One of the things that has surprised me most over the past year is how rarely my conversations with futurists actually stay focused on artificial intelligence. We usually begin there. We talk about generative models, autonomous agents, the next version of ChatGPT, the speed at which these systems are evolving. Yet after twenty or thirty minutes, AI almost disappears from the conversation. We find ourselves talking instead about labor markets, education, political institutions, governance and, eventually, something much larger than technology itself: the possibility that we are approaching the end of an economic model that has shaped modern societies for generations.
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AI isn’t the story
That shift in perspective has been difficult to ignore. We often compare AI to the internet or smartphones because it makes the transformation easier to understand. Those technologies undoubtedly changed our lives. But they never challenged one of the central assumptions underpinning modern economies: that human labor is the primary engine through which value is created and wealth is distributed. Artificial intelligence might.
Brett King during an interview with The Astana Times correspondent Aida Haidar. Photo credit: The Astana Times
During one of our interviews, futurist Brett King made an observation that has stayed with me ever since. The more automation we introduce into the economy, he said, the less the traditional mechanics of capitalism function in the way they were originally designed. As he put it, it will be the end of capitalism as we know it. Whether or not one agrees with his conclusion is almost secondary.
The more interesting question is what governments should do if he is even partially right. Because history suggests that institutions rarely have the luxury of waiting until structural change is complete before deciding how to respond. By then, the transition is usually far more painful than it needed to be.
Perhaps this is why I have gradually become less interested in AI itself and more interested in leadership. Not political leadership in the conventional sense, but the ability of governments to think beyond immediate political cycles and prepare societies for an economy that does not yet fully exist.
Brett challenged another assumption that many of us have taken for granted over the last four decades: that markets, left largely to themselves, will eventually solve most problems.
“The free market hasn’t solved climate change. The free market hasn’t solved poverty. It hasn’t solved homelessness. This is not something that the free market is going to solve. This is a function of coordinated governance,” he told me.
It is a provocative argument, particularly at a time when governments around the world are still trying to determine how much they should regulate artificial intelligence and how much they should simply allow innovation to unfold. Yet there is something compelling about the distinction he makes.
Artificial intelligence is not disrupting a single industry. It is beginning to influence healthcare, transportation, logistics, finance, manufacturing, education and public administration simultaneously. Unlike previous technological revolutions, it does not fit neatly within the responsibility of one ministry or one regulator. It cuts across virtually every institution that modern states have spent decades building.
If that is true, then leadership acquires a different meaning. It becomes less about managing today’s economy efficiently and more about preparing citizens for tomorrow’s economy before it fully arrives. This is perhaps why Kazakhstan has become an unexpectedly interesting case study.
Preparing before the future arrives
For years, discussions about Kazakhstan’s future largely revolved around energy, critical minerals, connectivity and its geopolitical position between major powers. Increasingly, however, another narrative has begun to emerge, one that places artificial intelligence at the center of the country’s long-term development strategy rather than treating it as another digital policy initiative.
Over the past two years, the government has launched the International AI Center Alem.ai, expanded the AI-Sana education initiative, invested in computing infrastructure and accelerated efforts to integrate artificial intelligence into public administration.
That shift is also evident in Kazakhstan’s official discourse. Speaking at the second meeting of the Council for the Development of Artificial Intelligence, President Kassym-Jomart Tokayev said that “traditional growth models based on resources and labour are losing effectiveness” and warned that unless Kazakhstan rapidly transitions to a fully integrated, AI-powered, data-driven economy, it risks falling behind in the global technological race.
Whether every initiative succeeds is, in some ways, beside the point. History offers very few examples of governments navigating technological revolutions perfectly. But there is a meaningful difference between preparing too early and preparing too late. One risks investing in ideas that will inevitably evolve. The other risks discovering that the rules of the global economy have already changed. This is precisely what Brett was referring to when he spoke not about technology, but about time.
Modern societies, he told me, have become trapped inside quarterly earnings reports, annual budgets and electoral cycles. Yet transformative projects have never been built that way. Cathedrals took generations. The Panama Canal took decades. The Apollo program demanded sustained political commitment that extended far beyond a single administration. AI, he believes, belongs in that same category of civilizational change.
Listening to him, I found myself wondering whether our biggest challenge is not AI at all. Perhaps it is our shrinking political imagination. Can democratic governments still think thirty years ahead? Can they justify investments whose returns may only become obvious long after today’s leaders leave office? Those questions feel increasingly relevant when looking at Kazakhstan.
President Tokayev has repeatedly noted that digital transformation is no longer optional but essential for maintaining competitiveness in a rapidly changing world. Speaking at the AI conference this July in Shanghai, he stressed that no country should remain merely a consumer of AI technologies and that every nation must develop its own human capital so technological progress serves society rather than deepening inequality.
“No country should remain merely a consumer of artificial intelligence. Every nation must have the opportunity to develop its own human capital, digital infrastructure and institutional capacity. At its core, this is a matter of fairness and equity,” he said.
The human side of an AI economy
What I find interesting is not the ambition itself. Many governments now speak enthusiastically about AI. What stands out is the attempt to connect AI with education, state capacity and long-term economic planning rather than viewing it simply as another technology sector. That connection surfaced repeatedly during my conversations with both futurists Brett King and Ron Immink.
Ron approached the issue from an entirely different direction. He was less concerned with algorithms than with culture. Most leading AI systems, he pointed out, continue to think primarily in English. Yet languages carry different ways of understanding the world, different historical experiences and different cultural contexts. If artificial intelligence is to become genuinely intelligent, it cannot simply translate languages; it must learn to understand them.
Ron Immink. Photo credit: The Astana Times
That observation gave me a different perspective on a seemingly minor piece of news: Kazakh has become one of the fastest-growing languages on ChatGPT. It is easy to dismiss that as an interesting statistic. But perhaps it represents something larger. In the age of AI, language is no longer only a question of identity. It increasingly becomes a question of participation. Cultures that exist inside AI systems will inevitably have a stronger voice in shaping how those systems understand humanity itself.
Education raises a similar challenge. Ron believes our schools are still largely organized around the needs of an industrial economy, preparing students for stable careers inside systems that may not exist in their current form within a generation. Brett goes even further. He says that philosophy, psychology, ethics and lifelong learning may become just as important as engineering because the defining skill of the AI era will not simply be coding. It will be adaptation.
After months of interviewing futurists, I have come to think that AI is asking governments a surprisingly old question. Not whether they can innovate faster than everyone else, but whether they are capable of imagining a future that does not yet exist and preparing for it anyway. No one knows what the AI economy will ultimately look like. Predictions differ, technologies evolve faster than policies, and history has a habit of humbling even the most confident forecasts. There is no guarantee that every initiative launched today will produce the intended outcome. But perhaps that is not the point. The point is that waiting for certainty may no longer be an option.
Looking at Kazakhstan today, what I find noteworthy is less the technology itself than the shift in thinking behind it. AI is no longer being discussed simply as another digital industry or another innovation agenda. Increasingly, it has become part of a broader conversation about education, institutions, public administration and the country’s long-term economic direction. Whether through AI-Sana, investments in computing infrastructure, the development of Alem.ai, or recent efforts to integrate AI across government, the common thread is an attempt to prepare before the transition becomes unavoidable.
Perhaps that is what leadership will increasingly mean in the age of AI: not the ability to predict every technological breakthrough, but the willingness to create the conditions for a country to adapt to profound uncertainty. Kazakhstan appears to be making that bet today, investing in institutions, education and digital capacity before anyone can say with confidence what the AI economy will ultimately look like.
