From Paradox to Progress A Net Positive AI Energy Framework 2025

Next steps and call to action The path to achieving net-positive AI energy is clear, but it requires coordinated, cross-sector action. The time to move from insight to implementation is now. Whether a technology provider, manufacturer, utility, policy-maker or academic institution, the following are immediate steps that can be taken: Short term (0–12 months): –Assess your AI energy and material footprint: Conduct AI system life cycle analyses, including training, deployment, infrastructure and embedded materials. –Benchmark and disclose: Establish transparent reporting standards and contribute to open data repositories. –Design for efficiency: Prioritize energy-efficient hardware, modular data centre design and model optimization. –Shape demand wisely: Educate users, implement pricing models and embed energy- conscious defaults into platforms. –Submit your use case: Strengthen the Forum’s public repository40 of best practices showcasing the business case for net-positive AI energy by submitting your use case using the Global AI Energy Impact Industry Use Case Submission Form. While the current inventory provides valuable insight into emerging innovation, it is not yet fully globally representative. Expanding it will enable broader representation, deepen collective understanding, and help accelerate global progress. Middle term (one to three years): –Deploy for impact: Integrate AI into efficiency strategies across operations, supply chains and infrastructure. –Collaborate across sectors: Join multistakeholder taskforces like the AI Energy Impact initiative, align with regional frameworks, and co-invest in shared infrastructure. –Invest in talent and consumer education: Launch AI energy literacy programmes, reskilling initiatives and university partnerships. Long term (more than three years): –Scale what works: Replicate high-impact use cases across geographies and sectors leveraging resources like the Forum’s upcoming AI Energy Foresight tool. –Advance standards and governance: Support the development of enforceable global AI energy accountability frameworks.41 –Drive innovation: Invest in next-generation technologies (e.g. neuromorphic computing, quantum AI) that reduce energy intensity. Final call AI is a strategic lever for competitiveness, resilience and climate action. Yet, without intentional design, governance and collaboration, its energy footprint could undermine the very progress it enables. Time will tell which trajectory prevails, steady transformation or speculative overshoot, and continued research must guide this balance as the ecosystem evolves. The current ecosystem marks a critical tipping point for shifting from growth-first to impact-first AI, not as a moral imperative, but as a strategic necessity. Scaling AI systems that are resource-efficient and aligned with energy realities can unlock new pathways to profitability, competitiveness and resilience. Achieving a net-positive AI energy future will not happen by chance; it requires intentional design, deliberate collaboration and purposeful scaling. From Paradox to Progress: A Net-Positive AI Energy Framework 33