Artificial intelligence is long past being a laboratory curiosity: today it is becoming the foundation of a new economy. The key is not just the technology, but entire ecosystems – from data and chips to startups and platforms – that states are deliberately building. What does global practice show and why is the pace of change accelerating sharply?
From isolated research to ecosystems
The speaker recalled that AI has been worked on for decades, but only recently has it entered widespread practice. A telling contrast is the difference between the long-standing foundations on which neural networks rest and the lightning-fast advances brought by, for example, modeling protein folding. The point: new discoveries emerge faster when they build on established knowledge and AI tools.
Where it once involved isolated teams, today AI rests on interconnected ecosystems: hardware, cloud, data, large companies, fast-growing firms, and local startups. The lesson from the Silicon Valley story is that a breakthrough environment does not arise from a single investment, but from long-term collaboration among universities, the state, and entrepreneurs in specific domains. Such ecosystems gradually give birth to entirely new industries – and the time needed to do so is being compressed from decades to a few years.
The race among countries: investments, capacity and partnerships
Across the world, governments are announcing billion-dollar plans for AI and infrastructure; this is especially evident in countries in Asia and the Middle East. Capital first brings quantity – teams, projects, compute – but over time also quality and scalable outcomes. Rankings of digital services show that alongside traditional leaders, countries such as the United Arab Emirates, Malta, and Denmark are rising quickly.
Hard capacity also matters: annual capital expenditures on cloud now match the historical spending of major space programs. Building top-tier AI data centers is extremely expensive – estimates run up to around $1.5 billion per facility – so partnerships and shared platforms are a more realistic path than isolated projects. The lesson from practice: instead of closed "catalogs of solutions," an open ecosystem, open interfaces, working with data, and collaboration with the private sector work better.
Platforms and productivity: what's coming to government offices and businesses
Those who build platforms perform best – from ministries of culture or tourism to standalone agencies – so that other players can plug into them. Deployments are growing, from call centers and automated responses through document summarization to "copilots" that help people in their everyday work. History shows that breakthrough technologies raise productivity, and AI has the potential to deliver another leap, which is important for aging societies with labor shortages.
Data from pilots suggest that AI agents can handle a large share of inquiries, and in some medical studies they achieved surprisingly high diagnostic accuracy without human intervention. Alongside the promising numbers, however, come ethical and practical questions: where to allow AI to make autonomous decisions, how to deal with bias, and what to leave to humans. As the lecture’s author said, if the technology is to push the boundaries, it has to feel "a bit like magic" – but with clear rules and accountability.
