I have sat through hundreds of pitch decks. I have seen countless presentations from founders brimming with passion and caffeine. And in almost every single one, there is the inevitable slide labelled TAM (Total Addressable Market).

It is presented as the cornerstone of the investment thesis. Look at this huge number! Look at the billions we could capture! It is meant to inspire confidence, but to a seasoned eye, it often signals one thing: a profound lack of imagination.

Let me be clear: in the current economy, obsessing over a predetermined, static market size is intellectual laziness. It represents a fundamental misunderstanding of how exponential value is actually created. Your market-size slide is useless. It is the metric of the incremental thinker—the person who assumes the world today is the final, finished product.

The tyranny of the existing pie

The typical market analysis starts with an established industry, slices it up into tidy segments, and then claims a tiny percentage of the existing revenue stream. This approach is profoundly limiting. It commits the entrepreneur to a war of attrition where one fights aggressively over the same customers that two dozen well-funded competitors are already fighting for.

This mindset forces you to think vertically: How can I get ten per cent more of the market already defined by my incumbent rival? It anchors your ambition to the current state of affairs, assuming that customer behaviour, technology, and needs will remain exactly as they are right now.

The largest, most enduring companies of the last two decades — the true titans of value creation — did not win by taking a tiny slice of an existing, defined market. They won by performing a strategic judo move: they created entirely new markets that were invisible to the old way of thinking. Before these companies existed, their market size was functionally zero.

Also Read: Gold hits US$4,500 while Bitcoin bleeds: The year-end market disconnect explained

Lateral movement: The key to invisible markets

The strategic move that matters is lateral movement. This is the ability to look at an existing, painful problem and solve it by linking two previously unrelated concepts, thereby defining a whole new category of demand.

Consider the example of the modern smartphone. Its initial market size wasn’t based on the “mobile phone market,” which was finite. It’s true, a massive market size was created by linking three separate, previously unconnected markets: mobile communication, digital photography, and personal computing. The market was created in the overlap, not claimed from the existing carriers.

Lateral thinkers use the existing market size only as a base, a launchpad for understanding the current customer’s frustration. They don’t see the figure as a ceiling; they see it as a springboard. They ask: What is this customer trying to achieve today, and how can I invent a solution that makes their current behaviour obsolete?

From analysis to strategy

This is the main strategy of entrepreneurship: transforming a rigid, defined need into a fluid, limitless opportunity. It requires moving the focus from the external metric (the size of the market) to the internal insight (the depth of the customer pain).

The strategic conversation should not be: Our TAM is US$50 billion. The strategic conversation must be: We are solving a problem that is so severe, so expensive, and so pervasive that it will compel the creation of a new, US$100 billion category of spending.

Also Read: Holiday liquidity warning signs emerge across stocks gold and crypto markets simultaneously

For the founder, this means abandoning the easy comfort of benchmarking against rivals. It means looking for the latent demand, the unvoiced frustration, and the structural inefficiency that no one has dared to tackle because it required combining resources in a way the old industry structure deemed impossible or illogical.

So, the next time you are building a pitch deck, use the existing market size figure for two purposes only: context and contrast. Use it to show the investors what the existing, poor solution looks like, and then immediately pivot to demonstrating how your lateral strategy will invalidate that entire number, compelling customers to flow into the vibrant, wide-open space you have just engineered.

If your sole competitive strategy is to capture five per cent of a market that already exists, aren’t you just admitting you plan to be marginally better, rather than truly indispensable?

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Meta has announced the acquisition of Manus, confirming that the Singapore-based artificial intelligence company is joining the US tech giant to scale its autonomous agent technology to billions of users and businesses worldwide.

In a joint announcement, Meta stated that Manus has built “one of the leading autonomous general-purpose agents,” capable of independently executing complex tasks such as market research, coding, and data analysis.

The Manus service will continue to operate and be sold as a standalone product, while also being integrated into Meta’s consumer and business offerings, including Meta AI.

Meta said Manus is already serving the daily needs of millions of users and businesses globally. Since launching its first General AI Agent earlier this year, Manus has processed over 147 trillion tokens and enabled the creation of more than 80 million virtual computers. Meta added that it plans to scale the service to reach many more businesses across its platforms.

As part of the acquisition of Manus, the Manus team will join Meta to help deliver general-purpose agents across Meta’s products. Meta said the combination of Manus’s tech and talent would help unlock new opportunities for businesses and improve the lives of billions of people who use its services.

Also Read: How an AI cybersecurity company harnesses the power of AI for optimal business performance

Manus, in a separate statement, described the deal as a significant milestone and a validation of its work on General AI Agents. The company said it has focused on building a general-purpose agent designed to help users tackle research, automation and other complex tasks through continuous product iteration.

The company positioned itself as an “execution layer” for AI, transforming advanced capabilities into scalable and reliable systems that can perform end-to-end work in real-world settings. It reiterated that its agent has already processed more than 147 trillion tokens and powered over 80 million virtual computers in just a few months.

Manus stressed that the acquisition would not disrupt its customers. The company will continue to offer and manage its subscription service through its app and website, and it will maintain its operations in Singapore.

Manus said its solution is already driving value for millions of users worldwide and that, over time, it hopes to expand its subscription offering to millions of businesses and billions of people on Meta’s platforms.

Also Read: Navigating the trust labyrinth: My perspective on ethical AI marketing

“Joining Meta allows us to build on a stronger, more sustainable foundation without changing how Manus works or how decisions are made,” said Xiao Hong, CEO of Manus. “We’re excited about what the future holds with Meta and Manus working together, and we will continue to iterate on the product and serve users who have defined Manus from the beginning.”

Both companies framed the Manus acquisition as a step towards accelerating the adoption of autonomous agents across consumer and enterprise use cases, while maintaining continuity for existing Manus users.

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Image Credit: Manus, Meta

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The playbook is getting clearer every year. Sell into the U.S. and other mature markets, build using Southeast Asia’s talent engine. It’s not just about lowering costs anymore. It’s about creating leverage, speed, and scale by combining global revenue opportunities with regional execution advantages.

As founders, we’re watching the geography of tech shift in real-time. And those who understand how to bridge this gap—between customer and creator, headquarters and build hub, AI strategy and human capital—will win the next decade.

From cost centre to growth engine

For years, Southeast Asia was viewed primarily as a cost-saving destination. Offshoring, outsourcing, and BPOs dominated the narrative. But what’s changed is the quality of talent. Whether it’s engineers in Ho Chi Minh City, product managers in Manila, or designers in Jakarta, the region has grown a mature, hungry, and technically fluent workforce.

What’s more, countries like Singapore have positioned themselves as financial and regulatory gateways, helping global companies establish local HQs while tapping regional labour. Government incentives, English-speaking populations, and increasing venture capital activity have all accelerated the trend.

At NewCampus, we scaled our learning experience and delivery teams in Cebu and Manila to build a high-quality, cost-efficient training engine rooted in local expertise. Our Philippines team adapted content and operations for regional nuance, while our coaches in Vietnam and Indonesia delivered programs in local languages.

By hiring locally and thinking globally, we deepened engagement, boosted learner outcomes, and scaled delivery without sacrificing quality. This approach turned Southeast Asian talent into a competitive edge, enabling us to serve global clients with authenticity, agility, and cultural fluency from the ground up.

What used to be a back office is now a growth office. Product teams. Growth squads. Customer success pods. These aren’t secondary, they’re integral. And increasingly, they’re led from Southeast Asia.

Also Read: From lead generation to pipeline hygiene: What startups often miss

Global ambition, local execution

Take Canva for example. A multi-billion-dollar design platform built with deep Australian roots, but with a heavy operational and engineering footprint in the Philippines. Their support and design operations run lean but powerful, giving them the scale to service a global base while retaining product velocity.

Then there’s Xendit, the Stripe of Southeast Asia. Headquartered in Indonesia, they’ve used their deep regional knowledge and infrastructure to serve both local and international businesses. Their growth is a case study in how local teams, armed with global playbooks, can outcompete bigger, slower players.

Another standout is Deel. While not SEA-born, Deel has leveraged Filipino, Vietnamese, and Malaysian teams across operations, sales, and customer support. It’s a key part of how they scaled to a $12B valuation while offering 24/7 service and onboarding customers globally.

The takeaway here isn’t just that you can build cheaply in Southeast Asia. It’s that you can build well—with speed, quality, and cultural fluency that rivals any major tech hub.

The future is distributed (and competitive)

With AI reshaping how we work, there’s a misconception that geographic labour advantages will disappear. But the reality is more nuanced. AI is great at scaling what you already do well. That includes well-run, geographically diverse teams.

A support agent in Manila using an AI co-pilot will outperform one in San Francisco, still toggling between tools. A product manager in Kuala Lumpur working async with a design team in Bali can ship faster than an under-resourced team co-located in NYC.

Also Read: Startups, is your email strategy driving growth, or just gathering dust?

But only if the systems are in place. Founders need to think deeply about documentation, time zone overlaps, tooling, and most importantly, culture. Distributed teams don’t work by accident. They work because leaders design for clarity, autonomy, and shared rituals.

That means building AI literacy into onboarding. Investing in good managers who can lead without micromanaging. And recognising that time zones don’t kill productivity, unclear priorities do.

Moving forward

The arbitrage between Western revenue and Eastern execution is narrowing, but it’s not gone. In fact, it’s becoming more valuable as companies are forced to become more capital efficient, more globally aware, and more operationally excellent.

If you’re a founder today, you don’t just have an opportunity, you have an edge. The ability to tap top-tier developers in Vietnam, growth hackers in Singapore, or CX leads in the Philippines is no longer reserved for Fortune 500s. It’s accessible at Seed, Series A, and beyond.

And as the next wave of tech companies emerge—those built on crypto, AI, climate, and commerce—the ones who master this balance will win. Build globally. Sell globally. Operate locally. That’s the new startup stack.

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We live in an age defined by paradox.

The world has never been more connected — yet opportunity has never been more unevenly distributed. Technology has lowered the barriers to entry, yet raised the bar for participation. Knowledge flows freely, yet economic mobility feels increasingly restricted.

Economists once used the phrase “islands of modernity in a sea of underdevelopment” to describe colonial economies: pockets of advanced activity built for exports and foreign capital, surrounded by a much larger local population trapped in low-productivity subsistence sectors. Two economies exist side by side, with almost no bridge between them.

Today, that pattern has returned — only now, these islands are digital.

The K-shaped economy: One country, two systems

It’s not just inequality; it’s economic bifurcation.

A modern dual economy, unfolding in real time.

On one side, you have the tech-enabled class: remote workers earning in USD, SMEs using automation to scale, founders leveraging AI, and professionals selling their skills globally rather than locally. They belong to a borderless economy where geography matters less than capability, and where global demand rewards speed, skill, and systems.

On the other side, you have the local economy, where opportunity remains limited by geography, wage ceilings, and the slow pace of traditional industries. Here, jobs are replaced faster than they are created. Retail, F&B, manual labour, and low-skill office roles face both automation and competition. The hardest hit are the young — university graduates entering a job market where entry-level roles are disappearing, replaced by AI or consolidated into senior roles requiring experience they never had the chance to gain.

This divergence forms what economists now call a K-shaped economy — an economy where some groups accelerate upward while others stagnate or decline. The upper arm of the K rises: tech workers, global freelancers, AI-enabled founders, cross-border teams. The lower arm falls: retail, hospitality, local services, admin-heavy roles, SMEs struggling with digital adoption.

These two economies operate in the same country, but rarely interact. They use different tools, speak different economic languages, and respond to different incentives. One ascends; the other treads water.

Also Read: How to thrive in digital entrepreneurship in Asia today

The uncomfortable truth

The uncomfortable truth is this: The digital revolution was supposed to close gaps, but instead, it has deepened them.

Technology increases productivity, but only for those who know how to use it. Remote work increases income, but only for those with global-facing skill sets. AI amplifies talent, but only for those who are trained to leverage it.

Everyone else is left running on a treadmill that only gets faster, as they compete for limited opportunities in slower, smaller, and more fragile markets.

And this is where the danger lies. The gap is not personal — it is structural.

The technological trends of the 2020s have recreated a dual economy, accelerated by digital transformation. The globalised class becomes more mobile, more valuable, more connected. The localised class becomes more fragile, more replaceable, and more exposed to shocks.

What we’re witnessing is not merely different income groups. It is two different economies living in the same country, the same industry, sometimes the same company, but moving in opposite directions.

The digital “islands” have systems, tools, and global connectivity. The “sea” around them has talent, ambition, and potential, but lacks infrastructure to turn it into mobility.

Yet this divide is not inevitable.

Also Read: Asia’s digital gold rush: How to win in the US$600B digital economy

Bridging the digital divide

The gap widens when people and SMEs cannot access the tools that plug them into global markets — when they are trapped behind information barriers, trust barriers, and capability barriers.

The solution isn’t charity: It is access, systems and infrastructure.

It’s giving traditional businesses and workers the means to participate in the modern economy rather than watching it from the sidelines.

This is where market infrastructure matters. Not platforms that merely facilitate transactions, but systems designed to bridge structural economic divides. To give SMEs the same leverage, data, and operational discipline as the global players. To transform local businesses into regional ones. To bring clarity where the market runs on opacity. To give talent, vendors, and entrepreneurs the infrastructure to compete on merit, not connections.

Because if the world is splitting into islands of digital prosperity surrounded by seas of stagnation, then the real work — the necessary work — is to build the bridges.

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The majority of Singapore retailers are still using a POS system with simple inventory management instead of a comprehensive ERP system for retailers.

Singapore’s retail landscape remains heavily reliant on traditional Point-of-Sale (POS) systems. While these systems provide basic inventory tracking and transaction processing, they fall short of delivering the integrated capabilities of modern Enterprise Resource Planning (ERP) solutions. ERP systems offer end-to-end visibility across supply chain, finance, membership management, and customer engagement. Yet, many small and mid-sized retailers in Singapore continue to operate with legacy POS systems, citing cost concerns and resistance to change. This reliance on outdated systems could hinder competitiveness in a market increasingly shaped by digital transformation.

Johor-Singapore Train: Good news or bad news for Singapore retailers?

The upcoming Johor-Singapore Rapid Transit System (RTS) Link, expected to be operational by 2026, presents both opportunities and challenges for Singapore retailers. On one hand, easier cross-border travel could increase footfall from Malaysian shoppers, boosting sales in Singapore’s retail hubs. On the other hand, Singaporean consumers may find it more convenient to shop in Johor Bahru, where prices are often lower due to reduced operating costs. Retailers in Singapore must therefore rethink their strategies, leveraging ERP-driven insights to optimize pricing, promotions, and membership programs to retain customer loyalty.

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

What are the other challenges of retailers in Singapore in 2026?

Retailers in Singapore face a complex set of challenges in 2026:

• Rising rental costs in prime retail locations
• Intensifying competition from e-commerce platforms
• Labor shortages and rising wages
• Shifting consumer expectations for personalized experiences
• Regulatory compliance in data privacy and digital payments
• Sustainability pressures, including demand for eco-friendly supply chains

These challenges highlight the need for integrated ERP systems that can streamline operations, manage memberships, and provide real-time analytics to support decision-making.

What are the differences between Retail ERP and POS System?

A POS system focuses on front-end sales transactions (billing, payments, receipts), while a Retail ERP system manages the entire back-end business operations (CRM, inventory, accounting, HR, supply chain, etc.). POS is about selling, ERP is about running the business.

Comparison: Retail ERP vs POS System

Risk of sticking with simple yet outdated POS systems

According to Stanley Pang, a veteran ERP expert from Multiable with over 15 years of experience in enterprise management systems, “Retailers who continue to rely solely on outdated POS systems risk falling behind in a rapidly evolving market. These systems may handle daily transactions, but they lack the agility and intelligence needed to respond to modern consumer demands. Without ERP integration, retailers face blind spots in inventory forecasting, membership engagement, and compliance management. The longer businesses delay upgrading, the greater the risk of losing competitiveness and profitability.”

Also read: How the top 10 best HR systems in Singapore reveal the new standards for HR technology

How will Retail ERP benefit Singapore retailers?

Retail ERP helps Singapore retailers by centralizing operations, improving inventory accuracy, enabling omnichannel sales, and enhancing customer experiences. In Singapore’s fast-paced retail market, ERP systems give businesses the agility and insights needed to stay competitive

Benefits of retail ERP for retailers

Why we write this article

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Banks are leveraging GenAI for a variety of uses, from fraud detection to portfolio management, and across various functions from IT to wealth management. McKinsey Global Institute estimates that across the global banking sector, GenAI could add between US$200 billion and US$340 billion in value annually.

The treasury function in banks also stands to benefit from this GenAI wave. The traditional treasury system was designed to provide the treasurer with tools to manage liquidity, funding, and risk. They have faced new and more complex challenges in recent years, such as more volatile financial markets requiring instantaneous liquidity and risk computations, new instruments and markets enabling more complex structures that stress existing treasury system capabilities and innovations which have enabled faster trading and delivery cycles for flow instruments. Today, this treasury system faces another new inflexion point, the rapid rise of GenAI.

Earlier iterations of AI involved pattern recognition and taking over repetitive functions. GenAI, however, introduces levels of cognition and intelligence that can comprehend context, analyse complex data, and support instantaneous, data-driven decision making. This evolution, known as agentic AI, heralds a new milestone in treasury management. Much like how electronic trading transformed market execution, blockchain revolutionised payments, and the cloud redefined operational agility across technology stacks, GenAI is poised to become a strategic partner for the modern treasury function.

From automation to augmentation

The traditional treasury management system has automated the fundamental functions of a treasury. These include tracking positions and limits during trading hours, executing payments, aggregating balances, and reconciling transactions. GenAI takes these activities to a new level. By deriving insights from structured and unstructured data across multiple systems, GenAI helps treasurers interpret dynamic market fluctuations, assess liquidity exposures, or forecast funding needs in real time.

Instead of making sense of dashboards or spreadsheets, a treasurer could simply input the following question into a GenAI-powered LLM platform – “How would a 25-basis-point rate cut impact my short-term liquidity position?”, and receive an instant, data-driven response. In this, GenAI evolves the treasury system from a technological tool to a trusted strategic advisor able to synthesise information, make tailored recommendations, and even execute routine actions within pre-set risk parameters.

Also Read: 2026’s fintech imperative: Lend responsibly, scale smartly, and build for the long term

An example of GenAI being deployed within a treasury function is Kondor Assistant, an AI-powered chatbot that simplifies complex tasks and enhances user experience by providing intuitive and efficient access to financial data. It helps treasury professionals interact with complex financial data via a seamless and interactive GenAI-powered interface with natural language, simplifying access to insights and generating detailed reports.

Responsible AI for a regulated world

The transformative potential of GenAI within the treasury function comes with an equally important responsibility: to build and deploy it safely. Treasury operates within one of the most tightly regulated environments in BFSI, where data privacy, compliance, and operational resilience are paramount.

GenAI systems must adhere to stringent governance, transparency, and security frameworks. Every AI-generated insight must be explainable; every data access must be authorised and auditable. Treasury functions looking to deploy GenAI must ensure that data privacy controls, human oversight, and compliance-by-design principles are baked into every stage of development and eventual deployment.

Regulators in the region are already cognisant of this. The Monetary Authority of Singapore (MAS) has undertaken Project Mindforge to examine risks associated with AI, and developed a toolkit to promote the fair, ethical, accountable and transparent use of AI in Singapore’s financial sector. Hong Kong’s Financial Services and Treasury Bureau (FSTB) also laid out guidelines when it comes to BFSIs deploying AI. Against the backdrop of these regulations, treasury teams must ensure their deployments are adherent to them.

Also Read: Why fintech companies should learn about customer retention from e-commerce companies

The treasury function’s new paradigm

GenAI is a game-changer in how treasurers manage complexity. As agentic AI systems mature, they are increasingly embedded across the treasury value chain, from cash and liquidity management to risk analytics and regulatory reporting.

It enables the sales trader to understand their customer better and manage order flows. The risk manager can focus on the limit exceptions and alerts identified by their assistant rather than trawling through reams of data. The operations user is able to quickly make sense of a complex trade record.

GenAI is more than automating treasury; it is augmenting it. The future belongs to treasurers who see AI not as a back-office tool but a strategic extension of their team. GenAI could help set treasury functions on a path toward a more intelligent, responsible, and proactive style of treasury management.

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Artificial intelligence has redefined productivity everywhere, and Southeast Asia has embraced it with exceptional speed. From Singapore’s National AI Strategy 2.0 to big digital pushes in Malaysia and Vietnam, the region is showing what’s possible when governments, companies, and everyday people leverage AI, instead of avoiding it.

While that traction is encouraging, we’re still thinking about AI through the lens of individual optimisation: write faster, analyse better, build quicker. To realise the region’s full potential, we need to shift our focus beyond just personal productivity to collective creation. 

Collaboration matters more than ever

Innovation is a team sport. The most enduring ideas, from open-source projects to global social platforms, were built by communities that shared knowledge freely. AI should follow that same path.

Today’s systems make it super easy for an individual to generate, automate, and build – but real progress will come from how well we design for shared creativity. As we move toward more collaborative workflows with AI, the goal is to align ownership incentives so that everyone who contributes to an idea shares in the value it creates. To achieve this, we need a transparent set of principles defining who is credited, how rewards are shared, and how human input remains visible even in AI-assisted work.

From solo tools to shared systems

No-code and low-code platforms have opened doors for millions, but they also show the limits of working alone. You can prototype quickly by yourself, but this doesn’t mean the final product will be better. The real progress will happen when AI platforms focus on co-creation instead of just convenience. 

In Southeast Asia, that shift is already underway. Singapore’s National AI Strategy 2.0 promotes cross-sector partnerships that unite government, academia, and industry. Meanwhile, innovation networks and large-scale hackathons in Indonesia, Thailand, and Vietnam are proving that open collaboration drives faster, more inclusive growth. Together, these ecosystems offer a glimpse of what the next evolution of AI could look like: diverse, decentralised, and deeply social.

Also Read: Unchecked shadow AI poses a major cybersecurity risk for 2026: Exabeam

The next wave of progress won’t depend on better algorithms alone; it will hinge on new collaboration models that understand context, intent, and contribution. When incentives are shared, and systems are designed to recognise every input, AI becomes more than a productivity engine; it becomes a medium for creative partnership.

The case for shared credit

AI has become part of workflows in practically every sector, but the real breakthroughs come when ownership encourages participation. Open-source infrastructure like Kubernetes powers vast digital ecosystems, yet the question of ownership remains unresolved.

In this new era, tokenisation and transparent attribution systems could redefine how value flows through creative and technical ecosystems. If the industrial age divided labour to increase efficiency, the AI age must distribute credit to sustain innovation and motivation.

A regional blueprint for collective AI

As Singapore advances its AI governance agenda and neighbouring countries invest in data ecosystems and upskilling, the opportunity before Southeast Asia is clear: to lead the world in building AI that is ethical, inclusive, and collaborative.

The region’s diversity of language, talent, and perspective is its greatest strength. By designing AI systems that reward participation and transparency, Southeast Asia can model a new kind of growth: one where collaboration drives competitiveness. The future won’t be built by AI alone, and it won’t be built by individual brilliance either. It’ll emerge from communities working together, using AI tools to share ideas, track contributions, and distribute credit fairly. 

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In today’s digital-first world, where artificial intelligence (AI) is revolutionising how we live, work and interact, cybersecurity has emerged as a cornerstone of resilience and trust. As organisations accelerate their adoption of AI-driven solutions, they must also fortify their digital perimeters against an evolving and increasingly sophisticated threat landscape.

AI has the potential to unlock transformative growth, streamline operations, and generate predictive insights that drive strategic business decisions. However, these capabilities hinge on the quality, security and governance of data – the very lifeblood of AI systems. Without robust cybersecurity protocols in place, businesses risk compromising not just their data but also the integrity of their AI models and the trust of their users.

At the core of AI lies an insatiable appetite for data sourced from myriad platforms and endpoints. This data trains AI algorithms, enabling them to identify patterns, automate tasks, and deliver actionable insights. Yet, if this data is poorly managed or inadequately protected, AI outcomes can be distorted, biased or downright dangerous.

Andy Ng, Vice-President and Managing Director for Asia South and Pacific region at Veritas Technologies, in his contributed post for e27, emphasises the critical role of automated data management platforms.

“A comprehensive data management system will lay a solid foundation for an effective data-driven decision-making environment,” he says.

Also Read: How Google Cloud is empowering SMBs to build for the future with AI

Sound data management not only fuels AI but also reinforces cybersecurity. Knowing what data you possess, where it resides, and how it is accessed is the first line of defence against breaches and misuse.

The rising tide of AI-focused cyber attacks

As AI adoption grows, so too does its appeal to cybercriminals. The increasing prevalence of proprietary AI models developed by startups has opened a new frontier for cyber threats. Startups are particularly vulnerable, given their limited resources and often immature security infrastructures.

Alvin Toh, a tech entrepreneur with expertise in data governance, highlights in his contributed post the threats such as model extraction and model inversion.

“These techniques allow attackers to replicate or infer sensitive data from AI systems, leading to intellectual property theft and privacy violations,” he explains.

Adversarial attacks, where malicious inputs are designed to deceive AI systems, are also on the rise, posing significant threats to the reliability and integrity of AI outputs.

Without sufficient cybersecurity measures, these threats can derail innovation, erode public trust, and expose organisations to regulatory and reputational risks. It is no longer sufficient to treat cybersecurity as a separate function – it must be embedded at the heart of every AI initiative.

To address these emerging challenges, industry leaders will converge at Echelon Singapore 2025, hosted at Suntec Singapore on June 10-11. One of the most anticipated sessions, titled “Cybersecurity at Core: Building a Resilient and Secure Digital Frontier in the Age of AI,” will take place on Wednesday, June 11, from 11:40 AM to 12:30 PM on the Future Stage.

Also Read: Why MCP is AI’s answer to open-source collaboration

Moderated by Eugene Teo, Chief Security Advisor at Microsoft ASEAN and Co-Chair of the Singapore FAIR Institute Chapter, the panel will feature experts who are actively shaping the future of secure AI:

– Johann Nallathamby, Director – Solutions Architecture, WSO2
– Kumar Ritesh, Founder, Chairman and CEO, CYFIRMA
– Chien-Wei (CW) Chia, Chief of Staff, CyberSG R&D Programme Office

Together, they will explore how organisations can balance innovation with protection, ensure AI model integrity, and implement end-to-end cybersecurity frameworks that align with the demands of the AI era.

Join us at Echelon Singapore 2025 at Suntec Singapore, June 10–11, and be part of the conversation shaping the secure digital frontier of tomorrow. Don’t miss this chance to engage with leading experts, discover innovative solutions, and future-proof your organisation in the age of AI.

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Image Credit: GuerrillaBuzz on Unsplash

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Artificial intelligence isn’t just some far-off concept in marketing anymore; it’s right here, right now, acting as a powerful engine that’s reshaping how we connect, personalise, and make smarter decisions.

As the founder of thirdi.ai, an AI-powered digital marketing solution, I witness every single day how AI can genuinely transform a brand’s ability to build meaningful connections with its audience. But as you probably have already heard from great saints , “with great power comes great responsibility!”

In today’s landscape, I believe it’s crucial for those of us in the AI marketing industry to proactively confront the ethical implications of our work. I’m talking specifically about how we handle privacy, keep data secure, and build something that’s fundamental to any good relationship: user trust.

Let’s be honest, the digital world has seen its share of blunders with data misuse and biased algorithms. This has, understandably, made users more discerning and, frankly, sometimes a bit skeptical.

For AI-led marketing to truly flourish, and for businesses like yours and mine to succeed, I’m convinced we need to navigate this complex “trust labyrinth” with our integrity intact and a genuine commitment to doing the right thing.

The big three: Privacy worries, data security anxieties, and vanishing trust

From my viewpoint, the main ethical headaches in AI marketing boil down to how we collect, use, and protect the data people share with us. Users are savvier than ever about their digital footprint, and they have every right to be concerned about how their information is being used.

Privacy: That tricky balance with personalisation 

AI is fantastic at creating those “wow” hyper-personalised experiences. I’ve seen it analyse mountains of data to understand what makes individuals tick, anticipate what they might need next, and deliver content that really resonates. The ethical tightrope we walk is ensuring this personalisation doesn’t feel like an invasion of privacy.

For me, it all boils down to being upfront and getting clear consent. Are we truly telling users, in plain language, what data we’re collecting and how it’s going to make their experience better? Are we giving them real control, a straightforward way to opt-out if they want to, without making them jump through hoops?

Also Read: Women and AI: How startups can prevent gender bias and promote responsible use of the tech

I’ve seen the backlash when companies aren’t transparent – like when AI-generated content pops up unannounced or it’s murky how user data is training AI models.

It’s a clear signal: people want honesty. As marketers, my belief is that our drive for relevance should never bulldoze someone’s right to privacy. This means we need to ditch the dense, jargon-filled privacy policies and opt for clear, easy-to-find explanations.

Data security: This one’s non-negotiable for me 

The more data our AI systems handle, the juicier a target they become for cybercriminals. A data breach isn’t just a technical issue; it can expose sensitive user information, leading to real-world harm like financial loss or identity theft. More than that, it absolutely demolishes user trust, and rebuilding that? It’s a monumental task.

That’s why I vote for robust data security – things like top-notch encryption, regular security check-ups, and ingraining “privacy by design” in everything we build – as fundamental duties, not just optional extras.

At thirdi.ai, protecting our clients’ data, and by extension, their customers’ data, is a top priority. For us, this means constantly investing in our security and strictly following data protection laws like GDPR, CCPA, and here in Singapore, the PDPA.

My advice to any business using AI marketing tools is to be really demanding about security standards from your vendors and always be open with your customers about how you’re protecting their information.

User trust: The real currency in today’s digital world

In hindsight, privacy and data security are the building blocks of user trust. And trust, in my book, is the most valuable currency we have. It’s not something you get automatically; you earn it, bit by bit, through consistent, ethical actions.

When people feel their data is being handled with respect and that AI is there to offer real value, not to trick or exploit them, they’re much more likely to engage with a brand. But if there’s even a whiff of shady data practices or AI making decisions behind a curtain of secrecy, you can bet they’ll walk away, and your brand will suffer.

Building that trust, from my experience, takes a few key things:

• Be open: Tell people clearly when and how AI is involved.
• Be accountable: We need clear ownership for our AI systems. If an AI messes up or shows bias, we need to have ways to make it right.
• Strive for fairness: We must actively work to reduce bias in our AI. Biased data can lead to unfair outcomes in how ads are targeted or what content people see, and that can just reinforce existing societal problems. Regularly checking our AI models for fairness is something I insist on.
• Keep humans in the loop: AI is great for automating tasks, but I firmly believe that keeping human oversight, especially in sensitive situations, is crucial. This ensures that ethical thinking is baked into our AI marketing, not just sprinkled on as an afterthought.

The way I see it: Ethical AI can be your edge

Tackling these ethical issues isn’t just about staying out of trouble or ticking compliance boxes. I genuinely believe it’s about building a digital marketing world that’s sustainable and that people can trust. As founders and marketers, we have a real chance here to make ethical AI practices a cornerstone of what makes us different and better.

At thirdi.ai, we’re building our platform on the conviction that responsible AI is the only path forward. For us, this means weaving ethical thinking into everything we do – from our data protocols and how our algorithms are designed, to the advice we give our clients.

Also Read: How to navigate the ethical landscape of responsible AI

If I could offer a few key takeaways for businesses, they would be:

• Get smart, and get your team smart: Really understand the ethical side of the AI tools you’re using. Build a culture where data responsibility is everyone’s business.
• Ask the tough questions of your AI vendors: Don’t be shy. Ask where their data comes from, how their models are trained, and what they’re doing about bias.
• Put users in control: Make it super easy for people to understand and manage their data preferences.
• Double down on security and privacy: Treat user data like the precious asset it is.
• Keep the conversation going: Listen to what users are worried about and be ready to adapt.

The future of AI in marketing? 

I’m incredibly optimistic about it. It promises amazing new ways to engage and be effective. But we’ll only get to that bright future if we all commit, right now, to navigating the ethical terrain with care and integrity.

By truly valuing privacy, locking down data security, and working tirelessly to earn and keep user trust, we can make sure AI-powered marketing is a win-win – great for businesses and great for the people we serve. This way, we establish ourselves not just as innovators, but as partners people can genuinely trust in this digital age.

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For forty years, trade shows were the arteries of globalisation — bustling marketplaces where buyers met sellers, deals were signed, and industries displayed their innovations. Today, those arteries are being rerouted.

The world is fracturing into competing economic and political blocs. The U.S.–China rivalry has intensified into a systemic decoupling; sanctions and tariffs have become strategic weapons. For global businesses, the cost of being on the wrong side of this divide can be enormous — from disrupted supply chains to sudden loss of markets.

Amid this turbulence, trade shows are transforming. No longer just venues for commerce, they are becoming strategic intelligence hubs — places where industries decode policy shifts, negotiate new partnerships, and rewire global supply routes. The question is no longer whether trade shows will survive, but which will evolve fast enough to lead in this new era.

The shift: From foot traffic to trust

Traditional measures of success — exhibitor counts, floor space, visitor numbers — now look outdated. What participants crave isn’t more bodies in the hall, but more intelligence in the room.

Three forces are driving this transformation:

• Geopolitics redefining trade routes

Tariff realignments and policy-driven industrial strategies are reshaping the flow of goods, ideas, and capital. Companies are relocating production for resilience, not just cost efficiency. This has created a new kind of demand at trade shows — not just for products, but for insight into where the next supply chain corridor will open.

Trade shows now double as policy classrooms: regional briefings on tariffs, compliance workshops, and strategic matchmaking sessions are replacing cocktail parties and badge scans. Exhibitors increasingly treat events as part of their risk-mitigation strategy, not just marketing spend.

• The rise of the trust economy

In a polarised world, trust has become the scarcest commodity. Buyers and suppliers must verify each other’s credibility, transparency, and sanction exposure. The most valuable trade shows are now those that function as trust filters — with vetted exhibitors, verified sourcing, and curated introductions.

The first question asked at the booth is no longer “What’s your price?” but “Are you geopolitically safe?”

• Intentionality replacing hope

Gone are the days when companies said, “We’ll go and see who we meet.” Travel budgets and board scrutiny demand outcomes, not anecdotes. Modern attendees arrive with data-driven objectives: who to meet, what insight to gather, and which alliances to explore. Leading shows now deploy AI-powered matchmaking and “meeting intelligence” tools to curate purposeful encounters.

Events as economic infrastructure

Trade shows have evolved from temporary gatherings into critical components of economic infrastructure. They now serve as the convening points where industries realign, build trust, and negotiate the future.

Key trends shaping this new infrastructure include:

• Economic intelligence environments: Events that blend commercial exchange with policy interpretation — decoding trade rules and regional shifts in real time.
• Relationship intelligence over volume metrics: Platforms that measure success not in visitors, but in verified partnerships and supply chain continuity.
• Regional trade clusters: Shows anchored around “trust corridors” — zones of mutual reliability and shared regulatory standards — rather than sheer global reach.

The model is shifting from “Go global” to “Go strategic.” The winning events will be those that enable companies to reconfigure themselves for resilience, not just visibility.

Also Read: Mastering sustainability: Your ultimate guide to hosting eco-friendly events in Asia

The ASEAN advantage: A new neutral ground

If the world’s trade map is being redrawn, ASEAN sits at its geographic and strategic crossroads.

The 10-nation bloc has emerged as the world’s most important “neutral zone” — trading actively with both the U.S. and China and benefiting from its inclusion in multiple free trade frameworks, such as the Regional Comprehensive Economic Partnership (RCEP).

In 2023 alone, ASEAN attracted USD 229 billion in foreign investment —roughly 17 per cent of global FDI —and became China’s largest trading partner. Equally significant, it is one of the few regions trading more with both superpowers simultaneously.

Why ASEAN works as a hub

• Geoeconomic neutrality: It does not force global firms to pick sides, giving them flexibility.
• Tariff resilience: US tariffs on ASEAN goods average below those on Canada or Mexico.
• Supply chain depth: ASEAN countries now handle everything from electronics (Malaysia) to EVs (Thailand, Indonesia) and logistics (Singapore).
• Connectivity: Singapore and Malaysia’s ports and airports are among the most efficient globally, while Vietnam and Indonesia are scaling fast.

These factors make ASEAN’s cities — Singapore, Bangkok, Kuala Lumpur, Ho Chi Minh City, and Jakarta — the new strategic bases for trade exhibitions. Attending an ASEAN show today is less about marketing reach and more about supply chain positioning.

Trade shows in the region have responded accordingly: offering policy briefings, factory visits, tariff workshops, and matchmaking with regional manufacturers. Exhibitors are asking not “How big is the crowd?” but “How geopolitically safe is this market?”

Beyond ASEAN: Indian Ocean contenders

• Mauritius: The ready neutral

Mauritius has quietly built the infrastructure and institutions to serve as the Indian Ocean’s Singapore. With a stable democracy, robust financial services ecosystem, and five undersea data cables, it is ready to host boardroom-grade trade and policy summits linking Africa and Asia.

Its Freeport logistics hub, investor-friendly laws, and new digital government blueprint make it ideal for trust-based, intelligence-rich conferences — particularly in finance, fintech, climate, and technology.

• Madagascar: The emerging corridor

Madagascar, strategically positioned on the Mozambique Channel, is poised for relevance. Port expansions at Toamasina and Fort Dauphin, alongside critical battery-mineral projects such as Ambatovy, could anchor resource- and logistics-focused trade shows.

If governance and infrastructure improve, Madagascar could become a powerful partner hub to Mauritius — pairing a policy-safe capital with a resource-rich hinterland for the Indian Ocean Region.

Together, they form a “twin-hub” model for Africa–Asia connectivity — mirroring how ASEAN connects East and West.

Also Read: ‘Tis the season to be shopping: Can businesses still capitalise on sales events in APAC?

Technology as survival: The case for AI-driven horizon scanning

To stay relevant, trade show organisers must become intelligence organisations themselves. In today’s volatile environment, AI-driven Tech Watch Horizon Scan (TWHS) systems are no longer optional. What TWHS does:

• Anticipates geopolitical shocks: AI monitors trade data, policy drafts, and sanctions chatter to flag early warning signs — enabling event planners to pivot topics or locations in advance.
• Identifies emerging sectors: Horizon scanning reveals where investment is flowing (e.g., EV supply chains in Thailand or semiconductors in Malaysia), guiding new event themes and partnerships.
• Curates forward-looking content: Scanning patent databases and academic papers highlights upcoming technologies to feature on the expo floor — from hydrogen to quantum computing.
• Enhances risk management: Predictive analytics can assess climate risks, unrest, or travel disruptions that might impact attendance.

In short, TWHS transforms organisers from reactive planners into strategic forecasters, ensuring their events remain indispensable to industries navigating change.

Where the next global hubs will rise

The future belongs to neutral, digitally fluent, and geopolitically stable hubs that can attract all sides of the global economy.

Leading the pack

• Singapore remains the gold standard — neutral, hyper-connected, and digitally advanced. Its trade shows increasingly blend thought leadership with deal-making.
• Dubai and Abu Dhabi serve as West–East bridges, hosting over 130 major events in 2025 across sectors from tech to logistics.
• Bangkok, Kuala Lumpur, Jakarta, Ho Chi Minh City — rising ASEAN hubs with growing infrastructure and sector specialisation (EVs, electronics, agri-tech).

Fast followers

• India’s metros (Bangalore, Mumbai, New Delhi): Combining scale, digital infrastructure, and policy ambition, they are fast becoming alternative hosts for multipolar trade.
• Geneva and Brussels: Remaining vital to global policy and standards forums, especially where government and industry intersect.
• Kigali and Astana: Emerging as new neutral conveners for South–South and Eurasian trade dialogues.

These cities share one crucial attribute: trust combined with connectivity. In a world of polarised alliances, they offer the rare promise of a level playing field.

Short-term outlook: 2024–2026

In the next two years, several developments are likely:

• ASEAN-centric expansion: More global fairs will move or launch editions in Southeast Asia, especially Singapore, Vietnam, and Thailand.
• Security and compliance by design: Events will build in sanctions checks, data privacy protections, and cyber-secure apps.
• Thought leadership integration: Expect every major exhibition to include a high-level policy forum component.
• Digital continuity: Hybrid participation, AI-driven matchmaking, and year-round online communities will become standard.
• Government incentives: Expect cities to compete fiercely for hosting rights, offering tax breaks, visa waivers, and digital trade facilitation schemes.

These trends point to one conclusion: trade shows are no longer short-term marketing events — they are policy instruments and economic accelerators.

The long view: What the 2030s could bring

Beyond 2027, several deeper trends could take hold:

• Parallel event ecosystems: Distinct “Western” and “Eastern” trade show circuits may form, meeting only in neutral zones like ASEAN or the Gulf.
• Mega-platforms: Fewer but larger cross-sector summits combining trade, technology, and policy.
• Sustainability mandate: Carbon-neutral exhibitions and green supply chain showcases as standard.
• Permanent hybridisation: 24/7 digital trade platforms supplementing periodic physical events.
• Personalised AI experiences: Intelligent assistants scheduling meetings and compiling insights for every delegate.

By the 2030s, attending a trade show may feel like entering a living network of global commerce — powered by data, trust, and cross-border collaboration.

Also Read: Why businesses need to rethink ‘black swan events’ to succeed in 2024

Recommendations for stakeholders

For organisers

• Evolve from event management to strategic intelligence delivery.
• Build AI-driven tech watch capabilities.
• Curate verified, trust-based exhibitor ecosystems.
• Offer data-rich, outcome-driven engagement — before, during, and after the show.

For policymakers

• Treat trade shows as economic infrastructure, not tourism.
• Invest in neutral, high-tech venues and digital trade facilitation.
• Use events as platforms for diplomacy and regional cooperation.
• Enable frictionless travel, data exchange, and cross-border logistics.

For businesses

• Integrate event participation into supply chain and geopolitical strategy.
• Send multi-functional teams (sales, compliance, and intelligence).
• Measure ROI not just in leads, but in strategic insights and alliances.
• Use trade shows as scouting missions for suppliers, technologies, and risk signals.

Conclusion: From exhibition floors to strategy tables

Trade shows and conferences are entering their most transformative era in forty years. As globalisation splinters into overlapping networks of trust, resilience, and ideology, events have become the connective tissue of a fractured world.

They are no longer mere showcases of products — they are operating systems for global commerce. The new generation of trade shows will not just reflect the world’s divisions; they will help bridge them.

For organisers, policymakers, and corporations alike, this is not a time to react — it is a time to lead. The Great Realignment is here, and the trade shows that embrace intelligence, neutrality, and trust will define the next decade of global business.

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