Generative AI for Sustainable Business Strategy: Can AI-Powered Decision-Making Improve Corporate Resource Efficiency and Environmental Performance?

Generative Artificial Intelligence (GenAI) is increasingly being incorporated into business planning, knowledge work, operational analytics, and decision support. Its sustainability value, however, cannot be inferred from productivity gains alone because AI systems also require electricity, computing infrastructure, water, hardware, and other resources. This study develops an evidence-based framework for examining whether GenAI-enabled decisionmaking can improve corporate resource efficiency and environmental performance. It distinguishes direct AI resource impacts from indirect efficiency benefits and evaluates five decision pathways: energy optimization, material and waste reduction, supply-chain resource allocation, water management, and sustainability reporting. Empirical evidence indicates that AI adoption can improve enterprise environmental performance through productivity improvement, pollution-control investment, and factor-input optimization. Evidence from building-energy research estimates potential reductions of approximately 8–19% in energy consumption and carbon emissions by 2050 under specified AI adoption scenarios. At the same time, the International Energy Agency reports that data centres consumed approximately 415 TWh of electricity in 2024, around 1.5% of global electricity consumption, demonstrating the resource burden associated with digital infrastructure. The findings therefore support a conditional rather than automatic sustainability effect: GenAI can contribute to resource efficiency when its decision benefits exceed the environmental burden of computation and when organizations implement data governance, measurement, human oversight, and sustainability controls. The paper proposes a Resource-Efficiency Decision Index, equations for avoided resource use and net environmental benefit, an evidence matrix, scenario analysis, and a managerial governance framework for integrating GenAI into sustainable business strategy.