The relationship between artificial intelligence and sustainability is intensifying rapidly. AI is now a core economic enabler, automating decisions across finance, logistics, procurement, energy systems, and compliance. But its power depends entirely on the quality of the underlying data. Where sustainability data is robust, AI can dramatically improve forecasting, optimise energy grids, strengthen climate adaptation, and enhance management of water, agriculture, and supply chains. New technologies offer to lift data beyond the control of any one actor, and to make knowledge about the prevalence and root-causes of social and environmental impacts a pre-competitive issue. However, AI’s growing physical footprint—soaring electricity and water consumption, rising demand for critical minerals, and mounting e-waste as data-centre infrastructure expands at hyperscale—cannot be ignored. For all its benefits, AI can also amplify inequality, embed opaque decision-making, and lock in flawed assumptions at speed, making governance essential before systems become irreversible. AI is both a sustainability tool and a sustainability risk: its impact will depend on the rules, incentives, and safeguards put in place now.