Navigating the Intersection of AI and Climate Change: A Call to Action for Responsible Innovation

The False Tradeoff: AI or Climate Action

1. Start with a Digital Carbon Audit

2. Consider AI Solutions to Cut Carbon and Costs

3. Right-Size Your AI for a Low-Carbon Future

4. Build a Culture of Climate-Smart AI Innovation

This Is the Leadership Moment

Navigating the Crossroads of AI and Climate Change

We are living in a rare moment in human history where two powerful forces—artificial intelligence (AI) and climate change—are reshaping our future simultaneously. One promises exponential progress, while the other demands urgent corrective measures. As cities grapple with stormy clouds of uncertainty, it’s crucial to understand how these twin forces impact our world.

Image by Nahil Naseer on Unsplash

Generative AI isn’t merely about automating tasks; it is redefining who we are as workers, creators, and decision-makers. Futurist Ray Kurzweil predicts human-level AI by 2029, anticipating a merging of human and machine intelligence within our lifetimes. However, voices like Eliezer Yudkowsky warn that the rapid advancement of AI may outpace our ability to align it with human values.

Simultaneously, attempts to treat climate change as background noise are failing. NASA and the World Meteorological Organization (WMO) recently confirmed that 2024 surpassed 2023 as the warmest year on record since global data collection began in 1850. We are witnessing increased frequency and severity of climate-related weather events, with dire consequences for people, economies, and ecosystems.

Each force—one environmental, the other technological—represents an inflection point. Can we afford to ignore one in pursuit of the other?

False Tradeoff: AI or Climate Action?

A World Economic Forum survey of 1,000 top employers reveals that 86% expect AI to rapidly transform their industries. AI can accelerate climate solutions, enhancing everything from smarter energy grids to real-time pollution tracking. However, its contribution to rising energy demand and emissions through significant computational needs cannot be ignored. According to the International Monetary Fund (IMF), data center electricity usage could match India’s by 2030.

Climate impacts are already reshaping supply chains and business strategies. A Deloitte survey of 2,100 executives found that 70% experienced climate-related disruptions necessitating strategy resets. The European Union is responding with mandates like the Corporate Sustainability Due Diligence Directive (CSDDD), which requires large companies to address their environmental and human rights impacts, including those related to AI.

As organizations race to adopt generative AI while fulfilling climate pledges, these forces often seem at odds. Can business leaders navigate AI innovation while maintaining sustainability?

Here are four actions to consider.

1. Start with a Digital Carbon Audit

Every digital tool—from cloud storage to AI models—creates a carbon footprint. By measuring the impact of AI workloads, especially in model training and deployment, organizations can make informed decisions. Companies like Mistral AI are leading the way by publishing carbon audits that quantify emissions from training and inference processes.

Tools like Climatiq automate carbon data collection and analysis across procurement and digital operations, addressing Scope 3 emissions. Google Cloud’s Carbon Footprint tool enables users to monitor project-level emissions, advocating for sustainability in everyday IT choices. Open-source solutions like Cloud Carbon Footprint provide accessible starting points for estimating cloud emissions.

2. Consider AI Solutions to Cut Carbon and Costs

AI isn’t just a business tool; it can also significantly reduce emissions while cutting costs. For instance, 45 Broadway, an office building in Manhattan, used BrainBox AI technology to optimize HVAC systems based on real-time conditions. Within 11 months, it reduced energy use by nearly 16%, saving over $42,000 and avoiding 37 metric tons of CO₂ emissions through a simple software upgrade.

Another effective strategy is “carbon-aware scheduling,” which involves running computational loads when the energy grid is cleaner. This can dynamically reduce the carbon footprint associated with AI operations.

3. Right-Size Your AI for a Low-Carbon Future

Not all AI systems are equal concerning their environmental impact. Decision-makers should prioritize energy-efficient AI models. While many models don’t disclose complete emissions data, new tools can operate more efficiently, reducing carbon footprints. For example, strategies detailed in FrugalGPT showcase how to cut operational costs by up to 98% without increasing emissions.

Organizations can focus on smaller, domain-specific AI models rather than larger general-purpose ones. This "right-sizing" can enhance data center efficiency while also promoting sustainable IT practices.

4. Build a Culture of Climate-Smart AI Innovation

Creating a climate-conscious organization requires structural and behavioral changes. One significant barrier to responsible AI deployment is siloed departments. Leadership should establish hybrid roles—like Responsible AI Officers or Sustainability + Data Strategists—to ensure alignment between IT and environmental goals.

Selecting partners based on their emissions transparency and commitment to renewable energy can extend accountability across the supply chain. Moreover, fostering workplace conversations about AI’s environmental impact is crucial. Incorporating sustainability into digital literacy can help employees adopt climate-conscious AI habits, such as reducing unnecessary compute cycles.

The future belongs to professionals fluent in both AI and sustainability. Developing dual fluency is essential as regulations, risks, and innovation converge.

This Is the Leadership Moment

Using AI responsibly isn’t about rejecting innovation; it’s about leveraging it thoughtfully. Business leaders who act now will not only shape the future of work but also influence the future of our planet.

In our race to adopt AI, we must remember that real progress is not just what we build, but how we build it. The intersection of AI and climate action could lead to unprecedented opportunities, but it requires a commitment to sustainability at every stage. Let’s harness this moment wisely.