65 global leaders share how to scale AI responsibly over the next decade

The World Economic Forum Annual Meeting 2026 in Davos, Switzerland, convened at a defining moment in the global conversation on artificial intelligence (AI) and energy system sustainability.

Across sessions held before and during the event, industry experts, Young Global Leaders and members of the Forum’s AI Energy community, spanning technology, energy, policy and investment sectors, came together to address a defining question: can the world achieve a net positive AI energy future by 2035?

Almost two-thirds of voices across these dialogues said “yes” but only if the world acts now to align AI’s exponential growth with energy transformation, resilient infrastructure and equitable governance.

Achieving a net positive AI energy future where AI’s resource efficiencies outweigh its consumption will require a new form of leadership that aligns the use of finite resources with economic competitiveness, transparency with innovation and investment with long-term resilience.

Feedback from recent cross-industry dialogues underscored the need for a shared “North Star” vision for AI over the coming decade, positioning “efficient and clean-powered intelligence” as a catalyst for energy transition, resilience and competitiveness.

This vision reframes AI from a sustainability burden into a strategic enabler of business, energy system efficiency and its security.

“It challenges both companies and governments to treat sustainability not as a corporate responsibility exercise but as a strategic lever for market advantage and energy independence,” said one leader from the financial services sector.

Innovations demonstrate that AI can be an energy consumer and an energy optimizer. Examples include Google’s commitment to carbon-free procurement and transparent reporting of water use, and Crusoe’s 1.8-gigawatt carbon-capture-enabled data centre in Texas.

“As AI adoption accelerates, access to clean, resilient, and rapidly deployable power is becoming as foundational as the AI models themselves,” said Natalie Sunderland, chief marketing officer at Bloom Energy.

“The organizations that thrive will be those who treat sustainable energy not as a constraint on innovation but as the engine that powers speed, scale, and competitiveness in the digital age.”

The real risk, leaders note, isn’t AI’s growth itself but unchecked growth. When designed for impact, AI can become a force for energy and economic resilience. Capital flows will determine how quickly such solutions scale.

Cross-sector leaders urged redirecting investment toward enabling technologies such as smart grids, energy storage and retrofitted data centres. Policy-driven incentives and blended public-private models can de-risk infrastructure modernization while ensuring equitable participation.

Global leaders across industries agreed that no single company or country can achieve net positive AI alone. A net-positive AI future depends on shifting from pilots to scaled, measurable outcomes.

As Rene Haas, chief executive officer at ARM, said during the Annual Meeting 2026, “AI is moving so quickly… it’s going to require a level of innovation that we haven’t yet seen.”

The path forward will depend on collaboration across technology, energy and policy ecosystems, forming coalitions that connect data centres, utilities and digital innovators under shared scaling and deployment goals.

“Without electricity, there can be no AI and without stronger, smarter and greener grids, there will be no electricity to feed the growing needs of power-hungry datacentres,” said Harmeet Bawa, group senior vice president at Hitachi Energy.

Potential coalitions could accelerate collective action through renewable energy procurement commitments, open data sharing and aligned accountability frameworks.

Initiatives such as 24/7 carbon-free energy agreements and the Forum’s recently launched AI Energy Foresight Tool exemplify how shared repositories of real-world use cases can help organizations benchmark and scale proven solutions.

“Building continuous learning networks, from adaptive policy sandboxes to peer exchanges and shared metrics, will be essential for scaling success and embedding trust across industries and borders,” shared Jeffery Preece, vice president of Energy Supply at EPRI.

Additionally, clear and harmonized standards will determine whether responsible AI scaling becomes the global norm.

Global leaders called for common frameworks on energy efficiency, carbon intensity, and renewable integration, supported by real-time reporting and independent verification. Shared data systems between the AI and energy sectors can enable organizations to align operations with sustainability targets dynamically, rather than retrospectively.

Open data expectations for large-scale infrastructure, cross-border standards for energy measurement, and transparent emissions accounting are the foundation for scaling trust alongside innovation.

“AI can solve its own energy crisis through flexibility. Transforming AI data centres from liabilities to power-flexible grid assets can unlock hundreds of gigawatts of stranded power, lower energy bills for communities, and accelerate AI infrastructure and innovation,” said Dr Varun Sivaram, CEO and founder of Emerald AI.

Beyond industry partnerships, leaders also called for participatory governance, involving policymakers, academia, and civil society, in the co-design of regulatory sandboxes. This approach enables adaptive learning while maintaining trust, accountability and inclusive innovation.

“Achieving a net-positive AI energy future requires pairing technological ambition with transparent, coordinated action. This mirrors the AI lifecycle itself, starting with big, versatile AI tools to uncover opportunities, then turning those insights into smaller, energy-saving solutions ready for deployment,” said AVEVA’s chief technologist Arti Garg.

Bold leadership will determine AI energy pathways from now to 2035, which could conceptually be defined by one of four AI scaling trajectories:

While the current trajectory remains uncertain, these scenarios offer a useful framework for understanding the range of futures that may unfold. Around 65% of recent cross-industry discussions expressed optimism about achieving a net positive AI energy future by 2035. Across this, consensus formed around several imperatives for short to long-term action:

According to C4IR Azerbaijan Head, Fariz Jafarov, “Immediate next steps should include contributing peer-learning examples with measurable results to open repositories such as the Forum’s AI Energy Impact database and joining collaborative networks like the AI Energy Impact Initiative.

“Over the longer term, there is a shared commitment to co-invest in Industry 4.0 solutions, co-develop global frameworks for industrial AI, and accelerate the integration of AI, data, and digital technologies to enable more efficient, resilient, and low-emission energy and industrial systems.”

Progress towards net positive AI will be a test of leadership. Those who rise to it will prove that scaling AI responsibly is not just compatible with global energy goals but also a source of lasting competitive advantage, essential to achieving them.