says. “Founders had to shift from raising money to actually making money.”

Why the downturn may have been necessary

While headline figures still show reduced deal volume and funding levels, He argues that today’s environment is fundamentally healthier.

Investors are no longer competing blindly for deals. Instead, they are:

• Conducting deeper due diligence
• Deploying capital more selectively
• Supporting portfolio companies more actively

At the same time, founders are more disciplined and are now focused on revenue, cost control, and sustainable growth.

“Everybody is being much more deliberate now,” He says. “And that’s what sets companies up for long-term success.”

Capital isn’t gone; it’s evolving

The perception that funding has dried up is only partially true. What has changed is the nature of capital.

Startups today are increasingly exploring alternatives to traditional venture capital, including:

Also Read: Southeast Asia’s VC winter? Funding dips sharply in February

• Venture debt, which allows companies to raise capital without dilution
• Private equity and strategic investors, which offer different structures and expectations
• Corporate venture capital, which brings both funding and commercial partnerships

“If venture capital starts to look like private equity in terms of control, founders will just go directly to private equity,” He notes.

This shift reflects a broader evolution: capital is still available—but it is more disciplined, and founders have more options.

AI: Capital magnet or distortion?

One of the most significant trends reshaping capital flows is the rise of AI.
Globally, AI startups are absorbing a disproportionate share of investment.

But in Southeast Asia, the picture is more nuanced. The region is largely building application-layer AI, tools and platforms that sit on top of foundational models developed elsewhere.

“It’s very hard to compete with the US and China on core AI infrastructure,” He explains. “Southeast Asia is more AI-adjacent.”

While this means fewer “50x” valuation opportunities, it also creates practical advantages. AI is helping startups:

• Reduce operational costs
• Accelerate product development
• Improve efficiency without constant fundraising

“If the AI bubble corrects, capital may flow back into more traditional sectors,” He adds.

The trust deficit: Lessons from eFishery

Recent scandals, including the collapse of Indonesian agritech startup eFishery, have cast a shadow over the ecosystem. (Cooley acted as legal counsel for eFishery during its Series D round announced in July 2023)

He describes the eFishery case as relatively straightforward in hindsight.
“There were two sets of accounts: management-reported and audited, and investors relied on the wrong one.”

But the broader impact is more significant.

For international investors unfamiliar with the region, such incidents reinforce concerns about governance and transparency. “It pours cold water over the ecosystem,” he says. “And that’s unfortunate, because there are many strong, credible founders here.”

Unlike more mature markets like the US or India, Southeast Asia still lacks a deep pool of high-profile success stories to offset such failures.

What investors are really looking for now

In today’s environment, investors are scrutinising startups more closely than ever, especially on fundamentals.

From a legal perspective, He highlights four critical areas:

1. Corporate structure: Ensuring proper ownership across jurisdictions
2. Intellectual property: Clear and defensible ownership of technology
3. Regulatory compliance: Particularly around data, privacy, and financial rules
4. Commercial contracts: Avoiding unfavourable terms with large enterprise customers

There is also growing scepticism around regional expansion narratives.
“Just because something works in Vietnam doesn’t mean it will work in Indonesia or the Philippines,” He says.

Also Read: When debt replaces equity: How SEA startups mask a funding winter

A shifting sector landscape

Capital allocation is also becoming more selective.
Investors are increasingly favouring B2B SaaS, deeptech, and AI and infrastructure plays. Consumer-facing businesses, once dominant in Southeast Asia, are facing more scrutiny, though they remain viable in large markets like Indonesia.

“The companies that succeed are the ones with steady growth, strong execution, and clear unit economics,” He says.

Exit reality: No quick wins

While some optimism has returned around IPOs and SPACs, He remains cautious. “SPACs are still a secondary option. If you can IPO, you IPO.”

In reality, the most likely exit paths for Southeast Asian startups are:

• Strategic acquisitions
• Private equity buyouts
• Secondary sales to new investors

A wave of exits is expected in the coming years, driven by fund lifecycle pressures. However, not all will deliver strong returns. “Many funds are reaching the end of their lifecycle,” He says. “They may accept lower returns just to exit.”

A more mature ecosystem emerges

For He, the current moment represents not a downturn, but a recalibration.
The excesses of the boom years have been corrected. The harshness of the funding winter has passed. What remains is a more grounded, disciplined ecosystem.

• Founders are building real businesses
• Investors are making deliberate decisions
• Capital is being deployed more responsibly

“This is what a sustainable venture ecosystem should look like,” He says.

The question now is whether Southeast Asia can translate this discipline into consistent success stories, and finally establish itself as a global startup powerhouse.

The post AI hype, hard lessons: Where SEA’s startup capital is really going appeared first on e27.

For decades, we’ve treated education as the ultimate equaliser.

Study hard. Get certified. Climb the ladder.

That formula powered the industrial economy and then the early knowledge economy. Degrees signalled competence. Credentials signalled readiness. Access to elite institutions signalled advantage.

Then GenAI arrived.

And quietly, without protest, it collapsed the scarcity model that education was built upon.

Today, anyone with a prompt can access legal reasoning, financial modelling, medical summaries, code scaffolding, strategic frameworks, and global research. The gates are no longer guarded.

This raises a difficult question: If AI has access to almost all codified knowledge — and most people now do too — what exactly is the education system optimising for?

The original purpose of education

Modern education systems were designed for three primary objectives:

• Standardisation of knowledge
• Industrial workforce readiness
• Credential-based sorting

It rewarded:

• Memorisation
• Compliance
• Accuracy within structured evaluation
• Linear problem-solving

In the industrial era, this worked. Fact recall was valuable. Access to information was limited. Standardisation ensured predictable output.

But in the GenAI era, memorisation is automated. Information retrieval is instant.

Structured reasoning can be generated in seconds. If the value of knowledge used to lie in having it, today the value lies in knowing what to do with it.

And this distinction exposes the cracks in the current system.

When AI has all the answers

GenAI does not experience impostor syndrome. It doesn’t doubt its competence. It doesn’t gatekeep information. It doesn’t fear being “found out.”

It simply accesses and synthesises.

Ironically, humans — who built the education system — are now the ones experiencing inadequacy. Because we were trained in scarcity.

Scarcity of:

• Access
• Tools
• Elite networks
• Research
• Mentorship

AI operates in abundance.

So the question shifts from: “Can you recall the answer?” to “Can you ask the better question?”

And this is where the current education model shows its limits.

Also Read: Gender gap in GenAI skills is narrowing, but progress remains uneven, Coursera finds

The hidden limitation: Education rewards convergence

Most education systems reward convergence thinking:

• Find the correct answer
• Follow the expected method
• Produce the accepted framework

But GenAI excels at convergence.

What it struggles with — and where human advantage lies — is divergence:

• Challenging premises
• Identifying unseen patterns
• Questioning assumptions
• Connecting disciplines in novel ways
• Acting with contextual judgment

Our education systems largely assess answers. The future economy will reward judgment. Those are not the same.

Education as a signalling mechanism is weakening

Degrees once signalled:

• Rigor
• Persistence
• Domain expertise
• Access to curated knowledge

But when AI can:

• Summarise an MBA textbook
• Draft a legal memo
• Generate a financial model
• Write production-ready code

Then the credential alone becomes insufficient. Not irrelevant — but insufficient.

What differentiates tomorrow’s knowledge worker is no longer: “How much you know.”

It becomes:

“How deeply you understand.”

“How effectively you apply.”

“How clearly you decide.”

Education, in its current form, does not consistently measure these dimensions.

The new divide: Curiosity vs compliance

GenAI does something profound. It removes knowledge access as a structural advantage.

But it introduces a new differentiator: curiosity.

Two individuals can access the same AI.

Only one chooses to:

• Probe deeper
• Refine prompts
• Challenge outputs
• Cross-check assumptions
• Explore adjacent domains

Education traditionally rewarded compliance:

• Follow curriculum.
• Pass exam.
• Meet benchmark.

The new economy rewards inquiry:

• What else?
• Why not?
• What’s missing?
• What’s next?

This is not a minor adjustment. It’s a systemic shift.

Also Read: GenAI in lending: Faster approvals, smarter risks, and personalised credit

What education must evolve into

If we are serious about preparing a generation of true knowledge workers, education must shift across five structural dimensions.

• From memorisation → Meta-learning

Teach students:

• How to learn
• How to unlearn
• How to validate AI outputs
• How to interrogate sources

AI can retrieve answers. Humans must validate relevance.

• From siloed disciplines → Interdisciplinary synthesis

Real-world problems do not come neatly packaged:

• Climate intersects with finance.
• Healthcare intersects with data ethics.
• Supply chains intersect with geopolitics.

True knowledge workers will be synthesisers, not specialists confined within narrow lanes.

• From fixed curriculum → Dynamic learning models

Curricula often lag the industry by years.

In a world where AI models update in months, static syllabi become outdated quickly.

Education must become:

• Modular
• Continuous
• Adaptive
• Stackable

Learning cannot end at graduation.

• From exams → Applied judgment

Assessment should increasingly measure:

• Scenario reasoning
• Ethical trade-offs
• Decision framing
• Risk calibration

The world does not grade people on multiple-choice questions. It rewards decision quality under uncertainty.

• From credential prestige → Portfolio evidence

Future differentiation will likely come from:

• Projects
• Problem-solving artifacts
• Real-world experimentation
• Public thinking

What you build may matter more than where you studied. It implies application.

The knowledge worker of the new age

Peter Drucker popularised the term “knowledge worker” decades ago.

But GenAI forces us to redefine it.

A true knowledge worker in the AI era:

• Does not compete on access
• Does not compete on recall
• Does not compete on surface frameworks

Instead, they compete on:

• Depth
• Context
• Original framing
• Decision velocity
• Ethical clarity
• Strategic foresight

Education systems must therefore cultivate:

• Systems thinking
• Probabilistic reasoning
• Bias awareness
• Creativity under constraint
• Communication clarity
• Cross-domain fluency

These are not exam-friendly traits. But they are future-critical capabilities.

Talent vs experience in an AI-accelerated world

AI compresses learning curves.

A junior analyst can produce outputs once reserved for senior professionals.

An executive can independently generate strategy drafts without layers of support.

So, where does experience fit?

Experience now becomes:

• Pattern recognition under ambiguity
• Judgment calibrated by lived consequence
• Crisis-tested decision making
• Ethical discernment

Talent becomes:

• Speed of synthesis
• Intellectual curiosity
• Cross-domain integration
• Learning agility

Education should nurture both.

But today, it often privileges standardised performance over adaptive capability.

Also Read: The use of GenAI is turning innocent employees into insider threats: Here’s how to fix it

The structural recalibration we need

If we continue educating for yesterday’s scarcity economy, we will produce graduates optimised for irrelevance.

If instead we redesign education for:

• Abundance of information
• AI-augmented productivity
• Continuous reinvention
• Portfolio-based credibility
• Judgment-based differentiation

Then we create a generation that does not fear AI — but compounds with it.

The real imposter is not the human.

It is the outdated system that measures humans by metrics AI can outperform.

In conclusion

GenAI is not replacing education. It is exposing what education was truly built to optimise.

The future knowledge worker will not win by competing with AI on answers.

They will win by:

• Asking sharper questions
• Integrating broader perspectives
• Exercising wiser judgment
• Pursuing depth relentlessly
• Exploring “what’s next” before it becomes obvious

Education must therefore evolve from a delivery system of knowledge into a training ground for discernment.

In a world where AI knows almost everything, the true advantage belongs to those who know what matters.

And that begins with rethinking how we educate — not just what we teach.

This article is Part 4 of a four-part series on “Redefining Knowledge Work: AI, Ownership, and the Future of Value.” Explore the rest of the series: Part 1, Part 2, Part 3.

—

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

The post The real imposter is the system: Rethinking education in the age of GenAI appeared first on e27.

Your pitch isn’t too long because you care too much. It’s too long because you don’t yet understand.

January 9, 2007 — Macworld, San Francisco. Steve Jobs takes the stage.

“Today, we’re introducing three revolutionary products. A widescreen iPod with touch controls. A revolutionary mobile phone. And a breakthrough internet communications device.”

He pauses. Repeats it. Then pauses again.

“These are not three separate devices. This is one device.”

Most people remember the reveal. Almost nobody studies the structure. Jobs did not explain — he engineered expectation, then collapsed it. He let the audience close the distance themselves, then handed them the reward of inevitability.

That is compression.

Meanwhile, your forty-seven-slide deck is sitting quietly in someone’s inbox. Unread. A polite pass is already half-drafted.

These two facts are not coincidental.

The battlefield you chose

Daniel Kahneman divided the mind into two systems: fast, intuitive System 1 and slow, deliberate System 2. Founders tend to assume investors operate in the second. They don’t.

Early-stage decisions are made in System 1. System 2 exists mostly to justify them afterwards.

Here is what that means in practice: The moment your pitch becomes dense — over-explained, over-hedged —you force System 2 online. And when System 2 activates, the investor is no longer listening. They are auditing.

Auditing is adversarial by design. It looks for gaps, inconsistencies, overreach — and it finds them, because every business has them. You have chosen to fight on the only terrain where you are guaranteed to lose.

The deck didn’t just fail to convince. It selected the wrong game.

Also Read: Cambodia startups move from pitch to payoff

The founder who speaks less — but lands precisely. Who answers without rushing toward silence. Who leaves space unguarded? That restraint carries a signal no slide deck can manufacture: I don’t need to persuade you. This already stands.

Over-explanation is not passion. It is fear, wearing the costume of diligence.

What Shannon knew

Claude Shannon defined information as entropy — the degree of surprise in a message. What you cannot predict carries information. What you already expect carries none.

The average pitch deck is 90 per cent predictable. TAM/SAM/SOM.  A competitive matrix. Five-year projections no one believes. Entropy: zero. Signal: zero. Noise, presented with the production value of rigour.

Now consider this: Fei-Fei Li raised US$230 million anchored on two words — Spatial Intelligence. No slides. No deck. A concept so compressed it reshaped the room. Inside those two words was the complete answer to every investor’s three-part question: Why now? Why her. Why does it change everything?

That is density. That is what a pitch is supposed to be — not a document, but a gravitational event.

A black hole compresses vast mass into finite space — not by removing meaning, but by eliminating everything that isn’t load-bearing. A great pitch obeys the same physics. 120 seconds that hold the market’s contradiction, the team’s irreversible proof, and the investor’s fear of missing it — all at once, without remainder.

If you cannot compress, you have not yet reached the centre of your own idea. The pitch is not the failure. The understanding is.

The asset called silence

Japanese aesthetics has a concept: ma — the charged space between notes, between gestures, between words. Not absence. Potential. The silence doesn’t mean the music has stopped; it means something is about to land.

In the best pitches, silence is not a gap in delivery. It is where the investor’s imagination enters. And once they begin to co-create the narrative — once they are supplying the ending — you no longer need to sell it.

Also Read: Your agency’s pitch deck is a clone: Here’s why Meta’s new rules and AI will force you to evolve or collapse

Mike Moritz once reflected on his first meeting with Google’s founders. “Larry and Sergey said very little,” he recalled. “But their silence said everything.”

That is not charisma. That is structure — trust, rendered in its most economical form.

Three tests

Don’t audit your pitch by adding. Audit it by removing.

What length actually reveals

Da Vinci wrote: “Simplicity is the ultimate sophistication.” In venture, this is not a sentiment. It is filtration. Investors use it as a screen before they finish their second slide.

A 120-second pitch is not a format. It is a measurement device. It reveals — with a precision no due diligence process can match — whether you have reached the centre of your own idea, or are still orbiting it.

And investors can read that signal before they open the deck.

“Your pitch isn’t getting longer because you care more. It’s getting longer because you’re not done thinking.”

—

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

The post Value creation: The compression principle — How to edit your pitch down to its atomic core appeared first on e27.

In the digital asset ecosystem, custody is not just a feature. It is the foundation upon which everything else rests. Cryptocurrency operates as a bearer asset. This means whoever holds the private keys effectively owns the funds. This simple truth carries profound implications. Unlike traditional banking, where a forgotten password triggers a straightforward reset process, losing or compromising a private key in the crypto world often results in permanent and irreversible loss. There is no customer service hotline to call, and no administrator exists to undo a transaction. No safety net catches you when you fall.

As we navigate 2026, the importance of proper custody has evolved from a technical consideration to an existential necessity. Blockchain immutability means that transactions cannot be undone. If assets are stolen via a compromised key, there is simply no recourse to recover them. The numbers tell a sobering story. Approximately 20 per cent of all Bitcoin, or roughly 4 million BTC, is estimated to be permanently inaccessible due to lost keys or poor personal custody practices. That is billions of dollars worth of value vanished into the digital ether.

The threat landscape has grown increasingly sophisticated. Phishing attacks were responsible for approximately 83 per cent of stolen funds in 2025. High-profile exchange breaches like the devastating US$1.5 billion Bybit hack in early 2025 sent shockwaves through the industry. These incidents underscore a harsh reality. Basic storage methods are no longer sufficient to protect against modern threats. Meanwhile, institutional adoption has reached a tipping point. As of 2026, 74 per cent of family offices are actively engaged in cryptocurrency. They come with stringent requirements. These sophisticated investors demand qualified custodians who can meet fiduciary duties, ensure proper asset segregation, and provide comprehensive insurance coverage. The message is clear. Custody has matured from a DIY experiment into a professional service industry.

Also Read: Bitcoin holds US$71K as Ethereum surges 15%: What’s driving the US$2.44T crypto rally

For those entering the crypto space, the question is not whether to use custody solutions. The question is which model best fits their needs. The industry has converged around three primary approaches. Each comes with distinct advantages and trade-offs.

Self-custody remains the purist choice. It offers total autonomy and privacy. This model appeals to tech-savvy individuals who value sovereignty above all else. When you hold your own keys, you answer to no one. No platform can freeze your assets. No intermediary can deny your transactions. No third party can surveil your holdings. This freedom comes with a sobering responsibility because there is no forgot password button. User error is the primary risk, and mistakes are unforgiving. A lost seed phrase, a compromised device, or a simple typo can result in permanent loss. Self-custody demands technical competence, meticulous attention to detail, and an acceptance of absolute personal responsibility.

Third-party custody offers professional security and insurance coverage. This makes it ideal for institutions and beginners alike. These platforms employ teams of security experts. They maintain robust infrastructure and often carry insurance policies to protect against losses. The trade-off is counterparty risk since you are trusting another entity with your assets. Platform insolvency, regulatory action, or internal malfeasance can all threaten your holdings. Recent history has shown that even the most reputable exchanges can fall. They can take customer funds with them. Third-party custody simplifies the user experience. It requires careful due diligence in selecting a trustworthy provider.

Emerging as the goldilocks solution for many is the hybrid model utilising Multi-Party Computation technology. This approach offers distributed control and flexibility. It is particularly attractive to enterprises and exchanges. MPC splits private keys into encrypted shares distributed across different parties. This ensures the complete key never exists in one place. This occurs even during transaction signing. This eliminates single points of failure while maintaining operational efficiency. This sophistication comes at a cost. Operational complexity is the primary risk. Implementing and managing MPC solutions requires technical expertise and careful coordination among multiple parties.

Also Read: Crypto falls 1.29% to US$2.34T as geopolitical fear triggers risk-asset selloff

Modern custody solutions have evolved far beyond simple password protection. Today, the security arsenal includes multiple layers of defence. These are designed to eliminate vulnerabilities and protect against increasingly sophisticated threats. Cold storage remains the bedrock of secure custody. It keeps private keys entirely offline in air-gapped hardware that cannot be accessed remotely. This physical separation from the internet provides robust protection against hacking attempts. It makes cold storage ideal for long-term holdings. For those who choose this path, hardware wallets have become increasingly user-friendly while maintaining military-grade security.

Multi-Party Computation represents the cutting edge of custody technology. By splitting private keys into encrypted shares distributed across different locations or devices, MPC ensures that no single point of failure exists. Even during the critical moment of transaction signing, the complete key never materialises in one place. This mathematical elegance provides security that is greater than the sum of its parts. Multi-signature technology adds another layer of protection. It requires multiple independent keys to authorise transactions. A typical setup might require three out of five designated keys to approve a transfer. This ensures that a single compromised device cannot move funds. This distributed authorisation creates a system of checks and balances. It mirrors traditional financial controls. Hardware Security Modules provide tamper-resistant physical protection for key generation and storage. These specialised devices automatically wipe their contents if physical interference is detected. This provides a final line of defence against determined attackers.

So how should you approach custody? The answer depends on your technical comfort, risk tolerance, and usage patterns. For long-term holdings that you do not need to access frequently, cold storage via hardware wallets remains the gold standard. The inconvenience of physical access is a small price to pay for the security of keeping your keys completely offline. For active trading or frequently accessed funds, reputable exchanges offer convenience. They should be used judiciously. A prudent approach is to keep only a small portion of your portfolio, perhaps less than 20 per cent, on exchanges. Treat them as transactional tools rather than storage solutions. Move profits to cold storage regularly. Never leave more on an exchange than you can afford to lose. For those managing significant assets or operating businesses, the hybrid MPC model offers an attractive balance of security and functionality. It requires careful implementation and ongoing management.

Also Read: Why crypto market cap falls to US$2.53T despite regulatory clarity win and 6-day ETF streak?

The crypto custody landscape reflects the maturation of the entire ecosystem. What began as a libertarian experiment in self-sovereignty has evolved into a sophisticated industry. It offers solutions for every type of user. This ranges from the casual investor to the institutional giant. The technology is more robust. The options are more diverse. The stakes are higher than ever. Your private keys are more than just strings of code. They are the keys to your financial kingdom.

Choose your custody solution wisely. Understand the trade-offs. Never forget that in the world of cryptocurrency, you are ultimately your own bank. With great power comes great responsibility. In 2026, the tools to exercise that responsibility have never been more advanced. The question is not whether you can afford to take custody seriously. It is whether you can afford not to.

—

The post The keys to your kingdom: Navigating crypto custody in 2026 appeared first on e27.