AI Environmental Impact Gets Limited Focus in US Firms’ Strategies

AI’s Growing Environmental Footprint Fails to Register on Corporate Radars

A striking disconnect has surfaced between corporate artificial intelligence adoption and environmental sustainability priorities, according to a new study. Research from The Conference Board, detailed in a report by a leading media house, reveals that only 13% of sustainability leaders consider environmental impact a “major consideration” in their companies’ responsible AI strategies. This oversight persists even as the massive computational demands of AI systems drive significant increases in energy and water consumption. For many enterprises, pressing issues such as ethics, bias, and data security continue to dominate the responsible AI discussion, effectively pushing ecological concerns down the agenda. The findings suggest that the corporate world’s rapid embrace of AI-powered efficiency is proceeding without a corresponding commitment to managing the technology’s substantial resource demands.

The data paints a clear picture of corporate priorities. Close to one-third (31%) of sustainability executives openly admit that environmental considerations rank behind other concerns in their responsible AI rollout plans. More concerning still, 42% reveal that ecological impact is either a minor consideration or not considered at all within their AI governance frameworks. Only a small fraction of companies — just 4% of those surveyed — have made sustainability a core pillar of all their responsible AI initiatives. Another 9% treat it as a major, but not primary, focus. This governance gap indicates that while companies are eager to harness AI’s potential for profit and innovation, they are less attentive to the external environmental costs associated with its deployment.

Primary Environmental Concerns: Energy Demand and Water Use

When corporate leaders do consider AI’s environmental effects, their concerns are overwhelmingly focused on energy. The report identifies data centre energy demand as the top concern, cited by 63% of respondents. General energy consumption follows closely at 58%, while 56% of leaders express concern about emissions resulting from electricity use for AI operations. Water use, a critical but less publicised resource issue linked to cooling massive server farms, is a concern for 37% of sustainability professionals. These figures highlight a growing awareness of the direct operational impacts of running increasingly complex AI models, which require vast quantities of power for computation and cooling.

According to the analysis by The Conference Board, featured in coverage by a leading media house, rising resource demand is becoming difficult to ignore. Andrew Jones, senior researcher and author of the report, notes that data centres already account for a growing share of US electricity demand, with water use rising in tandem as AI workloads scale. As AI investment continues at a record pace, its environmental footprint is becoming impossible to overlook. Jones argues that leading companies in 2026 will be those that adopt a “dual lens”, actively managing AI’s substantial resource appetite while simultaneously deploying the technology to accelerate their own sustainability goals.

AI as a Tool for Sustainability, Not Just a Challenge

Despite the apparent strategic gap, the report identifies a notable trend: companies are actively using AI to advance their environmental objectives. Three-fifths (60%) of sustainability leaders report deploying AI to achieve specific environmental goals. The most common application is for disclosure and reporting tasks, used by 34% of companies. This indicates that AI is primarily viewed as an administrative tool for managing sustainability data rather than an operational mechanism for direct environmental improvement.

Beyond reporting, applications are gradually diversifying. Approximately 22% of companies use AI to support carbon accounting and emissions tracking, enabling more accurate and efficient measurement systems. Another 15% employ the technology for climate risk modelling and scenario analysis, helping organisations anticipate and prepare for environmental disruptions. A further 12% use AI to monitor circularity, waste, and water management within their operations. Brian Campbell of The Conference Board Governance & Sustainability Centre observes that while early applications are centred on reporting, the highest-value opportunities lie in emerging operational uses that could deliver far greater environmental impact. AI’s environmental narrative, he notes, is not only about its footprint but also about its potential as a powerful tool for sustainability performance.

The Path Forward: Integrating Sustainability into AI Governance

The survey, which gathered responses from more than 60 corporate sustainability leaders at large US and multinational companies, ultimately highlights a critical turning point. The business world stands at a crossroads where a transformative technology presents both significant risks and substantial opportunities for the planet. At present, the prevailing corporate approach treats AI’s environmental dimension as a secondary concern — an externality to be addressed later, if at all. This reactive stance risks locking in high-emission, resource-intensive technological infrastructure for years to come.

The report implicitly calls for the strategic integration of sustainability principles into the foundation of corporate AI programmes. This would involve embedding environmental impact assessments from the initial design phase of AI systems, investing in more energy-efficient hardware and algorithms, and prioritising renewable energy sources to power data operations. The vision outlined is one in which companies do not choose between technological advancement and environmental responsibility but pursue a strategy that harnesses AI’s capabilities to address sustainability challenges while rigorously minimising its own footprint. The success of this integration is likely to shape not only corporate performance but also the broader environmental trajectory of the digital economy.