The role of AI in increasing sustainability and addressing climate change risks

Artificial intelligence (AI) is rapidly becoming a cornerstone in the fight against climate change, offering both significant opportunities and considerable challenges. 

While its computational demands – stemming from the vast processing power needed to train and operate AI models – contribute to energy consumption and carbon emissions, AI’s capabilities present transformative potential to mitigate climate risks and foster sustainability. For directors, navigating these dual aspects of AI is crucial for managing risks and capitalising on its vast potential.

AI’s impact on sustainability is a double-edged sword. On one side, the computational intensity of training and deploying advanced AI models is driving energy consumption to unprecedented levels. Large-scale models such as ChatGPT demand immense electricity resources, with AI-related data centre power consumption projected to double by 2026, potentially matching the electricity usage of entire nations like Japan. Additionally, the water-intensive cooling systems required by AI infrastructure further exacerbate its environmental footprint, with the training phase for models like ChatGPT-3 reportedly consuming around 700,000 litres of fresh water, and a single ChatGPT conversation using about half a litre of water.

While advancements in green algorithms – software designed to process tasks using less energy – are reducing their energy demands, and task-specific AI models are emerging as more sustainable alternatives to generalised systems, considering AI’s environmental risks requires a strategic approach. 

On the other side, AI’s potential to address climate change is extraordinary, and it is already driving efficiency gains and sustainable innovations across industries. For example, Eugenie.ai has developed an emissions-tracking platform to help companies in the industrial sectors to track, trace and reduce emissions by up to 30 per cent. In supply chain management, AI technologies enable real-time tracking and optimisation, reducing transportation-related emissions and waste. 

Tools like Microsoft’s Sustainability Calculator allow companies to measure and manage their AI-driven carbon footprints, empowering decision-makers with data to align their operations with climate and ESG (environmental, social and governance) goals. Advanced recycling technologies, such as those developed by AMP Robotics, are increasing material recovery rates and minimising landfill dependency. Furthermore, AI-powered climate models are helping businesses enhance disaster prediction and resilience, enabling proactive measures to adapt to a changing climate.

According to research by Google and Boston Consulting Group, the use of AI could reduce global emissions by between 5-10 per cent by 2030. As AI continues to evolve, purchasing systems with sustainability in mind should become a guiding principle for all organisations.

Directors have a pivotal role in harnessing AI’s potential while addressing its challenges. Embedding sustainability into governance frameworks is essential. Boards must prioritise evaluating AI’s environmental impacts and ensure that corporate goals align with broader climate commitments. Directors should encourage investment into AI systems that enhance productivity and support climate change and sustainability goals.

The integration of AI and sustainability offers a roadmap for businesses to drive meaningful climate action while creating long-term value and mitigating risks.

Considerations for boards

AI and climate-related issues are advancing rapidly, and boards have an opportunity to help their organisations navigate both the risks and potential benefits. Here are some areas that boards could explore: 

• Develop integrated AI and climate policies: Encouraging the development of policies that connect AI use with sustainability goals, including measurable targets for energy efficiency and responsible AI deployment, can help ensure AI is applied in a way that supports both business and environmental outcomes. 
• Invest in energy-efficient technologies and green algorithms: Boards can encourage investment in energy-efficient infrastructure, hardware and the development of green algorithms. This approach reduces operational costs, mitigates environmental risks, and supports long-term sustainability goals.
• Strengthen stakeholder communication: Engaging openly with stakeholders on the organisation’s approach to AI and climate issues can build trust, meet expectations, and support access to key markets.
• Establish a combined oversight committee: A committee that oversees both AI and climate initiatives, with cross-functional expertise from technology, sustainability and governance, can help ensure consistent oversight, proactive risk management and the strategic use of emerging opportunities.