Dr Francesco Fuso Nerini of the Environmental Change Institute (ECI) argues that the rapid rise of generative artificial intelligence presents a major opportunity and a critical policy challenge: ensuring economic gains are shared fairly and directed towards global public priorities.
Writing in Nature Machine Intelligence, he highlights that generative AI could create trillions of dollars in annual value, but warns that without deliberate intervention, those benefits are likely to be concentrated among a small number of companies and countries. This risks widening global inequality while limiting AI’s potential contribution to pressing challenges such as climate change, poverty reduction, and sustainable development. Dr Fuso Nerini said:
We need an AI economics capable of addressing three intertwined dynamics: the unprecedented wealth AI could create, the risk of widespread job losses, and slow progress towards environmental and social goals.”
In the piece he notes that while AI is already being used to augment human work rather than fully replace jobs, longer-term impacts on labour markets could be substantial, potentially affecting a significant share of global employment. This raises questions about how societies structure work, value creation, and redistribution in an AI-driven economy.
The paper outlines two broad approaches to addressing these challenges. The first is “top-down” policy action, including windfall taxes on extraordinary AI profits, social wealth funds, data governance reforms, and voluntary corporate profit-sharing mechanisms. These approaches could help governments capture part of AI-generated wealth and redirect it towards public goods.
However, Dr Fuso Nerini cautions that such mechanisms are often limited by national boundaries and uneven political feasibility. He suggests that additional international approaches may be needed, including voluntary contributions from leading AI firms and alignment with existing global financing mechanisms for development and climate action.
The second, more novel proposal is a “bottom-up” system in which individuals and organisations are rewarded for verified contributions to socially and environmentally beneficial work. This would combine AI-assisted evaluation with peer review and transparent reporting systems to assess contributions such as ecosystem restoration, community health initiatives, or food distribution.
Under this model, funding could be linked to AI-generated wealth, philanthropic pools, or matching funds, enabling what he describes as a new form of “public value remuneration” that could operate across borders and support global priorities such as the UN Sustainable Development Goals.
Dr Fuso Nerini, Honorary Research Associate at the ECI and Professor at KTH Royal Institute of Technology, argues that such systems could complement traditional labour markets in a future where AI significantly reshapes work, helping ensure that productivity gains translate into measurable social and environmental benefits rather than concentrated private wealth.
He concludes that governments, companies, and researchers have a narrow window to design governance frameworks that ensure AI advances global public goods. Without such action, he warns, the economic benefits of AI risk reinforcing existing inequalities rather than addressing them.
Read the full article in Nature Machine Intelligence: AI economics for the common good