The rapid growth of artificial intelligence (AI) has caused Big Tech share prices to soar, but it comes at the expense of the industry's climate goals. Google, for example, acknowledged that its data centers, essential infrastructure for AI, contributed to a 48% increase in greenhouse gas emissions since 2019, casting doubt on its target of achieving net zero emissions by 2030. Microsoft, the main financial supporter of OpenAI, also admitted that its net zero goal for 2030 might not be attainable due to its AI strategy. AI's environmental impact stems from its reliance on data centers, which consume large amounts of electricity and generate CO2 emissions. According to estimates, total electricity consumption from data centers could double by 2026, and AI is projected to account for 4. 5% of global energy generation by 2030. Water usage is also significant, with AI potentially consuming up to 6. 6 billion cubic meters of water by 2027. Experts highlight the importance of the energy source used by tech firms and the need to transition to renewable energy. However, the availability of clean energy could be a limiting factor, as there may not be enough to meet the growing demand from AI data centers. Governments aim to triple renewable energy resources by the end of the decade, but the International Energy Agency warns that global renewable energy capacity may only double by 2030 under current plans. To address the energy requirements of AI, tech companies would need to invest heavily in new renewable energy projects. While onshore renewable energy projects can be developed relatively quickly, challenges such as planning rules and grid connection delays may lead to delays of several years.

Offshore wind farms and hydro power schemes face similar obstacles, in addition to longer construction times. The unique nature of the AI industry raises concerns about its ever-increasing demand for electricity. While normal supply and demand principles suggest that rising energy costs would prompt the industry to economize, leading tech companies may choose to bear the cost and continue their pursuit of AI dominance. The competition for advanced AI systems is intense, with massive investments made in training runs. There is a sense that the winner takes all, fueling the race to spend exorbitant amounts on training runs to monopolize vital technologies. Despite advancements in AI technology enabling companies to achieve more with less computing power, this hasn't translated into reduced electricity consumption. Instead, it has led to the same amount of electricity being used to create even more advanced AI systems. This phenomenon, known as "Jevons' paradox, " demonstrates how efficiency improvements can lead to increased energy usage. In summary, the AI boom poses a threat to tech's climate aspirations due to the significant energy consumption and environmental impact of data centers. Without a more extensive transition to renewable energy and breakthroughs in energy efficiency, the industry's relentless pursuit of AI dominance may impede progress towards climate goals.