When Malaysian edutech startup Pandai first launched in 2020, its ambition was modest but clear: help students learn better outside the classroom through personalised digital support aligned with the national curriculum. Five years on, that focus on product depth rather than aggressive marketing has helped Pandai scale to more than one million users — and earn a place in the London School of Economics’ (LSE) prestigious 100x Impact cohort.

Pandai is one of four Southeast Asian ventures selected for the latest 100x Impact programme, an LSE initiative that identifies high-impact organisations with the potential to improve the lives of one billion people. Chosen from more than 800 global applicants, the cohort spans sectors including education, health, and income inequality, and features both for-profit and nonprofit models that are already delivering measurable results at scale.

For Pandai, participation in 100x Impact represents validation of a strategy that has always prioritised educational outcomes alongside sustainable growth. “Since Pandai started, the focus has always been on personalising the offering,” says Khairul Anwar, CEO and co-founder of Pandai, in an interview with e27. “Everything in Pandai — quizzes, tests, flashcards and gamified activities — is tailored to each student’s progress and performance.”

Unlike one-size-fits-all learning platforms, Pandai dynamically adapts its content. Even students from the same class using the app will have different learning journeys, depending on their strengths and weaknesses. The platform covers the full school curriculum for primary and secondary students aged seven to 17, combining curriculum-aligned content, AI, and gamification to drive engagement and retention.

That emphasis on product quality has played a critical role in Pandai’s user acquisition strategy. In its first year, the edutech startup invested nothing in paid marketing, instead relying on organic growth driven by word of mouth and social sharing. Even today, paid advertising plays a minimal role. “Our customer acquisition cost is very, very low,” Khairul says.

Also Read: Why Southeast Asia’s edutech must go beyond chatbots to truly transform learning

Most new users discover Pandai organically through recommendations from friends, social media or search, a key factor behind its strong SEO performance as an edutech startup. Affiliate programmes, where existing students invite peers, and a network of “Pandai consultants”—typically teachers and parents—further support growth. Over the past two years, Pandai has also expanded into B2B partnerships, working with schools, corporates and foundations to subsidise access for underserved communities.

This multi-channel approach has helped Pandai reach scale without compromising its social mission. About 30 per cent of its users come from rural or underprivileged backgrounds, a figure the company is particularly proud of. To support learners with limited connectivity, Pandai has developed an offline mode that allows students to preload content and continue studying even with intermittent or no internet access.

Pandai’s business model reflects this balance between impact and growth. The platform operates on a freemium basis, offering a free version that is available indefinitely. Paid subscriptions unlock features such as deeper performance analytics, interactive content and live classes. “The small portion of students who are paying are essentially subsidising the rest,” Khairul explains. “That’s how we stay true to our mission while remaining sustainable.”

The result is a rare combination in the edutech startup space: rapid scale paired with strong retention. Pandai’s monthly retention rate has improved from 60 per cent in its early days to an average of 94 per cent today, driven by continuous improvements in content, technology and user experience.

Behind the product is a founding team deeply shaped by education. The founders were schoolmates who benefited from scholarships and supportive learning environments, experiences that informed their decision to build an education-focused company. “We saw firsthand how education can transform lives,” Khairul says. “That’s why education felt like our calling.”

Also Read: TikTok and the future of education: How Generation Alpha actually learns

Support from external organisations has also been crucial. Programmes such as LSE’s 100x Impact provide frameworks and mentorship to help Pandai refine its long-term “impact endgame” — how it can scale responsibly while deepening outcomes for learners. For Pandai, being part of the 100x Impact cohort is less about prestige and more about amplification. “We cannot take credit for everything ourselves,” Khairul adds. “A lot of organisations around us have supported us to reach more students.”

As Southeast Asia emerges as a hub for social innovation, Pandai’s journey highlights how an edutech startup can grow by staying anchored to its mission. By focusing on personalised learning, low-cost user acquisition and inclusive access, Pandai is positioning itself not just as a fast-growing platform, but as a scalable solution to education inequality — one student at a time.

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Image Credit: Pandai

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The first wave of freelancing in Asia was about independence — choosing your clients, your hours, and your projects. The second wave, accelerated by the pandemic, brought a surge of creators, solopreneurs, and portfolio careers.

Now, a third wave is coming. And this time, it is shaped by AI.

For creative freelancers, the question is no longer “Will AI take my job?” but “What will my job become?” As someone who has spent over a decade championing the freelance space through CreativesAtWork and now building GenAI production workflows at Dear.AI, we are confident that we are heading towards a future where the definition of freelance work is being rewritten. We are no longer just “gig workers.” We are becoming architects of ideas.

From gig work to intelligent work

Freelancing has always been about independence. Yet, too often, that independence comes at the cost of stability. Freelancers traded security for flexibility, managing fluctuating income, burnout, and a constant chase for the next gig.

AI is changing that equation. It is giving independent professionals especially the creatives, the ability to operate with the efficiency and capability of a small agency — but without the overheads.

Instead of competing on price or speed, freelancers can now truly compete on value — by combining human insight with AI-driven execution. We are seeing the rise of “intelligent freelancers” (ie. professionals who use AI not just to do more, but to think differently).

Freelancers must rethink revenue models

AI compresses production time dramatically. If you are still billing by the hour, it will be a bad news! Your income will shrink as projects become faster to produce. New revenue models are not optional — they are essential. The new revenue models could be a combination of the following:

• Value-based pricing: Charging for business outcomes rather than hours.
• Licensing instead of one-offs: Designers, videographers, and writers across Asia are experimenting with licensing templates, story frameworks, and reusable assets.
• Monthly creative subscriptions: Clients access a creator’s brain and capabilities, not individual tasks.
• Revenue-share partnerships: More creators are co-developing campaigns, original IP, or brand content with profit-sharing models — especially in the creator and media economy.

Insight, originality, and taste will remain premium. Freelancers need to rethink their revenue models.

Also Read: Singapore’s workforce is facing its biggest reset yet and AI is forcing the shift

The new skillsets for freelancers

Technical literacy is now the baseline. To thrive in the new freelance economy, you need to level up in areas AI cannot touch:

• Creative direction: AI generates a thousand options; you are the one who decides what has meaning.
• Cultural curation: Asia is a mosaic of nuance. AI can remix culture, but it cannot originate the “soul” of a local story. Your cultural intuition is your greatest asset.
• Workflow orchestration: Knowing which AI tools to chain together is the new “mastery of the craft.”

The human advantage in an automated Asia

Asia’s freelance economy will not be shaped by AI tools alone. It will be shaped by:

• Cultural intuition
• Lived experiences
• Empathy
• Community roots
• Multilingual storytelling
• Emotional intelligence
  

AI can replicate style, but not soul. It can remix culture, but not originate it. As AI reduces the burden of technical labour, the value of human perspective increases — especially in a region as culturally rich and diverse as Asia.

A future where freelancers lead, not follow

Asia is uniquely positioned to lead this 2.0 freelance economy. We have a young, digitally native population and a booming creator economy hungry for storytelling. But remember: AI can replicate style, but it cannot replicate soul. It lacks lived experience, empathy, and community roots. As the burden of “technical labour” decreases, the value of our unique human perspective increases.

Conclusion

The freelancers who thrive, in the future, will be those who embrace hybrid identities — blending creativity, strategy, technology, and empathy. The future does not belong to the fastest adapter of tools. It will belong to the one who uses AI to become more creative, more human, and more original. Because in the age of AI, the most powerful work does not come from automation. It comes from amplified imagination.

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When I run workshops for older adults, I see the same moment every time. A trembling hand hovers over the keyboard. Someone looks up and whispers, “Teacher, if I press this key, will it spoil the computer?”

They do not dare to touch the screen. They worry that one wrong click will destroy everything. And when I tell them gently, “You can just delete it,” they still hesitate.

It is not the machine they fear. It is embarrassment.

Many midlife and senior learners are not afraid of technology itself. They are afraid of looking foolish, of doing it wrong, of being judged by others who “know better.” They do not want to risk fun for judgment. Or as one of my learners said with a laugh, “Jude who? Why risk fun for judgment?”

That small sentence says everything. Underneath every hesitation lies the fear of being laughed at instead of supported.

Where the fear begins

For those of us who grew up in a world of pens and paper, technology feels like a foreign language. Every update changes the grammar. Every new app comes with a new accent.

When you are not fluent in that language, silence feels safer than speaking. That is why many older adults say, “I cannot learn.” They simply do not want to feel small again.

The problem is not ability. It is confidence.

Learning needs safety, not speed

When seniors enter an AI class, what they need most is not information. They need a space where it is safe to try, fail and laugh.

One of my students once said, “I did not know I was allowed to make mistakes here.” After that, she started experimenting with voice-to-text, image generation and storytelling. Her progress was not because of the tool but because of the environment.

When we remove judgment, curiosity returns. And when curiosity returns, learning becomes natural.

Also Read: The second act: How midlifers are reinventing themselves with AI

Reframing what learning means

In school, mistakes are punished. But in creativity, mistakes are how discovery begins.

Adults need to unlearn the belief that knowledge only comes from perfection. AI actually rewards trial and error. It invites us to ask, test and adjust.

You cannot break AI by asking questions. But you can break your own confidence by not trying at all.

Building bridges between generations

Younger people often forget that older learners want to participate. They just need someone patient enough to walk with them.

When a teenager teaches a parent how to use AI, both grow. The younger learns empathy and patience. The older learns courage and self-trust.

It is not about who knows more. It is about discovering together.

Creating confidence through small wins

Confidence is built through small successes. Each time an older learner writes a story, generates a picture or records their voice, they prove they can still learn.

The key is to start small. Ask one question. Try one feature. Share one post. Every attempt removes fear and builds trust, not only in AI but in their own ability to grow again.

The gentle reminder

Technology will always evolve, but our curiosity can evolve with it. If we treat AI as a bridge rather than a barrier, it can reconnect generations and rebuild confidence.

The fear of breaking something is real, but the greater loss is never pressing the button at all. It is not about perfection. It is about participation.

So go ahead. Press the key. Delete. Retry. Post. Because courage begins with a single click.

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The once distinct lines between creator, player, and entrepreneur are dissolving into something new that fundamentally restructures how value is created and captured in the gaming ecosystem.

Gaming began as a subversive tool for consumption where value flowed one way from player to publisher, enabling publishers to build massive empires.

Esports was the first revolution that shook up this structure and allowed a microscopic segment of players to monetise their skills. However, of the over three billion global gamers in the ecosystem, only 15,000 can earn a sustainable living through competitive play, and even fewer earn the equivalent of a “professional athlete‘s” salary. 

Streaming was the second uprising that allowed over 9.2 million active streamers and gamers to find a path to monetisation. Yet the economics remain brutal, with only the top 10 per cent able to earn well. The platform-dependent revenue model, reliant on subscriptions, tips, and ads, means most operate on economic margins thinner than graphene.

We now stand at a more significant threshold with AI that doesn’t just add another revenue stream to the existing ecosystem—it rewrites the fundamental relationship between creation, distribution, and monetisation in gaming. These are encapsulated in the three phases of AI-powered gaming entrepreneurs.

Phase 1: Asset creation and community building

For the 95 per cent of streamers who struggle with differentiation and asset creation, AI offers immediate relief. The data is clear, 82 per cent of streamers report difficulties in creating unique visual assets for their brand and content, while 74 per cent struggle to maintain consistent creative output alongside their streaming schedules.

AI asset generation solves both a production and economic problem. Streamers who incorporate real-time audience participation through interactive content show 68 per cent higher viewer retention. When AI enables streamers to generate assets based on viewer input in real-time, the para-social becomes genuinely collaborative.

This shift has already begun. The most successful creators aren’t just playing games—they’re creating within them, building distinctive visual identities and interactive experiences that transform passive viewers into active participants.

Also Read: How sailing as a teenager prepared me for a career in tech and gaming

Phase 2: Monetisation through platform ecosystems

As streamers build communities around their AI-enhanced content, the next logical step is direct monetisation of their creations within existing game ecosystems.

The platforms are already massive, with Roblox has reaching 82.9 million daily active users and creator payouts hitting US$923 million in 2024 alone.  What’s more telling is the distribution, 20,000 qualifying Roblox creators earned an average of US$46,150 each.

Compare this to streaming, where only 23 per cent of streamers use sponsorships, and just 18 per cent sell merchandise. The User Generated Content (UGC) economy represents a significant expansion of monetisation potential, yet only four per cent of streamers currently tap into digital asset sales. This gap between current utilisation and market potential won’t last.

The successful transition from streamer to platform creator doesn’t mean abandoning streaming, it’s the opposite. Streamers who involve their communities in content creation see over three times the engagement and create a virtuous cycle where streaming builds audience, audience provides feedback on creations, creations generate revenue, and revenue enables more streaming.

Phase 3: Independent development and gaming entrepreneurship

The final phase, with the most transformative potential, is independent game development enabled by AI.

The economics of traditional game development have become increasingly punitive and unsustainable. Development costs for major titles doubled to US$200 million between console generations. Marketing costs frequently exceed development budgets. The barrier to entry isn’t just high—it’s stratospheric.

AI tools fundamentally changes this equation by reducing art production costs by more than half, automatically optimising code, and generating vast game worlds through procedural systems. The capital requirements for game development has decreased by orders of magnitude.

This democratisation creates an unprecedented advantage for creators who’ve cultivated loyal communities. Those who build dedicated followings through streaming and UGC gain the ability to sell complete games directly to an established audience. The model mirrors independent music artists who spend years building fan bases before selling out concerts and releasing albums that they own the rights to—keeping the vast majority of revenue instead of settling for industry-standard royalties. When a streamer with 100,000 followers releases their own game, they’re not starting from zero—they’re launching with a pre-built audience, distribution channel, and feedback mechanism already in place.

Also Read: Blockchain gaming trends in Asia: here’s what you need to know

For entrepreneurs building at this intersection of AI, UGC, and streaming, the potential extends beyond just making games. They’re building economic systems—places where value is created, exchanged, and captured continuously rather than in single transactions.

Why this time is different

We have seen democratisation promises before, game engines became more accessible and distribution platforms open up. Yet the gap between amateurs and professionals remain vast.

The AI difference does not just lower barriers, it actively allows collaborations. It does not just make tools more accessible, it augments human creativity in ways that fundamentally change what is possible for a small team or even an individual.

The integration of AI creation tools is rapidly erasing the distinction between professional and amateur content. The successful gaming entrepreneurs of tomorrow will not be those with the largest teams or development budgets, they will be those who best leverage AI to amplify their creative vision and community engagement.

For several years, the gaming industry has undergone a quiet restructuring. The development costs for AAA titles have become unsustainable, while user acquisition costs have risen 45 per cent year-on-year in mature markets, and the return on ad spend have declined by 30 per cent since 2021.     

These economic pressures create the perfect conditions for AI-powered disruption, and the platforms sensing this shift are already making their moves. Roblox nearly tripled creator payouts since 2022, Epic has been refining engagement-based payouts in Fortnite Creative, and major modding platforms have experienced download growth of over 40 per cent. 

The gaming entrepreneurs who will dominate the next decade are already building their communities. These are the streamers with 100 to 1,000 concurrent viewers who recognise that engagement is more valuable than pure reach, and these are the rising creators who see AI not as a replacement for human creativity, but as a force multiplier for it.

The path from player to professional and to entrepreneur is not just possible, but inevitable for those who recognise what’s happening. The game has changed. The only question is who will play it best.

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