IN China, people are being paid to fold clothes, wipe tables, and open microwave doors. Wearing virtual reality headsets and exoskeletons, they repeat the movements hundreds of times so humanoid robots can learn them. Across China, similar centres have people performing other painfully ordinary tasks. The work looks mundane, but it produces precious data.
It may seem like an odd way to begin a story about geopolitics, but like this piece, it offers important clues about who is better placed to ‘win’ the AI race — China or the US? The winner will have a much larger say in the next world order.
Donald Trump insists America must win the AI race, a contest his administration has likened to the Cold War’s ‘space race’. The analogy is attractive, but Michael Kratsios, Trump’s science adviser, later conceded the obvious problem. Unlike the race to the moon, this one has no finish line.
On the conventional scoreboard, the US remains formidable. Stanford’s 2026 AI Index counts 59 notable American models in 2025 against China’s 35. US private AI investment exceeded China’s 23 times over, though this understates Chinese spending through government funds. Yet the report says the model performance gap has “effectively closed”, as of March 2026, the leading US model was ahead by just 2.7 per cent.
Pakistan does not need to win the AI race. It needs to win from AI.
Frontier models are not the only measure of success. China may be building its advantage by pushing AI into the physical economy.
In March, the US China Economic and Security Review Commission ‘warned’ of a reinforcing loop in China. Cheap, open models spread into factories, logistics, and robotics. Their use generates specialised real-world data, which then improves the models. That could create an advantage proprietary American systems may struggle to match, even if they remain stronger on benchmarks.
Most importantly, China had classified data as a factor of production in 2020. Factories are paid for access to workers wearing cameras and sensors, while others earn money performing household tasks to train robots.
On the flip side, America’s AI boom grew out of an internet economy built on years of accumulated online content and behavioural data, where major platforms are accused of “vast surveillance” by the FTC, with users having little control over their data’s use.
I am not suggesting China has a better privacy regime. It does not. The point is that China is producing, pricing, and feeding data back into industry, building an ecosystem that could give it an immense edge over the US.
And it already has the machinery. China had more than two million industrial robots operating by 2024 and installed 354,000 in 2025 alone. According to the International Federation of Robotics, China accounted for 59pc of new industrial robot installations worldwide in 2025. The real advantage may, therefore, be the ecosystem itself, ie, factories produce robots, robots produce data, data improves AI, and AI improves factories.
Then comes energy, as I argued earlier in these pages. The International Energy Agency (IEA) expects data centre electricity use to nearly double to 950 terawatt-hours by 2030. Whoever can expand reliable, affordable power fastest will have an edge in building the AI ecosystem.
In the US, data centres are expected to account for nearly half of electricity demand growth to the end of the decade, while natural gas supplies more than 40pc of their electricity. Grid delays are pushing developers towards on-site gas generation. But the IEA says ensuring reliable supply requires generating capacity 30pc to 70pc above demand, while turbine shortages may undermine hopes of getting power faster.
To its advantage, China accounts for around 85pc of global solar supply chain production capacity and 80pc of lithium-ion battery capacity. It added nearly 500 gigawatts of renewable capacity in 2025 alone.
The idea isn’t to romanticise the figurative ‘Chinese model’, considering they still use coal to supply nearly 70pc of the electricity used by Chinese data centres. But their advantage is clear. China manufactures much of the machinery needed to generate and store the next unit of electricity.
However, China still faces weaknesses. It depends on foreign technology across parts of the semiconductor chain, while restrictions on advanced memory are raising domestic chip costs. Chinese firms are nevertheless developing alternatives to Nvidia, seeking to make AI deployment more affordable and reduce dependence on American hardware. The US retains substantial advantages in frontier research, Nvidia’s computing ecosystem and capital, but China is building more of the hardware and software needed for its own ecosystem.
The contest is also moving beyond the two countries. America’s AI Action Plan explicitly seeks to export full-stack US technology packages, including hardware, models, software and standards, whereas China is pushing open models and a competing international architecture.
To summarise, if I had to pick a likely winner in the figurative AI race, I would lean towards China. Its advantage may lie in how effectively it turns AI into industrial strength and economic productivity.
But the obvious question remains: Where does that leave Pakistan?
Pakistan should resist that pressure to choose sides and rethink what it means to become a regional AI leader. Competing in frontier chips, foundation models and vast data centres requires an industrial base we lack. Our scarce resources should go where they can make the greatest difference.
As I argued in ‘Pakistan’s AI checklist’, published in this paper in June, we need reliable power, computing capacity, local hosting for sensitive data, skilled people, local datasets, and rules that protect rights. We should use global tools where they help and build our own capacity where dependence leaves us vulnerable. The purpose of this investment must be clear.
I have said this earlier as well. Pakistan does not need to win the AI race. It needs to win from AI. Helping farmers conserve water, teachers identify learning gaps, businesses become more productive, and public departments reduce waste would achieve more than another announcement about becoming an AI hub.
China’s lesson is that technology becomes power when it translates into productivity. Our greatest risk is becoming little more than a market for systems built elsewhere, with too little capacity to shape how they serve us.
The writer is the founder of Media Matters for Democracy.
Published in Dawn, October 14th, 2026