Summary
Artificial intelligence (AI) is more than just new technology—it’s changing how money, energy, natural resources, jobs, and political influence are divided across the world. The authors explain how a few companies and countries are gaining more control over AI development and infrastructure, creating new demands on resources like electricity and water. AI’s impact on the environment can be both good and bad, as it uses resources but can also help improve energy efficiency and climate monitoring. Lastly, AI changes jobs by automating some tasks and creating new opportunities, with broader social impacts depending on policies and regulations.
What this means in practice
- •For policy makers: Design policies to manage AI’s effects on infrastructure, environment, and labor markets considering concentrated corporate and national control.
- •For energy planners: Plan for growing energy and water demands caused by expanding AI data centres to avoid local resource bottlenecks.
A position paper. It proposes an approach and reports no results.
Abstract
The rapid development of artificial intelligence is often discussed primarily as a technological breakthrough. Such an approach is insufficient because AI is also transforming the allocation of capital, energy, natural resources, labour, and political power. Investment in generative AI and computing infrastructure is increasing rapidly and is increasingly concentrated among a small number of corporations and countries. At the same time, the expansion of data centres creates new electricity and water demands, potentially producing local infrastructure bottlenecks and distributive conflicts. The AI value chain is dependent on geographically concentrated supplies of advanced semiconductors, manufacturing equipment, cloud services, energy, and specialised knowledge. Control over these bottlenecks may give states and corporations structural power that does not derive directly from military superiority. The environmental effects of AI are similarly ambivalent: AI systems consume energy, water, materials, and computing hardware, but may also improve energy efficiency, climate modelling, renewable-energy integration, and environmental monitoring. Finally, AI-enabled automation, including intelligent robotics, may reduce employment in some occupations while augmenting labour and creating new tasks in others. The social outcome of this transformation will therefore depend not only on the technology itself but also on competition policy, infrastructure planning, environmental regulation, social protection, collective bargaining, and the distribution of productivity gains.