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Green AI and energy transition: an agenda for the C-Level

My Tech Plan 4 min read
IA verde y transición energética: una agenda para el C-Level

Artificial intelligence has positioned itself as a central element to accelerate the energy transition and meet climate commitments. But beyond the discourse, what differentiates leading organizations is how they integrate green AI into their strategic core: not as a one-off tool, but as a system for decision-making, efficiency, and regulatory compliance. A KPMG report reveals that more than 70% of executives already consider it essential to achieve their ESG goals.

From ambition to execution: AI as a lever for sustainability

The true impact of AI on sustainability is not limited to cost reduction. The companies that manage to capture real value are those that integrate it into the core of their business, generating energy efficiency, environmental traceability, and new innovation opportunities. According to McKinsey, only 39% of companies have scaled AI with a measurable impact on EBIT. This is a fact that highlights the gap between strategic enthusiasm and effective execution.

The challenge lies in prioritizing high-return use cases: automation of ESG reports, energy optimization in factories, climate simulations for decision-making, or logistics with a smaller carbon footprint. An illustrative example is Carbon Re, a startup that uses deep learning models to reduce energy consumption in the cement and glass industries, sectors with high emission intensity. Its platform adjusts operating parameters in real time to maximize efficiency without compromising production. It is sustainability with economic impact.

Green AI: more than efficiency, a governance obligation

The growth of AI also poses an energy dilemma. Data centers already consume 1.5% of the world’s electricity, and their demand will continue to rise. Adopting a green AI strategy is not optional: it requires choosing more efficient models, limiting the use of high-consumption algorithms except in justified cases, and demanding transparency from cloud providers about their footprint. UNESCO has warned about the collateral environmental effects of the indiscriminate expansion of AI without sustainability criteria. This is where top management must exercise leadership: establish technology selection criteria that incorporate energy metrics, and align investment in AI with decarbonization commitments.

Regulatory compliance: the CSRD accelerates the ESG digital transformation

The new European CSRD directive requires more than 50,000 companies to accurately report their environmental, social, and governance impacts. This regulatory framework requires full traceability, metrics on Scope 3 emissions, and risk assessment. In this context, AI is not a competitive advantage: it is an operational necessity. Companies must automate data capture and analysis, and structure auditable reports. Those who do so quickly will be in a better position with investors and auditors, reducing their reputational risk and their cost of capital.

Where is the ROI of AI in sustainability?

It’s not just about efficiency. The true return on AI lies in its ability to reduce exposure to risks, anticipate regulatory scenarios, improve corporate reputation, and accelerate new sustainable business models. Microsoft estimates a potential ROI of 350% in well-designed projects. The key is to measure beyond savings: value the impact on compliance, the reduction in the cost of capital, and the robustness of the data for ESG audits. ESG metrics become indirect financial indicators, increasingly relevant for stakeholders.

Priorities for the C-Level: vision, control, and scale

To move forward, top management must assume an active and systemic role. Five actions make the difference:

  • Formalize AI governance under the CEO’s leadership.
  • Prioritize initiatives that comply with CSRD and reduce indirect emissions.
  • Apply green AI principles in each new implementation.
  • Redesign workflows to integrate AI as an operating system, not as a patch.
  • Demand an ESG ROI from each project that combines profitability, risk, and reputation.

The future will belong to organizations that connect technology with purpose and execute with coherence.