AI and energy consumption: How technological advancements widen the divide and COP 29’s failure to address it

Artificial Intelligence (AI) is transforming industries and daily life like never before, becoming indispensable to the global technological landscape. From personalised recommendations to advanced medical diagnostics and climate modelling, AI drives innovation and offers solutions to some of humanity’s most pressing challenges. However, its rapid growth comes with a paradox: while AI helps tackle issues like climate change, it also contributes significantly to energy consumption and a growing carbon footprint.

This irony took center stage at the COP 29 summit in Baku, where world leaders deliberated on strategies to curb emissions through AI and other digital technologies. Several recent reports, including those from the United Nations, underscore how AI can mitigate climate concerns—if the sector’s emissions are managed. Yet, these reports often sidestep the fundamental issue: the significant emissions AI generates and the challenges in reducing them, especially in regions reliant on fossil fuels. This paradox underscores the complexities of leveraging AI for climate action without inadvertently exacerbating the problem.

A study by Sasha Luccioni, an AI researcher at Hugging Face, emphasized the uneven impact of AI based on energy sources. She noted that AI deployment is beneficial in regions with cleaner power grids, such as France, but detrimental in countries like India and Kenya, where fossil fuel reliance is high. In these regions, AI adoption could exacerbate emissions, increase electricity consumption, and generate technological waste, ultimately worsening the climate crisis.

While setting up AI models in developed countries may seem like a promising solution, the broader implications should not be overlooked. Increased AI usage for a greener environment will attract more investment and trading opportunities, disproportionately benefiting economically advanced nations. A 2020 study by the International Monetary Fund highlighted how AI might widen the economic divide between rich and poor countries.

The study identified two main reasons for this disparity. First, AI technologies and robotics will replace high-wage labor in advanced economies, leading to increased production efficiency. Second, this efficiency will drive strong demand for robots and traditional capital, further enriching developed countries. Conversely, developing economies will remain reliant on manual, often unskilled labor, stalling their economic growth.

The AI revolution is thus deepening the divide between wealthy and developing nations. Advanced economies lead AI development and deployment, reaping economic and environmental benefits, while poorer nations struggle to access these innovations. Moreover, widespread adoption of robotics and AI will cause significant job losses in many sectors, potentially triggering mass migration and increasing the burden on developing countries.

Interestingly, while COP 29 leaders aim to curb emissions through AI, they seem to ignore the long-term implications of this approach. The indifference of developed countries towards the struggles of developing nations was evident throughout the conference. For instance, while developing economies estimate a need for $1.3 trillion to address the impacts of climate change, developed economies pledged only $300 billion. This disparity highlights their reluctance to shoulder their share of the responsibility, despite being major contributors to the climate crisis.

The dissatisfaction was evident in the words of Mohamed Adow, director of Power Shift Africa, a Kenyan think tank, who criticized the outcome of COP 29: “The rich world staged a great escape in Baku,” he remarked. “With no real money on the table, and vague and unaccountable promises of funds to be mobilised, they are trying to shirk their climate finance obligations,” he added, explaining that “poor countries needed to see clear, grant-based, climate finance” which “was sorely lacking”.

Adding to the challenge is the return of Donald Trump as President of the United States. Under his leadership, a strategic and dedicated U.S. involvement in climate initiatives becomes uncertain, given his history of dismissing climate change as a "hoax." Furthermore, while emerging economies like China—currently the world’s largest emitter—are expected to contribute, the agreements merely "encourage" voluntary action, leaving significant gaps in accountability. The sufferer? Poorer economies.

In the end, efforts to combat climate change through AI risk creating new disasters while attempting to resolve existing ones. The economic and technological divide between developed and developing nations will likely widen, leaving poorer nations to bear the brunt of climate impacts. While global conferences may continue to propose solutions, the reluctance and self-centeredness of advanced economies foreshadow an uneven and inequitable fight against climate change.