As the world faces pressing environmental challenges, artificial intelligence (AI) has emerged as a powerful tool when looking at how to combat them. By leveraging machine learning, automation, and predictive analytics, AI can help to mitigate the impact of climate change. From optimising energy consumption to revolutionising waste management, AI is reshaping industries to be more efficient and eco-friendly. Although this technology is touted as a revolutionary solution, it is important to recognise that it does not come without potential drawbacks.

 

Energy Efficiency and Storage

There are many key sectors in which the implementation of AI can be utilised to drive real change. One of these industries is the energy sector, where it is already being used to help make power generation, distribution, and consumption more efficient. The use of AI has also affected the renewable energy industry forecasting models predicting weather patterns, allowing us to match both our current and future energy demand, and optimising the selection of locations for future renewable energy sites.

AI is also making strides in assisting the efficiency of energy storage by optimising battery usage, and, subsequently helping reduce our reliance on fossil fuels. The emergence of efficient batteries helps individuals and businesses with the long-term transition to more sustainable energy storage by, for example, moving away from combustion to hybrid or electric engine vehicles, or the retaining of more power to those who have installed their own renewable energy sources (e.g. solar panels), helping reduce financial costs and negative impact on the environment.

 

Agriculture

With a growing global population, the impacts of climate change are putting a greater strain on our food supply. AI-powered precision farming techniques can help increase potential crop yield by optimising the conditions needed for crop growth whilst minimising water and pesticide usage. Alongside the impact of crop yield, AI can also support livestock management by monitoring animal health and predicting disease outbreaks, allowing farmers to take proactive measures that reduce antibiotic overuse and reduce the risk of future pandemics.

 

Waste Management

The evolution of AI is also transforming waste management and leading to the implementation of more circular economy initiatives. Intelligent waste-sorting systems can use AI to identify and separate recyclables from general waste. This, combined with the use of improved AI robotics, has led to an improved sorting efficiency at recycling facilities, ensuring that more materials are properly processed and reused, helping to reduce the amount of waste that ends up in landfill.

AI-driven marketplaces are emerging that aim to connect businesses with surplus materials, facilitating their reuse and extending product lifecycles. By enabling a circular economy, AI is reducing the reliance on virgin materials, cutting down on waste production, and helping to alleviate the impact waste management has on climate change.

 

Climate Change Mitigation

Beyond industrial applications, AI can play a crucial role in climate change mitigation and environmental protection. AI-powered satellite imaging is being used to monitor deforestation, melting ice caps, and ocean pollution in real time. This can help to gain a more accurate and up to date understanding of the measures needed to remain in line within the IPCC’s climate targets, as well as help to predict extreme weather events and improving disaster preparedness as a direct consequence of climate change.

Additionally, AI-driven carbon capture technologies are being developed to absorb and store atmospheric carbon dioxide in a more permanent manner, contributing to global emission reduction goals.

 

What are the challenges?

Despite its immense potential, AI-driven sustainability efforts come with challenges. The energy-intensive nature of training AI models, concerns over data privacy, and potential job displacement need to be addressed. It is essential to design AI solutions with sustainability in mind to maximise their benefits while minimising unintended consequences. For this reason, ethical AI deployment and regulatory guardrails will be critical in ensuring that technological advancements do not come at the cost of societal well-being.

Transparency and accountability are crucial in AI development. AI models must be trained using unbiased data to prevent reinforcing existing inequalities in access to sustainable technologies. Additionally, the implementation of AI must be accompanied by policies that support workforce transition. AI will replace many traditional jobs, but it will also provide many new job opportunities. Giving workers who are replaced by AI the means to reskill and benefit from this new wave of job creation will be key to avoid widespread social unrest and rising unemployment.

There are also growing concerns about the amount of physical infrastructure that will need to be implemented to keep up with the rapid growth of AI. Vast amounts of water will be needed to cool down AI data centres and the amount of WEEE that will be generated is likely to increase. This is not only damaging in terms of disposal, but also in terms of the mining and use of earth metals that are required for the manufacturing of the AI technological equipment which were already in short supply before the AI boom.

The UNEP suggests that the key to tackling the growing environmental concerns surrounding AI is through the implementation of global legislation to help standardise procedures for measuring the environmental impact of AI and help to ensure more tech companies are disclosing the direct environmental consequences of AI based products and services.

 

Conclusion

AI will be a game-changer for sustainability, offering transformative solutions to some of the world’s most urgent environmental challenges. As AI technology continues to evolve, collaboration among governments, businesses, and researchers will be key to unlocking its full potential for a greener, more sustainable future. For AI to realise its full potential in sustainability, investments in research and infrastructure must continue but care must be taken with unintended societal and environmental consequences.

 

Abbreviations:

IPCC – Intergovernmental Panel on Climate Change

UNEP – United Nations Environment Programme

WEEE – Waste from Electrical and Electronic Equipment