The Drop

The Drop

Across many emerging economies, something interesting is happening quietly behin...

Across many emerging economies, something interesting is happening quietly behind the scenes.

Technology leaders are experimenting with AI in isolation.

An CIO in Vietnam is testing agentic workflows alone at night after work. A startup founder in Cambodia is trying to automate operations with limited infrastructure. An operations manager in Laos is secretly learning prompt engineering because they know the industry is changing. A teacher in Myanmar is exploring AI tools without institutional support. A young developer in Indonesia is building AI agents from YouTube tutorials and online forums.

Thousands of people across emerging markets are learning, adapting, and experimenting.

But very few are talking to each other.

That silence matters.

In developed economies, AI ecosystems evolve through communities. Founders share lessons publicly. Engineers publish experiments. Universities collaborate with startups. Governments engage industry groups. Venture capital amplifies narratives. Media platforms continuously discuss what is working and what is not.

In many emerging economies, the opposite is true.

Many tech leaders work quietly. Privately. Defensively.

Sometimes because of politics. Sometimes because of company culture. Sometimes because they fear criticism and trust issues. Sometimes because there simply are not enough local communities discussing these topics seriously.

The result is fragmented progress.

Everyone is solving similar problems separately:

How to implement AI with limited budgets How to train staff with low digital maturity How to integrate AI into traditional businesses How to manage cybersecurity risks How to use AI when infrastructure is still developing How to convince senior management that AI is not just hype

Yet these lessons rarely become visible knowledge.

That creates a dangerous gap.

If emerging economies do not start documenting and sharing their AI journeys, the future of AI adoption in our regions will be shaped almost entirely by external narratives.

And external narratives rarely understand local realities.

A fintech in Laos does not operate like a tech startup in California. A family-owned manufacturer in Cambodia does not have the same capital structure as a company in Singapore. A regional school system in Indochina faces different workforce challenges than Europe or the US.

We need our own case studies. Our own experiments. Our own failures. Our own voices.

Not to compete with Silicon Valley or China's Shenzhen or Hangzhou.

But to ensure our regions are not invisible in the next economic transformation.

The irony is that emerging economies may actually have one hidden advantage in the AI era: adaptability.

Many organizations here are smaller, leaner, and less burdened by legacy systems. Younger professionals are already self-learning through AI. Small teams are beginning to operate with capabilities that once required large departments.

But isolated learning can only go so far.

Eventually, ecosystems matter.

The regions that share knowledge faster will compound capability faster. The countries that normalize open discussion around AI adoption will build stronger talent pipelines. The communities that collaborate early will attract future investment, partnerships, and opportunities.

This is why telling our own AI stories matters.

Not because we need attention.

But because visibility creates momentum.

And right now, too many capable people across emerging economies are building the future alone behind closed doors.

Agentic Frontier

Funding Tracker

Marketing operating system Nectar Social raises $30M Series A led by Menlo
[Source: techcrunch.com]

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