Artificial intelligence is transforming how businesses operate, innovate, and scale. But as AI adoption accelerates, so does its appetite for energy. A new survey by The Conference Board highlights a growing contradiction in corporate strategy: while AI is driving the largest surge in US electricity demand in decades, environmental sustainability remains a secondary concern in most responsible AI frameworks. The findings raise critical questions about how companies are balancing innovation, growth, and environmental responsibility.
Sustainability takes a back seat in AI decision-making
According to the survey, only a small fraction of corporate sustainability leaders consider environmental impact a core pillar of their AI strategy. Just 13 percent of respondents say sustainability is a major consideration, while over 40 percent view it as a minor issue or not a priority at all. For many organisations, concerns around ethics, bias, safety, and cybersecurity continue to dominate AI governance conversations, pushing environmental impact further down the list.
This disconnect is striking given the scale of AI’s growing footprint. As data centers expand and computing power intensifies, energy consumption and emissions are becoming harder to ignore.
The rapid expansion of AI-driven data centers is at the heart of the issue. Hyperscale facilities built to support AI and cloud workloads have doubled globally in the past five years, with a significant concentration in the United States. These facilities consume enormous amounts of electricity and water, contributing to greenhouse gas emissions and local resource stress.
Survey respondents identified data center energy demand, electricity consumption, and emissions as their top environmental concerns related to AI. Water use also emerged as a growing issue, particularly as cooling requirements increase. Beyond operational energy use, AI places pressure on supply chains through resource-intensive hardware production, land use for construction, and rising electronic waste from frequent hardware upgrades.
AI as both problem and solution
Despite these challenges, the survey also reveals that companies recognise AI’s potential to support sustainability goals. More than 60 percent of surveyed leaders are already using AI for environmental objectives, most commonly for sustainability reporting and disclosure. Tools for carbon accounting, emissions tracking, and climate risk analysis are gaining traction, helping organisations improve data accuracy and transparency.
However, these applications represent only the early stages of AI’s sustainability potential. High-impact operational uses, such as energy optimisation, logistics efficiency, and water management, remain underutilised. Experts note that these areas offer the greatest opportunity for AI to deliver measurable environmental benefits.
AI can play a significant role in reducing environmental impact when applied directly to operations. Intelligent energy management systems can identify inefficiencies and reduce consumption. AI-driven logistics and fleet routing can cut fuel use and emissions. Advanced tools using machine learning and remote sensing are already improving flood forecasting, waste sorting, and recycling outcomes in select regions.
Yet adoption of these applications remains limited. Many organisations are still focused on compliance and reporting rather than leveraging AI to redesign processes and systems for sustainability at scale.
The Conference Board’s findings underscore a pivotal moment for corporate AI strategy. As AI continues to drive unprecedented growth in electricity demand, companies face a choice: treat sustainability as an afterthought, or integrate it into the core of responsible AI governance. The real opportunity lies in adopting a dual approach—actively managing AI’s environmental footprint while harnessing its power to accelerate sustainability outcomes. In the years ahead, leadership will be defined not just by who deploys AI fastest, but by who deploys it most responsibly.
