In Southeast Asia, a new investment philosophy is gaining traction: funding for good. This approach goes beyond traditional profit metrics, seeking startups that tackle pressing social and environmental challenges while delivering solid financial returns.

For investors, the rationale is clear: businesses that solve real problems often create more resilient revenue streams, attract loyal customers, and reduce long-term risks—all of which translate into better returns.

Why funding for good works

Investing in ventures with measurable social impact isn’t just ethical—it’s strategic. Purpose-driven businesses often operate in underserved markets, leverage technology to scale, and build trust with stakeholders. With ESG and impact investing gaining momentum in SEA, startups that quantify their impact are increasingly attracting funding from both traditional and impact-focused investors.

Models of funding for good

Funding-for-good takes many forms, offering multiple ways for investors to create both impact and returns:

• Equity investment: Buying shares in startups with measurable social or environmental outcomes, sharing in both profits and mission-driven success.
• Sustainability-linked loans: Lending with interest rates tied to achieving specific ESG targets, such as carbon reduction, energy efficiency, or social impact metrics. Lower risk and lower costs reward measurable progress.
• Revenue-sharing or outcome-based financing: Investors receive returns only if certain social or environmental outcomes are met, aligning incentives with real-world impact.
• Blended finance: Combining concessional funding (from donors or development banks) with commercial capital to de-risk investments in high-impact sectors like agriculture, health, or renewable energy.

Also Read: The future of work with AI: 2025 and beyond

Catalysing industry-wide impact and transformation

These finance models, especially sustainability-linked loans (SLLs) are no longer niche financial instruments—they are catalysts for  transformation across Southeast Asia. By tying financing terms to measurable environmental or social outcomes, SLLs incentivise companies to embed sustainability into the core of their operations.

Here’s how different sectors are embracing this model:

Self-storage: StorHub’s green commitment

In 2023, StorHub secured an SG$180 million (US$133.2 million) SLL from CIMB and UOB, marking the first of its kind in Asia’s self-storage sector. The loan’s interest rate is linked to sustainability performance metrics across 13 properties in Singapore, including energy efficiency and carbon footprint reduction. This initiative underscores StorHub’s commitment to integrating ESG principles into its operations.

Beverage industry: ThaiBev’s sustainable growth

Thai Beverage Public Company Limited (ThaiBev) completed a THB 10 billion (US$270 million) SLL with Bank of Ayudhya (Krungsri) in 2024, the first SLL for a local beverage company in Thailand. The loan features Key Performance Indicators (KPIs) related to sustainability targets, aligning with ThaiBev’s commitment to sustainable growth.

Data centres: AirTrunk’s sustainable financing

AirTrunk, a hyperscale data centre operator, closed an A$16 billion (US$10.56 billion) sustainability-linked refinancing package across Australia, Hong Kong, Malaysia, and Singapore. The financing includes targets for energy and water efficiency, renewable energy uptake, and gender pay equity, aiming for net-zero emissions by 2030.

Supply chain: Goodpack’s green logistics

Goodpack, a Singapore-based sustainable supply chain solution provider, secured a US$790 million SLL coordinated by ING. The loan is the first private equity-backed leveraged SLL in Southeast Asia, supporting Goodpack’s efforts to enhance sustainability in the supply chain industry.

Education: Vinschool’s sustainable expansion

Vinschool Joint Stock Company in Vietnam signed a US$150 million syndicated SLL with the Asian Development Bank (ADB) in 2024. The loan supports Vinschool’s initiatives to improve educational infrastructure and access, aligning with sustainable development goals.

Also Read: From Seed to Series: Navigating different funding rounds with PR

These examples illustrate a key trend: SLLs and impact investing are penetrating diverse industries and supply chains, gradually making sustainability a financial and operational priority. For investors, this means climate change is no longer abstract—it’s actionable, measurable, and directly tied to business performance. Companies that adapt not only reduce environmental impact but also position themselves as leaders in a rapidly decarbonising economy, creating long-term value for both shareholders and society.

The investor perspective

It is clear that impact can be quantified, de-risked, and scaled. Funding for good is not charity—it’s smart, long-term value creation. By using modern investment instruments like SAFE, convertible notes, and sustainability-linked loans, investors can both structure risk efficiently and maximise measurable impact.

Funding for good is thus not philanthropy disguised as business; it is a strategic approach to long-term value creation.The question is whether SEA investors will seize this moment to make purpose-driven investment the standard.

The challenge—and opportunity—for investors is to make funding for good the norm rather than the exception. By backing startups that deliver measurable social impact, capital can flow toward ventures that strengthen communities, preserve the planet, and still generate strong financial returns.

The question is: will investors in Southeast Asia lead the charge in proving that doing good and doing well are not only compatible, but profitable for people, planet and profit?

—

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 Pro

The post Funding for good: A new era appeared first on e27.

As a CTO leading a company that specialises in app development, custom software, AI/ML solutions, and cloud services, I can tell you that many of my peers in the tech world focus heavily on the latest technologies. They chase after the newest frameworks, tools, or innovations. While this is important, I believe there’s something even more critical: trust.

In my years of experience, I’ve come to realise that technology, no matter how advanced, only thrives in an environment of trust. Without it, all the cutting-edge solutions in the world won’t make a real impact. Here’s why trust should be at the heart of everything we do in tech.

The trust factor in software development

When we build apps or custom software for clients, trust is the foundation. Clients must trust us to deliver what we promise on time, within budget, and with a high level of quality. They need to know that we’re not just chasing the latest tech trends, but that we’re focused on building solutions that solve their unique problems.

This trust goes both ways. We also trust our teams. When developers and engineers feel trusted, they’re more likely to be creative, motivated, and focused on delivering top-tier results. They know they have the freedom to innovate and the support they need to succeed.

Building trust in AI and Machine Learning

In the world of AI and ML, trust is even more crucial. These technologies can be transformative, but they’re also often seen as a “black box” mysterious and sometimes even intimidating. To use AI/ML effectively, businesses must trust that the algorithms are working as expected, that the data is secure, and that the models are making decisions in an ethical way.

As a CTO, I’ve always emphasised transparency in AI development. We ensure that our clients understand how we’re training models and making decisions. This openness builds trust, especially when dealing with sensitive data. By offering clear explanations and setting realistic expectations, we can make AI approachable and valuable.

Also Read: Indirect prompt injections: The AI attack vector you didn’t see coming

Cloud services and the trust challenge

Cloud services represent another area where trust is vital. Companies are placing their most important data and systems in the cloud, trusting that they’ll be secure, accessible, and reliable. Any disruption or breach could have severe consequences. That’s why we invest heavily in cloud security, compliance, and reliability.

We don’t just trust the cloud providers we work with — we build trust with our clients by making sure that their data is protected, and that they have 24/7 access to their services. Our commitment to keeping their systems running smoothly is what sets us apart in this competitive space.

Trust is built over time

Trust doesn’t happen overnight. It’s earned through consistent actions. As a CTO, I’ve learned that our clients’ trust is the result of our company’s track record. It’s about delivering on promises, addressing issues when they arise, and always being transparent about our processes.

We focus on long-term relationships, not short-term wins. We want our clients to know that we are always looking out for their best interests, that we aren’t just after the next big tech trend. Instead, we’re focused on making sure their technology works for them, now and in the future.

Trust with your team

I also want to emphasise how trust with your internal team is just as important. As a leader, you must trust your team to make decisions and take responsibility. This empowers them to do their best work. It also fosters a culture of collaboration, where everyone feels their voice is heard and valued.

Technology is ever-evolving, and there will always be new tools and frameworks to learn. But trust is timeless. When your team trusts each other and the leadership, it creates an environment where innovation flourishes.

Also Read: Semiconductors at risk: The invisible threats that could break global supply chains

The bottom line

While many CTOs may obsess over technology, I obsess over trust because I’ve seen firsthand how it drives everything else. Technology can solve problems, streamline processes, and improve business outcomes. But without trust, none of that matters. It’s trust that keeps clients coming back. It’s trust that inspires teams to perform at their best. And it’s trust that allows technology to reach its full potential.

So, while I’m certainly passionate about the latest tech trends and innovations, I never lose sight of the bigger picture. Trust is what makes technology truly powerful. It’s the glue that holds everything together and ensures long-term success. And that’s why, as a CTO, it’s what I obsess over most.

—

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 Pro

The post Most CTOs obsess over tech, I obsess over trust — here’s why appeared first on e27.

The withdrawal of the United States from a range of international climate and energy institutions marks a structural shift in how it exercises influence in global governance. The fiscal savings associated with withdrawal are minor relative to overall federal expenditure. The more consequential effect lies in reduced institutional presence, diminished influence over rule formation, and altered channels of international coordination. You can read about it here, in my earlier piece.

Institutional participation is a form of geopolitical leverage. It provides access to agenda-setting processes, influence over reporting standards, early insight into regulatory direction, and informal coordination channels across states. Even when US leadership has been inconsistent, continued participation preserved the ability to shape, slow, or redirect emerging norms. Withdrawal reduces that capacity.

The global climate and energy system is unlikely to collapse as a result. Major developed economies and climate-vulnerable states continue to support multilateral engagement. However, governance influence will shift toward actors that remain active. Standards, methodologies, and financing frameworks will increasingly reflect their priorities. The system will persist, but with greater fragmentation and reduced US shaping power.

For startup ecosystems, this matters because climate and energy governance operates upstream of markets. Definitions of “renewable,” “transition,” “carbon-neutral,” and “sustainable” influence procurement rules, capital allocation, disclosure requirements, and trade conditions. When institutional influence shifts, startup operating environments shift with it.

The most likely systemic outcome is regulatory divergence. Carbon accounting systems may differ across jurisdictions. ESG disclosure regimes may lose harmonisation. Hydrogen classification and transition taxonomies may evolve along separate tracks, look at how nuclear energy has become the hot topic when it was hydrogen a couple years ago. For multinational companies, this increases compliance complexity. For startups, it introduces market segmentation risk at an earlier stage.

Influence over climate governance will redistribute rather than disappear. The European Union is positioned to expand regulatory influence. China will likely continue emphasising infrastructure scale and manufacturing dominance. Middle powers will gain greater negotiation space. The United States is likely to exercise influence more through bilateral agreements and industrial policy than through institutional leadership.

Also Read: Why I’m trading bytes for atoms: The 65-year-old investor breaking the climate tech silos

Within this broader geopolitical adjustment, Southeast Asia occupies a strategically significant position.

Southeast Asia is characterised by rapid energy demand growth, high climate exposure, infrastructure deficits, and dependence on external capital and technology. It does not define global standards but implements them. Changes in institutional engagement by major powers, therefore, affect the region primarily through capital flows, project structures, and compliance frameworks.

A structural transfer of climate leadership from the United States to Southeast Asia is unlikely. The region does not possess equivalent research depth, capital scale, or institutional agenda-setting capacity. However, selective reallocation effects are plausible.

As regulatory uncertainty increases in advanced economies, investors may seek high-growth deployment markets. Southeast Asia’s energy transition requires:

• Grid expansion
• Distributed energy systems
• Storage deployment
• Climate adaptation infrastructure

These are capital-intensive sectors with clear demand fundamentals. Private capital may therefore allocate incrementally more toward the region, not as a governance substitute, but as a growth destination.

The geopolitical shift also increases the likelihood of bilateral, project-based engagement. If US climate diplomacy becomes more commercially oriented, Southeast Asia could see expanded direct partnerships in liquefied natural gas, grid modernisation, critical minerals cooperation, and energy infrastructure financing. In this context, the region becomes a strategic project arena rather than a co-designer of institutional frameworks.

For startups, the implications are concrete.

• First, market fragmentation increases the value of interoperability. Southeast Asian startups that can design products compliant with multiple reporting regimes and standards frameworks will hold a structural advantage. Regulatory translation and cross-border compatibility become investable capabilities. AI-led green growth is one big space, and I’ve talked extensively about it.
• Second, infrastructure-heavy innovation gains relative importance. Unlike mature markets focused on optimisation, Southeast Asia’s transition requires build-out. Startups in distributed solar, storage integration, grid software, microgrids, climate resilience, and water systems operate in markets defined by execution rather than abstract policy alignment. These sectors are less dependent on multilateral coordination and more dependent on capital mobilisation and public-private partnership structures.
• Third, capital formation within the region becomes more important. If global governance becomes less centralised, regional sovereign wealth funds, development banks, and blended finance vehicles may play a larger role in underwriting projects. Startups that understand these capital structures will scale more effectively than those relying exclusively on Silicon Valley or European venture capital.

Also Read: The shifting geopolitics of sustainability, energy, and climate

There are also constraints.

Regulatory harmonisation within ASEAN remains incomplete. Sovereign risk varies significantly across member states. Currency volatility, political transitions, and legal enforcement inconsistencies raise perceived risk for international investors. Deep-technology research infrastructure remains concentrated outside the region. These factors limit the scale of ecosystem migration from advanced economies to Southeast Asia.

The likely outcome is not a wholesale pivot of global clean-tech leadership toward Southeast Asia. Instead, the region becomes a deployment-intensive growth market within a more fragmented geopolitical system. Startups that treat Southeast Asia as an execution platform rather than a governance hub are better aligned with structural realities.

From a geopolitical perspective, the US withdrawal signals a shift from institutional leverage toward industrial and bilateral leverage. For startup ecosystems, this increases the importance of understanding how state power shapes capital flows, standards formation, and infrastructure finance.

For founders and investors operating in Southeast Asia, the core strategic question is not whether global climate governance continues. It is how fragmentation alters funding channels, regulatory pathways, and scaling models.

In a less centralised global system, startup ecosystems become more regionally defined. Southeast Asia’s advantage lies in demand growth, infrastructure needs, and its position between major power blocs. Its vulnerability lies in policy inconsistency and capital dependence.

The long-term trajectory depends less on US disengagement and more on Southeast Asia’s ability to strengthen regulatory coherence, improve project execution, and build institutional credibility. In a geopolitically fragmented climate regime, regions that reduce uncertainty and align capital with infrastructure needs will attract disproportionate innovation activity.

The shift underway is therefore not a transfer of leadership. It is a reordering of how and where clean-tech innovation scales.

—

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

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

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

The post Reconfiguration of SEA cleantech ecosystem appeared first on e27.

The global business landscape is currently undergoing a structural shift so profound it has been dubbed the AI Apocalypse. For decades, the global economy has been optimized for a world where human intelligence was the primary scarce resource. We are now witnessing the “unwind” of that premium. As machine intelligence becomes a competent and rapidly improving substitute for human cognition across a growing range of tasks, the financial systems built upon billable human hours are undergoing a painful, disorderly repricing.

Defining the AI apocalypse

The term “AI Apocalypse” does not refer to a cinematic doomsday scenario of rogue machines. Instead, it describes an economic “left tail risk” where the rapid adoption of autonomous, agentic AI triggers a mass displacement of white-collar work. According to the viral Citrini Research report, “The 2028 Global Intelligence Crisis,” we are entering a period where the traditional value of human-led data synthesis, strategic insight, and process management is being eroded by systems that can perform these functions faster and at a fraction of the cost.

The source of market panic

The current anxiety among investors and professionals stems from the realization that AI is moving beyond simple “copilot” assistance to “agentic” autonomy.

• Agentic AI can execute complex workflows without human intervention.
• This shifts the paradigm from technology augmenting humans to technology replacing the need for human intermediaries.
• The fear is not just about job losses, but a deflationary spiral where the collapse of labor costs leads to a contraction in consumer spending and a fundamental devaluation of service-oriented business models.

High-profile casualties: why Accenture and IBM?

Legacy consulting and IT services giants like Accenture and IBM have found themselves in a unique and uncomfortable position. Historically, these firms thrived on “information asymmetry,” they possessed expertise their clients lacked.

1. Model Conflict: Their revenue models are heavily reliant on billable hours. If AI can produce a 5,000-word strategic white paper in minutes, a task that previously took a team of consultants weeks, the core value proposition of the “billable head” collapses.
2. Cannibalization: To remain relevant, these firms are selling the very AI tools that allow clients to bypass human consultants. They are essentially building their own replacements.
3. Exposure: With massive global workforces, Accenture alone employs over 740,000 people, they carry enormous fixed cost bases that become liabilities if utilization rates drop due to AI-driven efficiency.

Also read: Why Singapore manufacturers must embrace MES for the future

Evidence of the “intelligence crisis” in 2026

Recent developments suggest the scenario described by Citrini Research is already in motion. In early 2026, the market response to new enterprise AI tools from providers like Anthropic saw Accenture stock drop significantly, reflecting an “AI scare trade.”

The “re-pricing” is visible in the divergent narratives between corporate messaging and market valuation:

• Falling Bookings: In late 2025 and early 2026, reports emerged of declining quarterly new bookings for major IT services firms. For instance, Accenture noted a slowdown in its U.S. federal business, with internal sources describing a scramble for work-breakdown structure (WBS) coverage as employees fight for billable projects.
• Booking-to-Revenue Lag: While firms report high “Advanced AI bookings,” there is a noticeable lag in converting these into actual revenue. In December 2025, it was noted that while AI bookings nearly doubled, they represented only a small fraction of total revenue, suggesting that “AI pilots” are not yet replacing the massive revenue streams lost from traditional consulting.
• The End of Transparency: In a telling move during the Q1 fiscal 2026 earnings call, Accenture leadership announced they would stop reporting specific metrics for advanced AI revenue and bookings. The company argued AI is now “pervasive,” but critics view this as a way to mask the potential “cannibalization” where AI projects fail to offset the decline in legacy services.

Strategic vision for the Singapore business community

For businesses in Singapore, the AI Apocalypse presents a critical crossroad. The city-state’s high-value, service-led economy is particularly exposed to the “intelligence unwind,” but also uniquely positioned to lead the transition.

• From Intermediary to Architect: Singaporean firms must move away from being “implementers” of technology to becoming architects of AI-integrated ecosystems.
• Outcome-Based Models: Local businesses should accelerate the shift toward “outcome-based” or “fixed-price” pricing. Relying on billable hours in 2026 is a strategy for obsolescence.
• Sovereign AI and Ethics: As global firms struggle with workforce friction and legacy models, Singaporean enterprises can gain a competitive edge by focusing on “Sovereign AI” and robust AI governance, areas where human oversight remains a high-value, non-negotiable premium.

The AI Apocalypse is not the end of business, but the end of business as we knew it. The firms that survive will be those that embrace their own transformation before the market decides they are no longer necessary.

Also read: Top 5 best ERP software for building material business in Singapore | 2026 guide

Why we write this article

PRbyAI aims to share updated market news using our team’s tech knowledge, helping B2B customers make informed decisions.

About PRbyAI

PRbyAI is a tech-driven Martech startup leveraging cutting-edge AISEO to help customers generate leads and tap into new markets.

—

Want updates like this delivered directly? Join our WhatsApp channel and stay in the loop.

This article was shared with us by PRbyAI

We can share your story at e27 too! Engage the Southeast Asian tech ecosystem by bringing your story to the world. You can reach out to us here to get started.

Featured Image Credit: Canva Images

The post The intelligence unwind: Navigating the AI apocalypse and the consulting crossroad appeared first on e27.

Conversations about equity in the digital economy often begin with representation. We measure the number of women who are founders, the number who work in engineering roles, and the number who hold leadership positions.

These numbers matter. But in practice, the inequalities many founders encounter begin much earlier, often before funding or hiring even enters the picture.

They begin with access to ecosystems.

Before a startup raises capital or gains media attention, there is a quieter question that shapes opportunity: who already understands how the ecosystem works.

The invisible infrastructure of opportunity

Technology ecosystems are built on networks.

Investors frequently meet founders through referrals. Speaking invitations often come through professional networks. Media coverage can begin with relationships that provide context and credibility.

For founders already embedded in these circles, the process can feel natural. For others, especially those entering the startup world for the first time, the pathways are far less obvious.

When I first started building companies, many aspects of the startup ecosystem were unfamiliar to me. Concepts like investor networks, founder communities, and speaking platforms were things I discovered over time rather than systems I was immediately part of.

This experience is not uncommon. Many founders know how to build products or market services, but the broader ecosystem around startups — capital networks, media exposure, and industry platforms — is something they encounter only after they begin building their companies.

Without that awareness, it is difficult even to know where opportunity exists.

Ecosystems compound opportunity

Being part of a network does not guarantee success. However, it can significantly increase the number of opportunities a founder encounters.

Visibility often creates a chain reaction.

A founder who gains exposure may receive speaking invitations. Speaking opportunities can build credibility. Credibility often leads to introductions. Introductions may eventually lead to partnerships or funding conversations.

Each step increases the likelihood of the next.

For founders who begin outside these networks, the challenge is different. They are not only building a company; they are also learning how the ecosystem itself operates.

That learning curve can be steep, particularly in industries where relationships and reputation play a significant role in opening doors.

Also Read: Cybersecurity and trust: A digital dawn for women in rural India 

Partnerships and hiring reflect similar dynamics

The same pattern appears in partnerships and hiring.

Startups frequently seek partnerships that allow them to expand their reach or credibility. Larger organisations often prefer partnering with companies that already demonstrate traction or visibility.

This creates a natural filtering effect. Companies with existing exposure tend to attract more partnership opportunities.

Hiring decisions can follow a similar logic. Many professionals prefer the stability of established companies with clearer career pathways. Startups, by contrast, rely on individuals who are comfortable with uncertainty and risk.

Neither of these patterns is inherently unfair. They are rational decisions from the perspective of individuals and organisations.

However, when combined, they can reinforce ecosystems in which opportunity tends to circulate among those already connected.

The role of AI in expanding reach

Artificial intelligence is often discussed as a tool that could level the playing field for founders. In practice, its impact is more nuanced.

AI primarily amplifies capability.

For founders who already understand how to conduct outreach, build networks, or create content, AI can significantly increase scale. Tasks that previously required teams can now be automated or accelerated.

Outreach campaigns, research, content creation, and operational workflows can be executed far more efficiently.

However, AI does not automatically replace strategic understanding. If someone does not yet know how to approach investors, position themselves publicly, or build professional networks, AI cannot fully bridge that gap.

In many ways, AI functions similarly to a team. It can execute instructions and scale processes, but the direction still comes from the founder.

For those who understand how ecosystems operate, AI can expand its reach. For those still learning, the underlying challenge remains the same: understanding how to navigate the system.

Also Read: Bridging the gender gap in GenAI learning: Strategies to get more women involved

Equity is also about ecosystem transparency

Discussions about equity in tech frequently focus solely on representation. Representation is important, but a wider set of factors influences ecosystems.

Geography, cultural context, and professional exposure all shape how easily someone navigates the startup environment.

In regions with mature startup ecosystems, founders may encounter investors, accelerators, and industry platforms early in their journey. In other regions, these pathways may be less visible or accessible.

Equity, therefore, is not only about who participates in the digital economy. It is also about how transparent and accessible the ecosystem itself is to newcomers.

Lowering the barriers to entry

One of the most meaningful ways to build a more equitable tech ecosystem is by making these pathways clearer.

This can include initiatives such as:

• Sharing knowledge about how investor networks operate
• Creating platforms where emerging founders can gain visibility
• Expanding mentorship and peer networks for early-stage founders
• Making ecosystem knowledge easier to access for those entering the industry

These changes do not eliminate competition or guarantee outcomes. Instead, they reduce the gap between founders who grow up inside startup ecosystems and those who enter them later.

Opportunity should not depend solely on proximity to the right circles.

Building more inclusive digital economies

The digital economy continues to evolve rapidly. Tools such as AI are lowering operational barriers and enabling smaller teams to build and scale companies more efficiently than before.

Yet the flow of opportunity within technology ecosystems is still heavily influenced by networks and access.

As ecosystems expand, the challenge is not only to increase participation but also to make the knowledge, relationships, and pathways that shape opportunity more visible.

When founders understand how these systems work, they can participate more fully and contribute back to the communities that support them.

Stronger ecosystems are not built only through innovation. They are built by ensuring that more people understand how to enter and navigate the opportunities they create.

—

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

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

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

The post Why access to ecosystems is tech’s true equality problem appeared first on e27.

One of the challenges leaders often come up against is how they can best instil a performance culture within their group. Much of this effort is around instilling a vision and an accessible plan that your team will buy into, linked to the values and behaviours that will forge your culture.

However, no leader can build this alone. You will need support, and the best way to instil culture is to get to a self-policing environment where behaviours form a culture leading to results.

Not only are you looking to align and build, but you are also looking for the pillars of your new culture and values, those people who will, in turn, be your leaders and who will embrace the new journey together with you. It is these people who will live the behaviours that will underpin and create your culture.

Finding these heroes early is critical to building your team. By exemplifying the values and behaviours that will shape your culture, both you and your team will steer the mission forward. Do not be shy to tell these critical players that you are conferring on them this leadership role, and bring them into decision-making and people decisions where appropriate.

What this often requires, and particularly if the group is large or geographically distributed, is the identification and enrolment of your leaders of tomorrow, who will become the cultural beacons for the transformation you are embarking upon. It is they who will help to distill your communicated message, and who within your cohort will support, motivate, and focus everyone on the commonly aligned goals you have set.

This is easily stated, but some leaders can struggle to inspire a colleague to take on more responsibility, or to take a step toward acting more like a leader.

Here what not to do when encouraging folks to step up and take a more enhanced role:

Don’t pressure or force them

The first thing you must not do is to assume that they want it, especially if it the ask is not going to come with more compensation, or even an elevated title, straight away. Approach the topic, therefore, with some delicacy. The way you approach this can significantly impact their willingness and readiness to take on the new challenge.

Applying pressure can be damaging and counterproductive to what you are trying to build. Pressure can lead to resentment and stress, especially if you are asking someone to go beyond their comfort zone.

If a colleague is feeling pressured into a role that they are not ready or interested in, then their performance and morale can suffer. This can lead to avoidance, distraction, and possibly even a desire to leave the company, or to refuse to take on new challenges in the future.

You should as a leader be in the business of constructing a binding message and vision for the business. This should involve the lived values and behaviours you would like to see as part of your outreach to your colleague. Having an open conversation about their role, should be a motivational and supportive process, not one driven by pressure or coercion.

Also Read: 6 leadership lessons I learned after we raised our seed round

Instead, share your values and vision for the business and encourage your colleague by highlighting their strengths and potential. Be clear on the roles and behaviors that you are asking them to deliver but make it clear that the decision is theirs to make. Offer to provide support and resources if required to help them to succeed, should they choose to step up. Always allow them time to consider.

Do not overlook their current workload

Encouraging someone to take on more responsibility without considering their current workload can be overwhelming and counterproductive. Of course, it could be that you are asking someone to be a bridge to other functions, building the network and spreading the word about your area’s vision and focuses.

It could also be that you want them to deliver through their ‘soft skills,’ such as showing up with values and behaviours such as “better together,” which implies the forging of individual internal networks, and focus on collaboration to find solutions to problems in the business. Whilst you might not consider these actions impactful on a colleague’s current responsibilities, you must also consider how much this is pushing someone beyond their comfort zone.

This stress alone, if unsupported, could serve to impact their current effectiveness within their current role. Instead, have an open and clear discussion about their current role, workload, and your defined new set of responsibilities, and how these might be integrated. Consider also, redistributing some of their tasks, or providing additional resources if required. This shows that you care about their well-being and are also committed to their success.

Don’t ignore their career goals

Again, don’t assume that they want it. Assuming everyone wants to take on more responsibility or a leadership role can be a mistake. Not everyone has the same career aspirations. This could especially be the case if the new responsibilities do not align with their career goals. If this is the case, they may feel unmotivated or disconnected from their work, and this could lead to a lack of engagement.

Instead, discuss their career aspirations and how taking on additional responsibilities will align with their long-term career goals. Demonstrate how the new responsibilities will help them to grow and advance in their desired direction. If you treat the approach as you would a sale, and tailor yourself to their individual goals you can make the proposition more appealing and relevant.

Don’t fail to provide proper training and support, including coaching

Do not assume that your colleague can immediately handle the new responsibilities without some form of training and perhaps close mentorship and support, particularly if the ask is to be a pillar of support toward a change of culture through demonstration of soft skills, values and behaviours.

Without proper preparation, they may struggle with their new responsibilities, leading to frustration and possible failure. This can lead to discouragement and serve only to undermine confidence.

Also Read: 10 unarguable things that great leaders do

Instead, offer them all the support and advice, coaching and mentorship that they need. Regular check-ins can help address any issues early on and ensure that your colleague feels that they are invested in, and gaining all the support they need to be successful. Remember to always create and support a psychological safe space for your people to express themselves in, without fear or judgement.

Don’t neglect to recognise and celebrate their efforts

Encouraging someone to take on more responsibility without recognition and celebration of their successes, can lead to a lack of motivation and sense of appreciation. The worst outcome could be that the ask made of them can seem insincere or exploitative.

Failing to acknowledge hard work and achievements can come across as inauthentic and lead to feelings of being undervalued and under-appreciated. This of course can have the total opposite affect from creating a centre of leadership aligned to your vision, goals, values and behaviours.

Instead, you might create a pocket of counter programming in your organisational set up. Instead, regularly acknowledge their progress as positive reinforcement boosts morale, motivating them to forge ahead.

Public recognition is also a powerful motivator and especially useful when building culture, if aligned to your published values and behaviours, such as “Winning it together,” “Creating magic,” and so on. Do not miss the opportunity to reinforce what you are trying to build by not acknowledging your organisational cultural building heroes.

Conclusion

Inspiring a colleague to step up and take on more responsibilities in a leadership role, requires a thoughtful approach matched to authentic support.

By avoiding the pitfalls of pressuring them, overloading their workload, ignoring their career goals, failing to provide support and training, neglecting to celebrate them – you can create a positive and motivating environment to encourage growth, not only of this individual but of the team and culture you are building.

Ultimately, by identifying the leaders in your group and working closely with them, you can get to a self-policing environment. That said, you must keep it fresh and ensure that you are always working to bind the group to the goals you are setting. This is why it is vital to identify and map your talent and potential leaders in the group early.

—

The post How not to elevate a colleague to a leadership role appeared first on e27.

In this interview, e27 speaks with Paruey Anadirekkul, Founder & CEO of Spacely AI, a generative AI platform focused on spatial design. As AI continues expanding beyond text and image generation into specialised professional domains, Spacely AI explores how automation can support architects, interior designers, and real estate professionals in visualising ideas faster and making earlier, more confident decisions.

This conversation forms part of e27’s broader AI Pulse coverage, which examines how organisations across the region are building, deploying, and governing AI in real-world settings.

Generative AI for spatial design workflows

e27: Briefly describe what your organization does, and where AI plays a meaningful role in your work or offering.

Paruey: Spacely AI is a generative AI platform built for spatial design — helping professionals turn ideas, floor plans, and rough concepts into realistic 3D visualizations and design iterations in minutes. Our customers are primarily interior designers, architects, and real estate professionals, with a large portion based in the US and Europe.

AI plays a central role in both our product and internal operations. On the product side, we use proprietary generative models and 3D algorithms to automate rendering, layout variations, lighting adjustments, and even 2D-to-3D model conversion. This shortens early-stage design cycles dramatically, where most cost and timeline decisions are made.

Internally, AI supports product development, customer success, marketing experimentation, and data analysis. We treat AI not as a feature add-on, but as infrastructure — embedded into workflows to reduce repetitive tasks and allow our team and customers to focus on higher-value creative and strategic decisions.

Reducing friction in design and property decisions

e27: What is one concrete way AI is currently creating value within your organisation or for your users or customers?

Paruey: One clear way AI creates value is by reducing friction at the decision stage.

For real estate brokers and agencies use Spacely AI to help buyers see the true potential of a property. Instead of relying on imagination when viewing an empty or outdated space, buyers can instantly visualize renovations or new layouts. This reduces hesitation, shortens the purchase decision cycle, and increases conversion because clients can see what they are buying — not just what exists today.

For Interior Design Company, the value is in faster client alignment. Early in a project, most delays come from back-and-forth discussions about style, mood, and direction. By generating multiple realistic design options quickly, Spacely AI helps clients react to something concrete. This shortens alignment time, reduces revisions, and allows the team to move into detailed design work faster.

In both cases, the outcome is not just speed. It is clearer communication, stronger confidence in decisions, and better commercial results.

Also read: AI Pulse Exclusive: How CoBALT is designing AI that teams can actually trust

Balancing model performance and economics

e27: What was a key decision or trade-off you had to make when adopting, building, or scaling AI?

Paruey: One key trade-off we faced was between model performance and economic sustainability.

Early on, we realized that generic models did not perform well for our target users. Interior designers and architects prompt very differently from casual users. So we invested time in fine-tuning and optimizing models specifically for spatial design workflows. That improved output quality and consistency, but it also increased compute costs.

At the same time, we had to balance cost, speed, and quality for different user tasks. High-fidelity rendering requires more GPU resources, while quick concept iterations can run on lighter infrastructure. Choosing when to use which model became a product decision, not just a technical one.

Gross margin is critical in AI SaaS. We had to design our pricing and token model carefully to protect margins while still delivering meaningful value to customers. The lesson was that AI capability alone is not enough — the real challenge is building a system where performance, user experience, and unit economics all work together sustainably.

Adoption momentum and integration challenges

e27: Looking back, what has worked better than expected, and what proved more challenging than anticipated?

Paruey: What worked better than expected was adoption speed. Once designers saw that AI could generate realistic concepts in minutes, not days, the willingness to experiment was high. Many professionals who were initially skeptical became regular users after seeing practical results in client meetings.

What proved more challenging was workflow integration. AI can produce impressive outputs, but using it effectively requires learning how to prompt well, iterate, and interpret results. There is still a skill curve. The value comes not from one-click magic, but from knowing how to guide the system.

Another challenge is the pace of AI improvement. Our rendering accuracy today is significantly better than it was six months ago. Costs, speed, and quality have improved rapidly. However, user perception often lags behind. Some customers still remember early limitations — like distorted elements — even though those issues have been resolved. Managing expectations in a fast-moving technology landscape has been just as important as improving the models themselves.

Rethinking workflows for AI adoption

e27: What is one lesson about applying AI in real-world settings that leaders or founders often underestimate?

Paruey: One lesson leaders often underestimate is that AI adoption is not a plug-and-play purchase.

Buying access to an AI tool does not automatically produce better outcomes. The real value only appears when teams rethink their workflows around it. Many organizations try to layer AI on top of existing processes without changing how work is structured. That usually leads to frustration or underuse.

In our experience, the biggest gains come when teams revisit where time is spent, where decisions are delayed, and where iteration cycles are slow. Then AI can be embedded intentionally into those pressure points. Adoption requires training, experimentation, and sometimes redefining roles — not just software procurement. AI is most powerful when paired with operational redesign, not treated as a shortcut.

Also read: AI Pulse Exclusive: How Asia AI Association is advancing human-centred AI across the region

Starting with outcomes, not models

e27: Based on your experience, what is one practical recommendation you would give to organisations that are just starting to explore or scale AI?

Paruey: One practical recommendation is: don’t start with the technology.

AI models change every few months — in cost, speed, and capability. If you start by choosing a model, you risk building around something that may soon be obsolete. Instead, start with outcomes. Define what you want to improve, map the current workflow, and identify the specific bottlenecks or repetitive tasks that can be automated or augmented.

Only after that should you evaluate which AI model fits the job today. Treat AI as a modular component. Design your architecture and processes so you can swap models as the landscape evolves. The advantage doesn’t come from picking the “best” model — it comes from building flexible workflows that can continuously improve as AI advances.

AI becoming invisible infrastructure

e27: Over the next 12 months, how do you expect your organisation’s use of AI, or the role of AI in your industry, to evolve?

Paruey: Over the next 12 months, AI will become less visible and more expected.

In our industry, AI will shift from being a standalone tool to something embedded directly inside design workflows. Users won’t “use AI” as a separate step — it will be integrated into rendering, planning, cost estimation, and collaboration processes. The focus will move from generating impressive outputs to improving measurable outcomes like faster alignment, reduced rework, and higher win rates.

We also expect leadership expectations to mature. Instead of being impressed by what AI can generate, leaders will ask: did this reduce costs, shorten timelines, or increase revenue? The conversation will move from capability to accountability. AI will become operational infrastructure — evaluated on business impact, not novelty.

Adaptability over technical advantage

e27: Anything else you want to share with the audience?

Paruey: One final thought: AI will not reward the most technical companies — it will reward the most adaptive ones.

The advantage won’t come from having access to the latest model, because everyone does. It will come from how quickly teams experiment, measure impact, and adjust workflows. The organizations that win will treat AI as an ongoing capability, not a one-time transformation project.

Also, we should be honest: AI is not perfect. It makes mistakes. It requires oversight. But so do humans. The real opportunity is designing systems where human judgment and AI speed complement each other. When that balance is right, the results are not just faster — they are better decisions made earlier, where they matter most.

Also read: AI Pulse Exclusive: How Explico is building AI teachers can actually rely on

Designing AI for practical creative workflows

This conversation highlights how AI is increasingly moving into specialised professional domains beyond general content generation. In areas like spatial design, real estate, and architecture, the emphasis is shifting toward faster iteration, clearer decision-making, and integrating AI directly into everyday workflows. As adoption matures, organisations may find that the real advantage lies less in the models themselves and more in how effectively teams adapt processes to work alongside AI.

For more interviews, analysis, and real-world perspectives on how organisations across the region are applying AI in practice, click here.

—

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

The e27 team produced this article

We can share your story at e27 too! Engage the Southeast Asian tech ecosystem by bringing your story to the world. You can reach out to us here to get started.

Featured Image Credit: Spacely AI

The post AI Pulse Exclusive: How Spacely AI is bringing generative AI into spatial design workflows appeared first on e27.

In the high-pressure world of startups, every decision counts. You are competing with others, trying to ensure rapid growth, and trying to beat your own pace for innovation. You feel the pressure to build a squad that can match your speed and work ethic.

While working towards meeting all these demands, a vital consideration is constantly ignored: empathy as an element of the hiring process. It is quite easy to assume that soft skills, such as empathy, are secondary to speed and technical know-how.

Empathy isn’t merely an afterthought to consider. It underlines strategic advantages. Leaders who lead with empathy foster trust, improve communication, and create more agile and responsive teams.

Integrating empathy into the hiring process does not entail an act of kindness. Rather, it involves fostering a culture that boosts a company’s appeal and helps retain sought-after employees.

Redefining empathy in hiring: More than just soft skills

Empathetic hiring is understanding candidates as people, not only as a CV or resume. It is listening, communicating, and ensuring courtesy and respect at every step of the recruitment process.

Absence of empathy in hiring can be very expensive. Negative candidate experience is a primary reason for high turnover rates and toxic work cultures. As an example, in their survey, KPMG found that 88 per cent of the business leaders admitted that they retained toxic employees to a damaging degree, costing companies anywhere from £2,000 to £10,000 per month.

During a major reorganisation, Avon focused on empathetic recruiting by clarifying their hiring processes and by improving job descriptions and feedback processes. The fairness of the hiring process dramatically increased through empathy.

Empathy widens soft skills assessment and improves retention, thus strengthening the company culture. While valuing empathy strengthens the investment in the team, it also improves the resilience and cohesion of the team.

Challenges of building people-first teams under pressure

As a startup founder, the need to scale is ever-present. This pressure can lead to difficult choices that force you to make quick compromises on your team’s cohesion.

Meeting your growth targets with a fixed number of employees creates a backlog of positions that must be filled immediately, however, a rushed recruitment process is guaranteed to yield bad results. The cost of hiring the wrong person for a position (role) at this pace will exceed what you would spend on a slowed recruitment process.

The temptation to hire based on personal values and backgrounds is ever-looming. However, this limits innovation and new ideas. Homogeneous teams are outperformed by diverse teams.

Also Read: Leading during uncertain times: The rising importance of empathy

Accessing wider segments of talent pools as a result of remote work systems comes with its challenges. For instance, some spontaneous interactions that promote collaboration are often muted as well. Synchronising in-office presence during hybrid working models can increase spontaneous collaboration while retaining the benefits of remote work.

Taking care of potential candidates while managing an organisation’s hiring needs is challenging, but empathy should play a role in the entire process. Neglecting empathy ultimately results in attrition of the talent pool as the culture becomes maladaptive.

How AI is revolutionising empathetic hiring in startups

The integration of AI tools can uncover a bare minimum threshold of unconscious bias in the evaluation of resumes and applications. This evaluation will focus on the skills and qualifications, ensuring no bias during evaluation on all fronts.

Estimation of the written and spoken sentiment with tone and cultural fit is done through NLP Technology in real-time during conversation. This makes it easier to think more profoundly, making it more holistic.

AI chatbots enable candidates to communicate instantly 24/7. They can provide answers and updates regarding the progress of the hiring process. This enhances the experience of candidates as they appreciate being continuously informed.

Hiring remains personal when there is a blend of AI accuracy with human scrutiny. The more tech solutions are used, the more devoid of empathy the outcomes become, resulting in senseless automation and poor judgment. Empathy–guided AI makes interactions intelligent and multifaceted.

Onboarding with empathy: The secret sauce to retention

Structures not designed with the new hire in mind can lead to rapid employee resignation. An alarming 20 per cent of new employees resign within the first 45 days of employment.

Onboarding with empathy solves this, so the aim is to respond to the issue through clearly defined dedicated learning pathways, continuous feedback loops, and providing psychological safety. Feeling valued is extremely important, especially from day one.

Contemporary applications of AI make it easier to manage adaptive onboarding by tailoring experiences to the user’s preferences and their approaches to learning. These systems will adjust to the new employee’s preferred pacing, provide real-time help as needed, and monitor participation rates to ensure that every employee receives the attention necessary for engagement.

Implementing empathy into the onboarding processes has both strategic effectiveness and intent. The organisations can benefit from increased retention rates, while the new employees set themselves up for ongoing success events by having AI customisation of their onboarding experience.

Building and managing people-first teams in high-pressure settings

Demonstrating empathy becomes vital in critical situations. It is the only path forward that everyone can agree upon. Trust, burnout, and performance are intertwined in coherent ways that empathetic leadership addresses and resolves.

Also Read: AI revolution: Balancing human empathy and robotic efficiency in customer service

Empathy-based leadership strategies:

• Active listening: Acknowledge and address concerns raised by team members. Listening strengthens trust, and trust fortifies communication.
• Transparent communication: Provide pertinent business intelligence like objectives, goals, and challenges to employees. Employees are granted autonomy from the shackles of ambiguity. Alignment with the organisation is further enhanced.
• Flexibility: Respond to the specific demands of the employees. A properly directed flexible work schedule enhances balance and leads to greater job satisfaction.

Authentic obstacles: Burnout and disengagement in scaling teams

Particularly in scaling up, startup centres face the challenge of burnout and disengagement, with disengagement standing out as a pronounced attribute. Struggles remain for the founders even as startups flourish. A survey indicated 53 per cent of founders reported burnout within the previous year, highlighting a need for sustainable growth.

The notion of burnout is a menace that stems from the offshoot threat facing organisations. Tasks are perceived to be augmenting solely to incentivise the employees to perform overtime work. That is where AI can truly shine.

The use of AI solutions solves all of these problems. MeBeBot is an example of a bot that can analyse conversations and retain the morale of the team as long as they are typing. This enables you to solve problems before they become too big to fix. Furthermore, AI Workload on Asana can also pinpoint an imbalance where a team member is taking on too much work.

The future is people-first and AI-smart

To fully develop resilient, high-performing teams, organisations’ AI-focused hiring won’t work; they will need to incorporate empathy-driven hiring processes. Enhanced candidate experience starts with integrating human connection to hiring and team management processes, which leads to stronger, connected, engaged teams in organisations.

Empathy allows leaders to establish this intelligent coexistence that intertwines the benefits of AI with those of human efforts. The effectiveness of AI simplifies and automates tasks like administration whilst reducing workplace biases, but trust, growth, and workplace culture are built around the human touch. Compassionate leadership guarantees that technology is not meant to take over the work that makes success achievable.

This is the perfect moment to reflect on your hiring approaches, as well as the structuring and managing of your teams. Adopt empathy-centred AI tools as they allow you to improve human interaction and communication within your organisation. This approach allows you to acquire amazing talent and, in addition, builds a company where people flourish and provide sustainable, impactful, positive contributions.

—

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, LinkedIn, and our WA community to stay connected.

Image courtesy: Canva Pro

The post Hiring with empathy: How to build people-first teams in high-pressure environments appeared first on e27.

What is an AI visibility tool?

An AI Visibility Tool is software that monitors and analyzes how a brand, product, or service appears on Generative AI platforms and Large Language Models (LLMs). Unlike traditional SEO tools, these tools focus on “generative engine optimization.” They track if a brand is mentioned or recommended by AI agents like ChatGPT, Perplexity, Gemini, and DeepSeek. Businesses can use this information to understand their digital footprint in the era of conversational search. They can also adjust their content strategies to remain visible to users interacting with AI.

Major challenges of SEO marketing in Singapore amidst the AI shift

In Singapore, buyers are increasingly relying on AI assistants instead of search bars. This shift presents a major challenge for the SEO marketing industry. The primary difficulty is the loss of “click-through” data. When an AI provides a direct answer, the user often does not visit the original website, which makes traditional traffic metrics less useful. In addition, Singapore is a multilingual hub. AI models often synthesize information differently across languages. This means a brand might be visible in an English search but invisible when a user searches in Mandarin or Malay. Navigating this requires a complete change in how marketers define “visibility.”

Also read: AI agents and ERP: Why Singapore businesses must act now

Why Singapore’s SEO marketing sector is dissatisfied with legacy SEO tools

The SEO marketing sector in Singapore is increasingly frustrated with traditional platforms. These tools were built for a search environment that is quickly changing.

• Keyword Focus: Traditional tools focus on keywords, but they do not account for how AI interprets context and intent.
• Lack of LLM Coverage: Most traditional tools do not track mentions within ChatGPT, Perplexity, or DeepSeek. This leaves marketers unable to see where recommendations are happening.
• Delayed Data: Traditional SEO data relies on periodic crawls. AI models and “live” search features require real-time monitoring.
• Inaccurate Localization: Legacy platforms often struggle to simulate the localized experience of a user in Singapore, especially when switching between different regional AI configurations.

Top 5 reliable AI visibility tools

Several tools have emerged to help marketers bridge the gap between traditional SEO and AI visibility. Here are the top five options currently available for the Singapore market.

1. BuildSOM

Pros

• The only global AI Visibility Tool that offers native non-English AI visibility monitoring, providing accurate results for Chinese, Malay, and other regional languages.
• Cost of effective prompt is among the lowest in the market, making it accessible for high-frequency tracking.
• Results from LLMs are captured through the browser UI, simulating the true consumer journey for realistic data.
• BuildSOM provides the largest coverage of LLMs among competitors, ensuring a comprehensive view of the AI landscape.
• A global tool that natively caters to DeepSeek, a critical LLM platform for the non-English community.

Cons

• Focuses on AI visibility, so its traditional SEO offering is limited.
• The user interface is English-only.

2. SEMrush

Pros

• Extensive historical database for keyword research and backlink analysis.
• Comprehensive site auditing tools to maintain technical health.
• Integrates social media monitoring with traditional search metrics.

Cons

• Support for non-English prompts is minimal. Results for non-English queries are often executed on English platforms, leading to inaccurate data for the Singapore market.
• The domain-based pricing scheme is expensive, with subscription fees easily increasing for brands managing multiple domains.
• LLM support is limited and does not include DeepSeek, Google AI Overview, or Copilot.

Also read: Why traditional SEO is dying in Singapore — and how AISEO pioneers are winning the next Blue Ocean

3. Ahrefs

Pros

• Backlink crawler and data accuracy for traditional link-building metrics.
• Detailed competitor analysis features.
• Content Explorer tool helps identify high-performing topics.

Cons

• The interface is designed for technical SEO professionals.
• The platform remains SEO-focused, with AI visibility playing a small role.
• Lacks native non-English AI visibility results.

4. Profound

Pros

• Focuses on brand mentions within generative AI responses.
• Offers data visualization tools to track brand sentiment.
• Provides alerts when brand citations change within AI models.

Cons

• The cost per prompt is higher than competitors.
• The Starter plan is restrictive, supporting only one LLM, forcing users into a more expensive plan.
• Does not support DeepSeek or Google AI Mode.

5. Otterly.ai

Pros

• Provides a view of brand mentions across AI chatbots.
• Includes automated reporting features for agency-client communication.
• Allows tracking of specific competitor sets.

Cons

• No free account option.
• The user experience is hampered by slow page loads and a fragmented dashboard.
• LLM support is restricted and lacks integration with DeepSeek and Google AI Mode.

Also read: The architect’s mandate: Building a resilient foundation for the intelligent enterprise

Preparing for the future

Many industry experts believe the transition to AI will be complete by 2028. At that point, traditional search may become secondary to AI-driven information gathering. It is recommended to try different AI Visibility Tools to find your best fit. Act quickly to integrate these tools, or prepare to become irrelevant in a world where AI agents are the new information sources.

Why we write this article

PRbyAI aims to share updated market news using our team’s tech knowledge, helping B2B customers make informed decisions.

About PRbyAI

PRbyAI is a tech-driven Martech startup leveraging cutting-edge AISEO to help customers generate leads and tap into new markets.

—

Want updates like this delivered directly? Join our WhatsApp channel and stay in the loop.

This article was shared with us by PRbyAI

We can share your story at e27 too! Engage the Southeast Asian tech ecosystem by bringing your story to the world. You can reach out to us here to get started.

Featured Image Credit: Canva Images

The post Top 5 reliable AI visibility tools for SEO marketing in Singapore appeared first on e27.

Most digital products do not fail because of bad features. They fail the moment a user hesitates before clicking “confirm”.

That hesitation rarely comes from design alone. It comes from trust. Can I trust this payment to go through? Will my data be safe? If something goes wrong, will the system catch it?

In Southeast Asia, where digital adoption has scaled faster than regulation and infrastructure in many markets, that moment of hesitation matters more than ever. Cybersecurity is no longer a backend function. It is the layer that allows the digital economy to function at all.

Without it, fintech cannot move money, startups cannot scale across borders and users simply stop engaging.

Trust is the real product

Southeast Asia’s digital economy is projected to exceed US$300 billion in gross merchandise value, according to the e-Conomy SEA report by Google, Temasek and Bain & Company. Much of this growth is driven by payments, e-commerce and platform-based services.

But underneath that growth is a quieter system at work.

Every successful transaction depends on invisible checks. Fraud detection models flag anomalies in milliseconds. Encryption protocols secure user data. Identity verification systems confirm that the person clicking “pay” is who they claim to be.

Users do not see these systems. But they feel them.

A payment that processes smoothly builds confidence. A suspicious delay, an unexpected OTP loop, or a failed transaction does the opposite. Trust is not built through marketing. It is built through consistent system behaviour.

This is why cybersecurity is better understood not as protection, but as permission. It gives users the confidence to act.

Where systems break, trust follows

Despite this, many companies still treat cybersecurity as a compliance layer rather than a core part of product design.

This gap becomes visible when systems scale.

In fintech, fraud incidents continue to rise across the region. In Singapore, scam losses crossed a record SG$1.1 billion (US$814 million) in 2024, a 70 per cent increase year-on-year, with over 51,000 reported cases. The trend has continued into 2025. Victims lost SG$456.4 million (US$338 million) in just the first half of the year, despite stronger controls and enforcement.

Across Southeast Asia, the scale is even more significant. An estimated US$23.6 billion was lost to scams in the past year, with nearly one in ten consumers falling victim and 84 per cent expressing concern that scams are increasing. In Malaysia, fraud remains heavily driven by social engineering and impersonation schemes, with telecom-related scams alone accounting for RM715 million (US$150 million) in losses across nearly 29,000 cases in 2025.

These are not only security failures. They are trust failures.

When users lose money or data, they do not distinguish between a phishing attack and a platform vulnerability. The perception is simple: the system was not safe enough.

Startups often underestimate this. Early-stage teams prioritise speed, onboarding and growth metrics. Security is handled reactively, usually after an incident or when enterprise clients demand it.

This creates a pattern. Systems appear to work at a small scale, but begin to strain as transaction volumes grow, integrations multiply and cross-border complexity increases.

Also Read: Cybersecurity is not an IT problem: It is a trust architecture crisis

The overlooked risks inside organisations

External threats often get the most attention, but many vulnerabilities sit inside organisations.

Access control is a common blind spot. As teams grow across markets, permissions are rarely updated with the same discipline as product features. Employees retain access they no longer need. Third-party vendors are integrated quickly but not always audited thoroughly.

In HR systems, for example, inconsistent data structures and fragmented access can lead to deeper issues than simple inefficiencies. Leadership dashboards become unreliable. Headcount visibility weakens. Decision-making slows because the data cannot be fully trusted.

This is not typically framed as a cybersecurity issue. But it is part of the same trust layer. If internal systems cannot guarantee data integrity, external trust becomes harder to maintain.

AI and data amplify the stakes

The rapid adoption of AI tools across Southeast Asia is adding a new dimension to the trust equation.

Companies are integrating AI into customer service, analytics and internal workflows. In many cases, this involves feeding large volumes of data into third-party platforms.

The risk is not always immediate breaches. It is the gradual erosion of control.

Sensitive business data, customer information or proprietary models can be exposed through poorly governed usage. Employees may not fully understand what data is being shared or stored.

This creates a new kind of vulnerability. Not one driven by malicious attacks, but by unclear boundaries.

As AI becomes more embedded in operations, cybersecurity needs to extend beyond infrastructure into usage behaviour. Policies, training and system design all become part of the trust layer.

Moving from protection to trust design

The shift that companies need to make is not simply adding more security tools. It is rethinking how systems are designed.

Reactive protection focuses on preventing breaches. Trust design focuses on enabling confidence.

This can take simple but meaningful forms.

Clear transaction flows reduce uncertainty during payments. Visible verification steps reassure users without adding unnecessary friction. Transparent data policies help users understand how their information is used.

Internally, structured access controls and consistent data governance improve reliability. Systems become easier to audit, scale and integrate across markets.

The difference is subtle but important. Security stops being a barrier and becomes part of the user experience.

Also Read: Cybersecurity: The evolution from digital safeguard to economic governance

A regional challenge, not just a technical one

Southeast Asia adds another layer of complexity.

The region is not a single market. It is a collection of regulatory environments, infrastructure maturity levels and user behaviours. What works in Singapore may not translate directly to Indonesia, Vietnam or the Philippines.

This makes cybersecurity less about standardisation and more about localisation.

Payment habits differ. Identity systems vary. Regulatory requirements evolve at different speeds. Companies expanding across the region need to account for these differences while maintaining consistent trust standards.

This is where many rollouts struggle. Systems are designed centrally but implemented unevenly. Security controls become inconsistent. Gaps emerge between markets.

Users may not articulate these gaps clearly, but they feel them in the form of friction, delays or uncertainty.

Trust is the limiting factor

The next phase of Southeast Asia’s digital growth will not be limited by demand. Adoption is already strong. Digital behaviours are deeply embedded.

The limiting factor will be how much trust systems can sustain.

Cybersecurity, in this context, is not a defensive function. It is an enabling layer. It determines whether users complete transactions, whether businesses scale across borders and whether investors view systems as reliable.

For founders and operators, the question is no longer whether security is important. It is whether their systems are designed to be trusted.

Because in the end, users do not engage with infrastructure. They engage with outcomes.

And trust is what makes those outcomes possible.

—

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.

The post Cybersecurity is the trust layer powering Southeast Asia’s digital economy appeared first on e27.