In this interview, e27 speaks with Eric about the Asia AI Association’s work in advancing AI innovation, professional collaboration, and ethical adoption across Asia, as well as how organisations can approach AI transformation responsibly.

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.

Fostering AI innovation, networking, and ethics across Asia

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

Eric: Fostering AI Innovation, Networking and Ethics Across Asia Promoting technological advancement in Artificial Intelligence, facilitating professional connections, and championing ethical practices in Asia

1. Professional Development – Gain access to educational resources, career advancement programs, skill development training, and expert consultancy to boost your AI career.
2. Networking and Collaboration – Connect diverse communities of AI professionals, academics, and enthusiasts for collaborative research, and events.
3. Industry and Ethical Insights – Stay updated on AI trends, technologies, and best practices while engaging in discussions about interdisciplinary applications and ethics.

Promoting AI adoption through collaboration

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

Eric: As a business association focused on AI, AAIA connects with corporations, individual professionals, and business networks to provide training, knowledge-exchange platforms, workshops, and hackathons—promoting how AI can benefit everyone.

The rapid advancement of Artificial Intelligence (AI) has reshaped industries, revolutionized workflows, and transformed the way we interact with technology. With AI-powered automation, machine learning, and generative models now performing tasks once reserved for human expertise, many professionals fear being replaced by intelligent systems. However, while AI significantly enhances efficiency, it lacks the deeper capabilities of Human Intelligence (HI)—such as intuition, creativity, critical thinking, and emotional intelligence.

This is where AAIA comes in: to guide innovation through deeply human collaboration with technology. AI on its own is powerful; AI guided by empathy, ethics, and human creativity is transformative. This is the role of Human Intelligence (HI) that we advocate and champion.

Navigating organisational change in AI transformation

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

Eric: As a business association serving our members, the general public, business networks, and the public sector, we recognise that change is often painful—but it is also inevitable. One example is a technology member of ours who spent over 90% of the engagement working closely with a local clinic chain on its AI transformation, converting manual bookkeeping and accounting processes into automated workflows. The key hurdles for the client were:

1. Clearly understanding and accurately presenting existing processes; and
2. Adapting to new AI-assisted workflows and embracing the discomfort that comes with change.

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

Rising awareness alongside cautious adoption

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

Eric: Public awareness of AI is improving rapidly, and adoption is happening faster than ever before. However, most people still treat AI merely as a tool—some embrace it enthusiastically, while many remain cautious or even fearful. Few have fully considered how AI-driven transformation can fundamentally improve and reshape the way we live, work, and make decisions in our daily lives.

The underestimated effort behind AI transformation

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

Eric: Leaders and founders often underestimate the effort, time, and resources required for meaningful transformation. While many existing business processes may appear to function adequately, they are frequently ambiguous or messy beneath the surface. Converting these informal processes into structured workflows or systems requires first making the situation transparent, then introducing new ways of working—both of which take time, alignment, and patience to “clear the air” before real progress can happen.

Communication as the foundation for AI adoption

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

Eric: A practical recommendation for organisations that are just beginning to explore—or looking to scale—AI adoption is to prioritise communication above all else. Effective communication must happen at every level and in every form: from strategic planning and leadership alignment, to clear documentation of existing and future processes, and down to day-to-day verbal conversations across teams.

AI transformation is not purely a technology exercise; it is a shared understanding exercise. When goals, assumptions, workflows, and expectations are communicated clearly, organisations can surface ambiguities early, reduce resistance, and align people around a common direction. This clarity makes it far easier to redesign processes, adopt AI-assisted workflows, and move toward the intended outcomes with less friction and fewer costly detours.

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

Continuing the AI plus human intelligence approach

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?

Eric: Continue to roll out the AI + HI (Human Intelligence) program to aid the industry to improve with human touch.

Invitation to engage with the AI community

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

Eric: Readers are encouraged to join our events & as members.

Human intelligence in the AI era

This conversation highlights the growing importance of keeping AI development grounded in human judgment, ethics, and collaboration as adoption accelerates across industries. As organisations move from experimentation to real-world deployment, initiatives that prioritise professional education, responsible innovation, and interdisciplinary dialogue will play a key role in ensuring AI strengthens human capability rather than replacing it.

For more interviews, analysis, and real-world perspectives on how organisations across the region are applying AI in practice, subscribe to our newsletter. You can also explore more AI stories 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: 1SeeThrough

The post AI Pulse Exclusive: How Asia AI Association is advancing human-centred AI across the region appeared first on e27.

For centuries, government has often been seen as a slow, reactive bureaucracy. Citizens fill out forms, wait in lines, and hope for a response. Artificial Intelligence (AI) is beginning to change this in a fundamental way, enabling a shift from a government that reacts to problems to one that anticipates needs.

Think of it like managing a city bridge. The old way was to wait for cracks to appear or, worse, for the bridge to fail, and then scramble to make repairs. The new, AI-driven approach is to use sensors and predictive models to understand the bridge’s structural stress in real-time, allowing engineers to prevent the failure before it ever happens.

This shift is more than just a technological upgrade; it’s a redefinition of the social contract. As decisions about benefits, health, and safety move from human clerks to algorithms, the relationship between the citizen and the state is fundamentally changing.

This is the promise of AI in government: to build a more proactive, personalised, and efficient state that can forecast health crises, disburse benefits to those in need without lengthy applications, and optimise city traffic dynamically. This document will explore what “AI” really is, see how it’s being used to remake key public services, and understand the critical challenges we must address, all based on insights from the “Tools to build an AI state” report.

What exactly is the ‘AI’ in government? A simple toolkit

“Artificial Intelligence” isn’t a single technology; it’s a collection of tools. Just as a mechanic has different tools for different jobs, governments use various types of AI to solve specific problems. The table below introduces three of the most common AI technologies used in public services.

Now that we understand the basic tools in the government’s AI toolkit, let’s explore how they are being applied to improve the services that impact our daily lives.

Also Read: A new ocean order: What startups and investors need to know about the High Seas Treaty

How AI is remaking public services: Three key examples

This transformation of the social contract is not abstract; it’s happening now in the public services that define our daily lives. From the classroom to the hospital to the daily commute, AI is being applied to fulfil the state’s core promises more effectively.

Here are three key examples.

• Education: From standardised lessons to personalised learning

The traditional challenge in education has always been the “one-size-fits-all” model, where a single teacher must try to meet the diverse needs of a large classroom. AI’s primary promise is to make learning adaptive and personalised for every student.

• AI-driven tutoring: Platforms like Squirrel AI in China provide millions of students with tutoring that adjusts the difficulty of lessons in real-time based on their performance, acting like a personal tutor for each child.
• Smarter teacher tools: AI can automate routine tasks like grading assignments and generating lesson materials aligned with national curricula, providing teachers with detailed analytics on student progress. This frees up teachers’ time to focus on what matters most: mentoring and providing personal support to their students.
• Building economic pathways: AI is not just for children. Platforms like Singapore’s SkillsFuture use AI to analyse labour market trends and guide adult workers toward in-demand skills and jobs, strengthening the promise of lifelong economic opportunity.

Just as AI can tailor a student’s education, it is also beginning to personalise healthcare from the moment a person seeks care.

• Healthcare: From treating sickness to predicting it

Healthcare systems worldwide are strained by rising costs and a focus on treating people only after they get sick. AI is playing a central role in shifting this focus from treatment to anticipation, making public health more predictive and preventive.

• Faster, more accurate diagnosis: Computer vision algorithms can analyse medical images like X-rays and MRIs with incredible speed and accuracy. These systems can identify anomalies in seconds, flagging risks that allow for intervention before a crisis occurs and leading to better patient outcomes.
• Predicting health crises: During the COVID-19 pandemic, AI-driven epidemiological models helped governments predict where outbreaks would occur, allowing them to allocate resources more effectively. Beyond pandemics, these models can analyse health records to flag patients at high risk of conditions like sepsis, allowing hospitals to intervene preventatively.

While AI’s impact on personal health is profound, its ability to analyse and optimise large, complex systems is also reshaping the public infrastructure we all share, starting with our transport networks.

• Transport: From traffic jams to smart traffic flow

Every city dweller is familiar with the frustration of traffic congestion, transit delays, and infrastructure failures. By analysing vast amounts of real-time data, AI is helping make transport systems adaptive and predictive, smoothing out the flow of people and goods.

• Dubai’s smart traffic signals: In Dubai, AI-powered traffic lights respond dynamically to real-time traffic conditions. Instead of following a fixed schedule, they adjust their timing to reduce congestion and cut down on waiting times for drivers.
• China’s city brain: This massive platform, developed by Alibaba, analyses city-wide data from cameras, GPS, and public transit. It orchestrates traffic flow across entire districts, dramatically cutting response times for emergency vehicles by minutes that can save lives.

These examples show a future of exciting possibilities, but this progress also comes with significant challenges and questions that society must carefully address.

Also Read: Asia rises in the AI chip race: China to outgrow US by 30 per cent by 2030

The Big questions: Balancing progress with people

Deploying this technology responsibly requires confronting the profound governance challenges it creates. While the benefits are clear, AI’s use in the public sector forces us to ask critical questions about fairness, accountability, and our fundamental rights.

• Is it fair? The challenge of bias

AI systems learn from the data they are given. If that data reflects historical human biases, the AI can learn and even amplify those same prejudices. For example, a predictive policing model trained on biased arrest records could unfairly target a community that was already over-policed, creating a vicious cycle of discrimination.

• Who’s in charge? The accountability problem

Many advanced AI systems are a “black box,” meaning it can be difficult, even for their creators, to understand exactly why they made a specific decision. This raises a critical question: if an algorithm wrongfully denies a person welfare benefits or flags them as a risk, who is accountable for the mistake?

• Are we being watched? The privacy puzzle

To work effectively, AI often requires vast amounts of data about citizens, from their health records to their daily travel patterns. This creates a fundamental trade-off, raising serious concerns about the potential for government surveillance and the protection of personal privacy.

Conclusion: Governing wiser, not just faster

Artificial Intelligence is clearly more than just a new technology; it is a powerful force that is reshaping the relationship between citizens and the state. It offers the tools to build a government that is not only faster and more efficient but also more proactive and personalised.

However, the true measure of success for AI in government will not be speed or cost savings alone. It will be whether these tools are used to strengthen the social contract by making governance more transparent, inclusive, and trustworthy.

The goal is not simply to adopt AI the fastest, but to integrate it wisely, ensuring that this powerful wave of technological innovation is carefully aligned with our democratic values and the public’s trust.

Watch this space for a follow-up article for a deeper dive into AI applications in Government, and where opportunities lie for startups and investors.

A comprehensive analysis, “Tools to Deliver The AI State – a Technology Watch and Horizon Scan”, is available here.

You can also find me on my podcast and newsletter, where I share regular insights on geopolitics and leadership.

—

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 generated using AI.

The post AI in action: How governments are using technology to predict, prevent, and personalise appeared first on e27.

Over the past few years, I’ve come to genuinely admire how far Apple and Google have pushed the world toward stronger privacy and security.

Their efforts have not only reshaped user expectations but also forced the entire tech industry to rethink how data is handled, stored, and protected. Their frameworks — from Apple’s App Tracking Transparency to Google’s Privacy Sandbox — have raised the bar for what users expect in terms of trust and control.

These frameworks didn’t just appear overnight; they were the result of years of advocacy, user demand, and a growing recognition that privacy is not a luxury but a necessity in the digital age.

But as someone working in privacy-preserving AI, I’ve also seen the other side of this progress: access. This is where the narrative gets complicated. While these safeguards are undeniably beneficial for users, they also create an unintended consequence: they can stifle the very innovation that aims to enhance privacy further.

The paradox of privacy

Every new safeguard limits who can access sensitive device signals — including notifications, app usage, and network patterns. That’s good for users. After all, no one wants their personal data to be exploited or mishandled. These protections ensure that users have more control over their digital footprints, which is a significant step forward in an era where data breaches and misuse are all too common.

Yet, in practice, these restrictions mean the same companies that set the rules also keep privileged access for themselves. This creates a dynamic where only a handful of players—those with the resources and influence to shape these frameworks—can fully leverage the data they collect. Smaller players, even those with innovative solutions, are often left on the sidelines, struggling to gain the access they need to prove their concepts.

Also Read: How to build customer trust with improved data privacy

Independent innovators — the ones building privacy-enhancing technologies that never move or expose data — often can’t even demonstrate their models because the APIs are closed. This is particularly frustrating because these innovators are often the ones pushing the boundaries of what’s possible in privacy-preserving tech. Without access to the necessary tools and data, their potential contributions remain untapped.

It’s a strange paradox: we protect privacy by preventing the very people designing privacy-safe systems from proving their value. In essence, we’re creating a system where privacy is protected, but only for those who already have power. The innovators who could help democratise privacy are left struggling to gain a foothold.

The bigger picture

Regulators have started to notice this imbalance. Regulators have started to notice this imbalance. This is a positive sign, as it indicates that the conversation around privacy is evolving beyond just protection to include fairness and accessibility.

• The EU Digital Markets Act (DMA) now classifies large platform owners as “gatekeepers” who must support interoperability and fair access to the data business users generate.
• Singapore’s PDPA and AI Governance Framework name Federated Learning, Multi-Party Computation, and Differential Privacy as key enablers of responsible data use.
• Global standards bodies such as OECD and NIST are defining what trustworthy privacy-preserving collaboration looks like.

These developments aren’t about punishing Big Tech. Rather, they’re about creating a more equitable digital ecosystem where innovation isn’t stifled by monopolistic practices. They’re about ensuring that privacy doesn’t become a monopoly, reserved only for those who own the operating system. The goal is to foster an environment where privacy is a shared responsibility, not a privilege reserved for a select few.

Also Read: How to unlock possibilities through data privacy enhancing technologies

A personal reflection

I don’t write this to criticise Apple or Google; their leadership in privacy has influenced how users perceive digital trust. In fact, their contributions have been instrumental in shifting the industry toward a more user-centric approach to data privacy. Without their efforts, we might still be in a world where user data is treated as a commodity rather than a right.

However, progress in technology should be inclusive, not exclusive. Inclusivity in this context means ensuring that the tools and frameworks designed to protect privacy are accessible to all innovators, not just those who already have a seat at the table. If we truly believe that privacy is a universal right, then access—guided by transparency and compliance, not control—must be part of that vision.

Because privacy shouldn’t be a privilege, it should be a fundamental right that is accessible to everyone, regardless of their size or resources. It should be the foundation on which fair innovation is built.

—

The post When privacy becomes a privilege: Balancing user protection with fair access for innovators appeared first on e27.

Farming practices across Asia face mounting pressure to increase output while reducing environmental damage. For BioArk, a Singapore-based agritech company, this challenge is a starting point for rethinking how fertilisers are made, applied, and integrated into existing systems without demanding costly changes from farmers.

Rather than focusing on history or legacy methods, BioArk’s team develops bio-based fertilisers that compete directly with conventional chemical inputs.

“Our goal is to provide a like-for-like substitute,” says Jeremy Chua, BioArk’s CTO and co-founder, in an email to e27. “One that performs as well, costs comparably, and doesn’t require farmers to rework their operations.”

Its flagship product, Arktivate, is positioned as an interchangeable input that delivers immediate results while improving soil conditions over time. The company frames this as part of a broader “symbiotic ecosystem” approach, blending ecological processes with applied science to produce measurable outcomes in crop yields, soil health and environmental impact.

Key to BioArk’s development philosophy is the view that plant health cannot be separated from environmental health.

“Nature manages nutrient cycling and biodiversity without external inputs,” says Chua. “We try to understand how that works, identify the underlying scientific principles, and build those into our product designs.”

Also Read: You are what you eat: Opportunities in Southeast Asia’s agri-food sector

This involves using biotechnology processes to incorporate sustainably sourced organic inputs. The aim is to enhance the availability and uptake of nutrients while supporting the surrounding soil microbiome. According to the company, field tests show that these fertilisers can match or outperform traditional inputs while reducing reliance on fossil fuel–based products like urea or mined resources such as phosphate and potash.

The company also points to early evidence suggesting that every tonne of its fertiliser used may help store about 0.5 tonnes of CO₂ equivalent annually through improved soil biology. While this data is still being validated, it speaks to a wider goal: to enable farming methods that are economically viable while contributing to climate mitigation and ecosystem regeneration.

Growth strategy

BioArk is currently focusing on expansion in Indonesia and is exploring similar opportunities across key Southeast Asian agricultural markets. Countries such as Vietnam, Thailand and the Philippines are particularly interesting, given their high food production levels and vulnerability to environmental degradation.

The company’s strategy involves close collaboration with local farming communities to adapt its products to specific soil conditions and crop types. In practice, this includes on-the-ground demonstrations, training sessions and ongoing agronomic support. This approach is intended to reduce barriers to adoption and ensure compatibility with existing agricultural practices.

Also Read: Singapore anchors inaugural ClimAccelerator for agritech startups in APAC

The decision to avoid requiring major behavioural shifts reflects one of the company’s core assumptions: that new tools for sustainable agriculture must be easy to use, or risk being ignored altogether. Many of today’s alternatives—such as organic farming or precision agriculture—offer environmental benefits but often require significant capital investment or operational changes.

“Inertia is a real issue,” Chua says. “If we want widespread change, solutions must fit into current systems, not expect systems to change first.”

BioArk’s approach also reflects broader shifts in how agricultural innovation is pursued, particularly in urban hubs such as Singapore. As a regional centre for agri-food research, the city-state has provided BioArk access to government-backed R&D facilities, startup support networks and policy frameworks that prioritise sustainability.

Partnerships with local agencies, including Enterprise Singapore (ESG), have supported BioArk’s product development and helped position its technology for international deployment. Chua says this environment has allowed the team to quickly iterate and validate its fertilisers before scaling into wider markets.

Looking forward, BioArk aims to expand its manufacturing capacity, extend field trials across Asia and forge new partnerships to accelerate adoption. Its long-term objective is to reduce the agricultural sector’s reliance on synthetic fertilisers while contributing to improved soil resilience and carbon storage.

“Our focus is on scaling what works—environmentally, scientifically and economically,” Chua says. “Not in isolation, but in partnership with the growers who work the land every day.”

—

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

Image Credit: BioArk

The post BioArk’s growth strategy plants seeds for a greener agricultural future appeared first on e27.

In a powerful demonstration of purpose-driven innovation, Indonesian agritech company Elevarm has unveiled its 2024 Impact Report, shedding light on its transformative contributions to the nation’s horticulture sector. The report outlines how Elevarm’s integrated ecosystem model is revolutionising farming practices, improving farmer livelihoods, and advancing sustainable agriculture across the archipelago.

“Indonesia’s food security depends on empowering farmers with the right tools, knowledge, and support,” says Bayu Syerli Rachmat, co-founder and CEO of Elevarm, in a press statement. “By directly addressing sustainability at the grassroots level, Elevarm is proud to help close the productivity gap while protecting the environment.”

In 2024, Elevarm supported more than 16,000 smallholder farmers. These farmers experienced a remarkable transformation, with 36.5 per cent reporting increased yields and average incomes rising from IDR12.1 million (US$735) to IDR14.1 million (US$857) per crop cycle.

Beyond financial gains, farmers saw a 14 per cent reduction in chemical usage, thanks to Elevarm’s organic solutions such as vermicompost, produced and distributed in-house.

At the core of Elevarm’s achievements lies its integrated ecosystem service model, designed to create “triple wins”: boosting livelihoods, enhancing food security, and strengthening environmental resilience. Through a blend of advanced technology, tailored financing, market infrastructure, and advisory services, Elevarm addresses systemic challenges in Indonesian agriculture.

Also Read: Unlocking agritech’s potential: Can Southeast Asia rise to the challenge?

Tech-driven cultivation support

Elevarm leverages cutting-edge tech to deliver tailored cultivation practices. Farmers are equipped with high-quality inputs, including seeds, organic fertilisers, and biostimulants. The company also employs tech-driven solutions such as soil testing, monitoring dashboards, IoT-based field devices, and a dedicated farmer app that offers real-time insights and personalised guidance.

Addressing one of smallholder farmers’ most significant barriers, Elevarm provides affordable loans tied to harvest repayment. This financial support covers an average of 62.5 per cent of farmers’ working capital needs, reducing dependence on informal lending channels.

Moreover, crop and life insurance options protect farmers from risks associated with climate events, pests, and unforeseen personal tragedies. By shifting reliance away from informal lending, the company intends to help farmers gain financial stability and peace of mind.

To ensure farmers have reliable markets for their produce, Elevarm has established a comprehensive market infrastructure. Under its Farmer Partnership Model, farmers commit to selling their entire harvest to Elevarm at mutually agreed-upon fair prices. This approach guarantees off-take certainty and strengthens market trust, reflected in the growing volume of produce sold directly to the company.

Sustainable and professional farming practices

Sustainability remains central to Elevarm’s vision. The company promotes Good Agricultural Practices (GAP), polyculture (adopted by 42.1 per cent of its farmers), organic fertilisation, and reduced chemical and water usage. Their flagship vermicompost and NextBio products are pivotal in improving soil health, enhancing plant resilience, and driving long-term environmental benefits.

A rigorous data-driven approach underpins Elevarm’s operations. The company employs stratified sampling, historical yield analysis, field surveys, and third-party datasets to measure impact accurately. This meticulous data collection informs strategic decisions and ensures transparency in reporting outcomes.

Also Read: Automation, AI, and agritech power Vietnam’s VC momentum

A robust governance framework incorporating Standard Operating Procedures (SOPs), Service Level Agreements (SLAs), and comprehensive risk management supports Elevarm’s model. This structure ensures consistent service delivery, timely input distribution, efficient payment processing, and reliable claim verification.

A vision for nationwide transformation

Looking ahead, Elevarm is poised to scale its model nationally. Following its focus on impact in 2024, the company plans significant expansion in 2025, targeting new high-value commodities such as shallots, tomatoes, and beans. It will also venture into agroforestry, revitalising underutilised lands in Purwakarta, West Java.

By 2026, Elevarm intends to extend operations to Sumatra and Sulawesi, with an eye on institutionalising its model through policy advocacy and government collaboration.

The company is also developing a predictive AI-powered digital platform that aims to become an indispensable tool for farmers, offering even more precise and timely insights.

As part of its growth strategy, Elevarm plans to introduce third-party audits and Social Return on Investment (SROI) analyses to further validate its SDG-linked outcomes. These efforts will expand the scope of measurable indicators, including gender impact, environmental footprint, and income stability.

—

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

Image Credit: Elevarm

The post Indonesia’s Elevarm runs a data-driven farming model targets national expansion by 2026 appeared first on e27.

In less than two years, generative AI has gone from novelty to necessity. It writes our emails, designs our slides, drafts our articles, generates our images, scripts our videos, and even suggests what we should think next. For many organisations, the question is no longer whether to adopt generative AI, but how fast they can integrate it into every workflow.

Yet quietly, beneath the enthusiasm, a new sentiment is emerging across creative, professional, and knowledge‑based industries: fatigue.

Not burnout from overwork—but a subtler exhaustion. A sense that creativity is becoming automated, flattened, and strangely hollow.

This is generative AI fatigue. And it forces us to ask an uncomfortable question: are we over‑automating creativity itself?

The promise: Efficiency, scale, and democratisation

Let’s be clear: generative AI works.

It lowers barriers to entry. A solo founder can produce what once required an agency. A junior employee can draft with confidence. A non‑designer can create visuals. A non‑writer can publish.

From a business perspective, this is revolutionary. Generative AI compresses time, reduces cost, and scales output. In an economy obsessed with speed and efficiency, this feels like progress.

It also democratises access. For many people who previously lacked language fluency, technical skill, or formal training, AI tools provide a starting point—a scaffold.

But scale and speed come with trade‑offs. And those trade‑offs are now becoming visible.

The symptom: Everything starts to sound the same

Scroll LinkedIn. Read Medium. Browse Substack. Watch short‑form videos.

You’ll notice a pattern.

Polished. Structured. Clean.

And eerily interchangeable.

Thought leadership posts follow identical rhythms. Articles echo the same metaphors. Marketing copy repeats familiar frameworks. Even “personal” stories feel optimised rather than lived.

Also Read: Creativity at the heart of business growth

This is not because people have suddenly lost originality. It’s because generative AI systems are trained on what already exists—and rewarded for producing what statistically resembles success.

AI doesn’t invent culture. It averages it.

When creativity becomes prompt‑based and output‑driven, uniqueness is no longer the goal. Predictability is.

The result? Content abundance—and meaning scarcity.

The deeper problem: Creativity without friction

Creativity has always been inefficient.

It requires boredom, false starts, uncertainty, and discomfort. It often involves writing badly before writing well. Thinking slowly. Sitting with ideas that don’t immediately resolve.

Generative AI removes much of this friction.

At first, this feels liberating. But over time, it creates a subtle dependency: we stop wrestling with ideas and start selecting from options.

When AI does the first draft, the hard part disappears. And with it, something else quietly vanishes—the depth that comes from struggle.

This matters because creativity is not just output. It is a process.

Without process, creativity becomes aesthetic production rather than thinking.

The workplace impact: Faster, but shallower

In corporate environments, generative AI is often positioned as a productivity multiplier. Employees are encouraged—sometimes pressured—to use it to work faster, respond quicker, and produce more.

But speed has consequences.

When everyone uses similar tools trained on similar data, differentiation erodes. Strategy documents converge. Campaign ideas blur. Internal thinking becomes less exploratory and more formulaic.

Ironically, the very tool meant to enhance creativity may be making organisations more risk‑averse. AI optimises for what has worked before, not what might work next.

Innovation, however, lives in deviation—not repetition.

The psychological toll: Creative disengagement

There is also a human cost.

Many creatives report a loss of ownership over their work. When ideas are co‑generated, authorship becomes ambiguous. Pride diminishes. Motivation fades.

Others feel a constant pressure to “keep up”—not with other people, but with machines. If AI can produce ten variations in seconds, why should your one carefully considered idea matter?

This leads to a quiet disengagement. People stop investing emotionally in their output. Work becomes transactional. Creativity becomes mechanical.

Fatigue sets in—not from effort, but from meaninglessness.

Also Read: After failure, rekindling our creativity and finding balance

Are we confusing productivity with value?

At the heart of generative AI fatigue is a fundamental misalignment: we are measuring the wrong thing.

We celebrate output volume, not insight. Speed, not originality. Optimisation, not depth.

But creativity has never been about efficiency. The most influential ideas in art, technology, and culture did not emerge because they were fast or scalable. They emerged because someone saw the world differently—and took the time to articulate that difference.

When everything is optimised, nothing feels essential.

A reframe: AI as assistant, not author

The solution is not rejection. Generative AI is not going away, nor should it.

But we need a cultural reset.

Also Read: Can generative AI usher us into the gilded age of ad creativity?

AI should support creativity, not replace the thinking behind it. It should help with execution, not identity. Drafting, not deciding. Formatting, not forming opinions.

The most valuable creative work going forward will not be the most polished—it will be the most human.

Messy ideas. Strong points of view. Lived experience. Moral judgment. Context.

These are things AI cannot automate.

The future: Scarcity of thought, not tools

In a world flooded with generative content, originality will become rarer—and therefore more valuable.

The competitive advantage will not be who uses AI best, but who knows when not to use it.

Those who can still think slowly, write imperfectly, and sit with uncertainty will stand out.

Generative AI fatigue is not a rejection of technology. It is a signal.

A reminder that creativity was never meant to be frictionless—and that meaning cannot be automated.

The question is no longer whether AI can create.

It’s whether we still remember why we do.

—

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.

Featured image generated using AI.

The post Generative AI fatigue: Are we over‑automating creativity? appeared first on e27.

e27 has been nurturing a supportive ecosystem for entrepreneurs since its inception. Our Contributor Programme offers a platform for sharing unique insights. As part of our ‘Contributor Spotlight’ series, we shine a spotlight on an outstanding contributor and dive into the vastness of their knowledge and expertise.

In the sections below, she reflects on her journey, the lessons she’s learned, and what keeps her going.

How I found my place

I see myself, and hope people see me, as a connector of talent, be it in my primary expertise (technical recruitment), or making connections between investors, educators, speakers and builders. For many, many years, I’ve had the pleasure of partnering with visionary deep tech and high-growth founders, investors, and companies to find the best minds who will bring their technological dreams to life. It’s a heartfelt process of weaving together strategy, empathy, and a relentless search for the right people to create the engineering and leadership foundations for Asia’s next wave of innovation.

A perspective that evolved over time

I once believed that scaling technology unicorns was the most meaningful work. I am now more drawn to the raw energy of early-stage deep tech. It’s really quite exciting being there from the very beginning, knowing that every person you bring on board will be writing the chapter of the story for the future.

Also Read: The art and science of feedback: A guide for first-time founders and new managers

The problem I’m focused on solving

In a nutshell, I connect brilliant ideas with brilliant people. Founders have these innovative, world-changing visions, but they can’t build them alone. Investors keep working passionately on making Singapore a viable place to safeguard and grow industries. My work is to dive into that vision and passion and then go out to find the amazing engineers, leaders, and creators who can turn those dreams into a reality.

The startup conversation we’re still not having

The startup world is a rollercoaster right now, and it’s not just about hiring fast during the good times. The real opportunity is in creating strong, connected teams from the start that can stick together and innovate through anything. It’s about building a culture where people feel secure and motivated to do their best work, no matter what the market looks like.

Why I write

I’ve been really lucky to have had a front-row seat to some of Asia’s biggest tech growth stories, and I’ve seen what works and what doesn’t. I’m currently embracing my granny-goddess era by sharing those hard-won lessons by writing here, to help other founders succeed on their own journeys.

My advice for aspiring thought leaders

The most articulate people I know are often great listeners as well. Be sincerely curious about what others think. If you communicate from a place of empathy and a desire to connect, your message naturally becomes clearer and more powerful. It’s less about sounding smart and more about being understood.

Also Read: A founder’s field guide to managing performance and giving feedback that lands

Influences that shaped my thinking

I’m on a mission to read everything Bill Bryson has written. I’ve been a fan of his books for a few years now. Past influences include Haruki Murakami, Milan Kundera — when I find an author I love, I often go on a hunt to track down and procure their “hidden gems”. Years ago, someone who was in love with me said that Eva Luna (by Isabel Allende) was his favourite book — it still remains the book that I aim to reread, every single year.

What drives my curiosity

Being a design-led person and a brand owner, I’m fascinated by how great design can spark positive social change. To see a well-designed product create deep conversations, or even a simple well-designed process, make life better and more equitable for people, this really floats my boat. It’s a wonderful reminder about how creativity matters and can even be a powerful force for good in the world.

Take a look at Lee’s articles here for more insights and perspectives on her expertise.

—

Are you ready to join a vibrant community of entrepreneurs and industry experts? Do you have insights, experiences, and knowledge to share?

Join the e27 Contributor Programme and become a valuable voice in our ecosystem.

The post Rachel Lee: The talent connector building Asia’s deep tech dreams appeared first on e27.

Investors processed unexpectedly soft retail sales data that simultaneously lifted hopes for Federal Reserve easing while exposing fragility across multiple asset classes. The Dow Jones Industrial Average managed a modest 0.1 per cent gain to establish a new record closing high. This narrow advance masked broader weakness as the S&P 500 declined 0.34 per cent to 6,941.33 and the Nasdaq Composite fell 0.6 per cent to 23,099.18. This divergence reflected a rotation away from technology and growth-oriented assets toward more defensive industrial names.

The fundamental catalyst, December retail sales, suggested a concerning loss of consumer momentum. Core sales dipped 0.1 per cent, contrary to expectations of expansion. This signalled that household spending power may have peaked by the end of 2025, with potential implications for fourth-quarter GDP growth calculations.

The bond market reacted decisively to the economic softening, with Treasury yields dropping sharply. The 10-year yield fell to approximately 4.14 per cent, its lowest level in a month. This move underscored how quickly market participants recalibrated their expectations for monetary policy. Money markets now price in elevated probabilities for three interest rate cuts during 2026. Federal Reserve officials, including Cleveland President Beth Hammack, emphasised that there is no immediate urgency for policy adjustments. This tension between market pricing and central bank communication created an undercurrent of uncertainty that permeated risk assets throughout the session.

Gold capitalised on the lower-yield environment, surging to consolidate above the psychologically significant US$5,000 per ounce threshold. Its non-yielding appeal has strengthened relative to fixed-income alternatives. WTI crude oil held steady near US$64.20 per barrel. Diplomatic developments in US-Iran negotiations supported prices by tempering fears of supply disruptions.

Also Read: The US$71000 Bitcoin bounce lacks foundation but Japan’s rally has real teeth

A noteworthy disruption emerged in the financial services sector, with shares of Charles Schwab and LPL Financial plummeting by at least seven per cent. Altruist Corp launched an AI-driven tax strategy tool, triggering broader anxiety about technological displacement across wealth management. This industry had long been considered relatively insulated from automation.

The severity of the reaction suggested investors recognised this as more than a niche competitive threat. It represented a potential inflection point for an entire professional services category. Global markets displayed their own complexities with Asian equities reaching an all-time high earlier in the trading day. South Korean strength led these gains, though Treasury trading remained subdued due to a Japanese market holiday. This limited cross-market feedback loops during a pivotal session.

The cryptocurrency market reflected these macro crosscurrents, declining 2.03 per cent to a total valuation of $2.35 trillion over the preceding 24 hours. This move exhibited a moderate 50 per cent correlation with the S&P 500. Digital assets increasingly moved in tandem with traditional risk sentiment rather than operating as an independent store of value. Beneath this surface correlation lay crypto-specific stressors of alarming magnitude. Bitcoin mining difficulty experienced its largest downward adjustment since 2021.

This signalled widespread miner capitulation as operational unprofitability forced network participants to shut down equipment. The exodus created direct selling pressure while simultaneously undermining confidence in the ecosystem’s foundational security layer. When those responsible for transaction validation and network integrity face existential financial pressure, the implications extend far beyond immediate price action.

Compounding this structural weakness, institutional capital continued its retreat from regulated Bitcoin exposure. Spot ETF assets under management contracted by US$13.6 billion within a single week, falling from US$110.92 billion to US$97.31 billion. This outflow represented a reversal of one of the primary drivers behind the previous bull market cycle. Derivatives markets experienced a violent deleveraging event, with open interest dropping 9.76 per cent in 24 hours.

Funding rates turned negative, triggering forced liquidations of overextended long positions. The convergence of miner distress, institutional withdrawal, and speculative unwinding created a self-reinforcing negative feedback loop. Each element amplified the others, producing cascading selling pressure across the digital asset landscape.

Also Read: From US$70K to freefall: Can Bitcoin hold the US$60K lifeline after US$1B liquidation event?

Technical indicators suggested the market was approaching an inflection point, with Bitcoin’s relative strength index plunging to 24.33. This indicated an oversold condition that historically precedes short-term bounces. The critical threshold rested at US$68,000, where a successful defence could catalyse a relief rally toward US$70,500.

A breakdown below this support level threatened to extend the downtrend significantly. The path forward depended on two key variables. ETF flows needed to reverse before additional miner selling emerged. The outcome of White House stablecoin legislation talks also mattered, with a policy deadline approaching at the end of February 2026. Regulatory clarity around stablecoin yields might provide the catalyst needed to restore institutional confidence, though timing remained uncertain.

The day ultimately revealed markets operating at an inflection point, with traditional and digital asset classes moving in concert yet retaining distinct vulnerability profiles. Traditional markets grappled with the contradiction between softening economic data and still hawkish central bank rhetoric. Crypto markets faced acute structural pressures at their operational core. The miner capitulation represented more than a price catalyst. It signalled stress at the very foundation of blockchain security models.

This moment of fragility also contained the seeds of potential renewal. Network difficulty adjustments have historically preceded major cycle bottoms by forcing inefficient participants out of the ecosystem. The coming weeks would test whether coordinated policy responses and technological adaptation could stabilise these interconnected markets.

Deeper recalibration might remain necessary before sustainable growth could resume. Investors now faced the challenge of distinguishing between temporary volatility and fundamental regime shifts across both traditional finance and its emerging digital counterpart.

The interplay among macroeconomic data points, technological disruption, and network-level stressors created a multifaceted environment that demands nuanced analysis rather than simplistic narratives. Market participants who recognised these layered dynamics stood better positioned to navigate the uncertain terrain ahead.

—

The post Dow hits record high, Nasdaq tumbles 0.6 per cent, Bitcoin miners flee: Signals deeper stress than price alone appeared first on e27.

In startup conversations, few phrases raise a quieter red flag than this one: “I want to sell to everyone.”

It’s usually said with optimism. Sometimes with ambition. Often with confidence. But almost always, it signals a deeper issue, not of scale, but of clarity.

Founders don’t struggle because they think too big. They struggle because they think too vaguely.

The most expensive confusion in the go-to-market

A brand cannot speak to a first-time founder the same way it speaks to a seasoned operator. A product cannot sell to a solo creator the same way it sells to an enterprise team. And yet, many early-stage startups attempt to do exactly that, flattening their message in the hope of maximising reach.

The result is predictable. Messaging becomes generic. Value propositions blur. Sales conversations stretch. And the product slowly morphs into something that tries to please everyone, and resonates deeply with no one.

When a founder says “everyone”, what they are really saying is: “I haven’t made the hard decision yet.”

Luck, budget, and brute force are not a strategy

Of course, there are exceptions.

With enough capital, distribution power, or sheer luck, a broadly positioned product may still find traction. But luck is not a repeatable system, and brute force is not a defensible moat.

In the early stages of a company, clarity consistently outperforms scale. The startups that move fastest are not the ones shouting the loudest; they are the ones that know exactly who they are speaking to and why.

Also Read: Revisiting “Something Ventured”: What the birth of venture capital still teaches Founders today

What strategic clarity looks like in practice

Founders who build multiple businesses quickly learn this lesson the hard way. Different products require different audiences.
Different audiences require different languages. And different problems demand different promises.

An AI platform designed to act as a founder’s digital twin, Seraphina AI, for example, is not competing with generic productivity tools. It is built for people who already have opinions, frameworks, and a voice, and want leverage, not replacement.

A female founders community, Royal Visionary Society, focused on freedom, sustainability, and long-term well-being, is not optimised for founders chasing growth at any cost.

A speaking ecosystem, Speakers Society, designed around placement, positioning, and monetisation, is not for hobbyists looking to overcome stage fright.

A marketing automation platform, People’s Inc. 360, built for operational scale, is not meant for teams that equate growth with hiring more people.

Each of these businesses succeeds not by expanding its audience indiscriminately, but by narrowing its focus deliberately.

Different doors. Different conversations. Same strategic discipline.

The quiet advantage of being clear

The strongest brands in the ecosystem share a common trait: restraint.

They know who they are for. They know who they are not for. And they design their product, messaging, pricing, and systems around that decision.

This clarity shows up everywhere, from onboarding flows to sales conversations, from roadmap decisions to customer support.

Trying to appeal to everyone does not make a company more inclusive. It makes it forgettable.

Also Read: Bridging innovation and market success: The role of a commercial co-founder in biotech startups

The hidden cost of over-inclusivity

When founders avoid choosing a clear audience, the costs compound quietly:

• Product roadmaps bloat with edge cases.
• Marketing messages lose sharpness.
• Sales teams struggle to qualify leads.
• Customers feel vaguely interested, but never fully committed.

Most churn is not caused by poor execution. It is caused by unclear positioning.

People do not leave because a product is too specific. They leave because they never felt seen.

A simple clarity test for founders

Before worrying about traffic, funding, or scale, founders should be able to answer three questions clearly:

• Who should immediately feel understood when they encounter this product? Not impressed. Understood.
• Who is this deliberately not built for? Every strong brand repels by design.
• If this product disappeared tomorrow, who would genuinely feel the loss? If the answer is “anyone”, it is probably no one.

If these answers are unclear, the problem is not distribution. It is positioning.

Conviction is the real growth lever

The companies that scale well are not the ones that hedge their message. They are the ones who commit.

They choose a lane. They build with intention. They speak directly, even when it means being misunderstood by those outside their audience.

Because in a crowded ecosystem, clarity is not a limitation. It is leverage.

And real growth does not come from dilution. It comes from conviction.

—

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

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

Image courtesy: Canva

The post If you’re building for everyone, you’re building for no one appeared first on e27.

Startup ecosystems are often portrayed as bottom-up systems driven by founders, venture capital, and technological breakthroughs. That view is incomplete. In practice, startup ecosystems are also downstream expressions of state power, shaped by policy decisions, institutional participation, and geopolitical alignment.

This US withdrawal from international climate and energy institutions alters the conditions under which startups are built, financed, and scaled, where climate and energy governance are strategic infrastructure for global markets.

The climate-energy stack the US stepped away from

The US withdrawal spans a broad range of climate, energy, and environmental institutions. Together, these bodies form the global climate–energy operating system. They do not build grids, finance startups, or operate markets directly. Their influence is structural rather than transactional.

Climate science bodies establish baselines that flow into regulation, finance, and insurance. Energy agencies coordinate definitions of “renewable,” “transition,” and “clean” that underpin procurement and investment decisions. Nature and forestry platforms shape land-use rules, carbon markets, and supply-chain traceability. UN coordination mechanisms align agencies, donors, and reporting frameworks across borders.

These institutions sit upstream of markets. They determine what is measured, how it is measured, and which activities are recognised as legitimate or investable. Startups rarely engage with them directly, but their outputs shape the environment in which startups operate.

By withdrawing, the United States is not exiting climate or energy markets. It is exiting the multilateral rule-shaping layer that influences how those markets evolve globally.

Survival without the US does not mean neutrality

From a financial perspective, most affected institutions are likely to survive. European governments, Japan, Nordic states, and philanthropic actors can backfill near-term funding gaps. Many of these bodies already operate with diversified funding sources and experience donor volatility.

Institutional survival, however, should not be confused with institutional neutrality or effectiveness.

Also Read: Code, power, and chaos: The geopolitics of cybersecurity

As US participation recedes, three structural shifts are likely. First, agenda-setting power (and hence influence) concentrates among the remaining major funders. Second, standards and methodologies evolve according to the regulatory philosophies of those still at the table, gradually redefining what becomes “normal” or “default” in global markets. Third, even modest funding disruptions can slow research cycles, narrow mandates, and reduce technical ambition.

For startups and investors, the critical point is not collapse but tilt. The global climate–energy regime becomes less US-centric and more shaped by European regulatory logic, Asian industrial priorities, and Global South adaptation needs.

That tilt matters because it reshapes the assumptions embedded in products, platforms, and business models.

The fiscal reality: Small savings, large signals

From the US federal budget perspective, the direct savings from withdrawal are modest. The combined reduction in assessed dues and typical voluntary contributions amounts to tens of millions of dollars per year.

Measured against a federal budget and annual deficits exceeding a trillion dollars, and rapidly rising interest costs, these savings are economically immaterial. They do not alter the debt trajectory or meaningfully expand fiscal space.

Markets, however, respond less to absolute numbers than to signals of power and intent. A decision to step away from rule-writing institutions sends a strong signal about priorities, alignment, and future engagement. That signal reshapes expectations about where standards will be set, where capital will flow, and which jurisdictions will define the next generation of market rules.

The financial impact is small. The geopolitical signal is large, and the market price signals.

What this means for corporates: The end of a single global rulebook

For large enterprises, the immediate impact is not loss of market access but loss of predictability.

As climate and energy governance fragments, companies face growing divergence between US, European, and Asia-Pacific standards. The assumption that a single global compliance strategy will suffice becomes increasingly untenable. Firms operating across regions must navigate multiple definitions, reporting regimes, and certification systems.

The strategic response is operational rather than ideological. Climate and energy policy must be treated as trade policy, supply-chain policy, and security policy. Scenario planning must assume fragmentation, not convergence.

The era in which global companies could rely on a single, slowly evolving rulebook is ending.

What this means for startups: Geopolitics enters the product roadmap

Startups experience these shifts earlier and more acutely than incumbents. The most exposed ones are climate tech, energy software, grid and storage systems, ESG and climate data platforms, supply-chain SaaS, carbon markets, advanced materials, and industrial automation.

The core challenge is that global scalability becomes more complex. Different blocs increasingly favour distinct standards, data requirements, and compliance pathways. A product designed around US regulatory assumptions may encounter friction in Europe or Asia—not because it lacks technical merit, but because it no longer aligns with how legitimacy is defined.

For founders, the implications are practical. Go-to-market strategies must account for regulatory geography alongside customer geography. Early product decisions may need to anticipate multiple standards regimes. Policy and regulatory expertise may need to be integrated earlier than in previous startup cycles.

There is an opportunity embedded in this complexity. Startups that can bridge standards, abstract compliance, or translate between regimes gain value as fragmentation increases. In a splintered system, interoperability becomes a competitive moat.

Also Read: How cybersecurity companies can build trust through digital PR

What this means for investors: Repricing policy risk

For investors, the withdrawal changes how climate and energy risk should be underwritten. Policy convergence can no longer be assumed. This increases jurisdictional risk, complicates exit pathways, and heightens sensitivity to political change.

Capital will increasingly favour companies with geographic optionality, diversified revenue exposure, and resilience to policy shifts. Business models that depend heavily on continued US federal leadership or multilateral climate mechanisms will be discounted.

The investor question shifts from “Is this aligned with climate policy?” to a more strategic inquiry: “Which political system does this company scale under?”

Geopolitical literacy becomes a core investment competency rather than a peripheral concern.

Supply chains: Where geopolitics becomes physical

Beyond software and data, the effects propagate into physical value chains. Critical minerals, energy hardware, batteries, grid equipment, and industrial manufacturing face higher coordination costs, greater reliance on bilateral agreements, and increased exposure to sanctions and political risk. Governments must now work a lot harder to find bilateral partners, as multilateralism now breaks up.

For startups embedded in these chains, technical excellence alone is no longer sufficient. Understanding geopolitical context—who controls resources, who sets standards, and who provides security—becomes central to long-term viability.

Conclusion: Geopolitics as a startup variable

This is not a story about climate virtue or environmental ambition. It is a story about how state power reshapes markets and innovation ecosystems.

The US withdrawal from international climate and energy institutions saves little money, but it changes who writes the rules that govern future markets. That shift increases complexity, raises the premium on geopolitical awareness, and alters competitive dynamics across the startup stack.

For founders, executives, and investors, the implication is clear:

Geopolitics is no longer background noise. It is a core variable in startup strategy, capital allocation, and scale.

Those who understand this will adapt early. Those who do not will experience it as friction they cannot fully explain—until it becomes a constraint they cannot escape.

—

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

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

Image courtesy: Canva

The post When nation-states shape startup outcomes appeared first on e27.