The AI Race

The first general-purpose technology since electricity to be governed by export controls before deployment.

The brief

By 2022, generative AI models were performing tasks that had long served as markers of human intelligence in computing: large language models could write essays and code and hold open-ended conversations; diffusion models could generate images. The release of ChatGPT that November was estimated to reach a hundred million monthly users inside two months — one of the fastest consumer adoptions on record. By 2025 the leading systems were passing graduate professional examinations, contributing meaningfully to mathematics research, and spreading through white-collar workflows. The pace of capability gain caught much of the field, including many of the researchers building the systems, off guard.

The technology has moved, almost from the start, into a geopolitical frame. The training of frontier models requires the largest data centres ever built, vast quantities of high-end semiconductors (most designed in the US by Nvidia and fabricated in Taiwan by TSMC), and electricity at the scale of small countries — a supply chain whose chokepoints concentrate in a handful of firms and one geopolitically exposed island. The United States has imposed sweeping export controls — from October 2022 onward, tightened repeatedly — on the most advanced chips and a broad range of specialized semiconductor-manufacturing equipment needed to make them, including lithography systems led by the Dutch firm ASML, to slow Chinese progress; China has responded with a state-directed industrial policy of unprecedented scale to achieve self-sufficiency, while open releases like DeepSeek showed in early 2025 that the gap was narrower than assumed and that algorithmic efficiency could partly route around hardware bans; the European Union has chosen to regulate first with the AI Act and, through the mid-2020s, was being lapped by both on frontier capability. The strategic stakes are not subtle: if AI continues to accelerate, the country whose firms lead may compound advantages in productivity, military capability, and scientific research at rates the international system has not previously had to absorb. The downside risks — systemic accidents, deliberate misuse, alignment failures, mass displacement of cognitive labour — are also being actively negotiated, in public and in private, more or less for the first time in real time, by people who concede they do not fully understand what they have built.

Why nowAI is becoming a general-purpose technology, and its deployment is being shaped by export controls, treaty negotiations, and national-security review before its full economic and social effects have arrived. The compute build-out alone — hundreds of billions in data centres, straining power grids — is reordering capital markets and energy policy. Whether it is governed well, or at all, will be one of the defining stories of the next decade.