The advent of artificial intelligence (AI) in recent years, particularly with the introduction of groundbreaking platforms like ChatGPT, has catalyzed transformative shifts across various sectors, propelling stock markets to unprecedented heights this year. Morningstar’s research indicates that within the S&P 500, there are 67 stocks tied to AI, with the remaining 433 lacking AI association and underperforming.
While discussions surrounding AI and technology often revolve around carbon footprints and energy consumption, an aspect that warrants equal attention is water usage. The operation of data centres, integral to the functioning of AI systems, not only demands vast amounts of energy but also relies significantly on water for cooling purposes.
Beyond its water-intensive operations, AI holds immense potential in fostering collaboration and innovation toward climate solutions.
Over recent years, tech giants such as Microsoft and Google have witnessed a surge in water consumption by nearly 20-30%, accentuating the pressing need to address the water footprint of AI technologies. Academic research, including studies from the University of California, underscores the potential for AI to exacerbate water withdrawal, with projections suggesting consumption levels rival those of entire nations.
Central to this challenge is generative AI models, particularly large language models, which necessitate immense computational power for processing voluminous datasets. Server farms rely heavily on water-based cooling systems, dissipating absorbed heat from the equipment into the atmosphere, where a significant portion evaporates. The water footprint of AI becomes even more pronounced when considering the staggering output of advanced models like ChatGPT. Estimates from a study indicate that generating a mere 10 to 50 responses with the previous iteration of ChatGPT3 was equivalent to the consumption of a 500 mL water bottle.
However, amidst these concerns, it is imperative to contextualize the broader implications of AI deployment. Beyond its water-intensive operations, AI holds immense potential in fostering collaboration and innovation toward climate solutions. It can aid in optimizing energy consumption in buildings, forecasting weather patterns to manage resources effectively, refining agricultural methods to minimize waste, enhancing renewable energy production, and assisting in ecosystem monitoring and conservation efforts. Moreover, it’s essential to recognize that AI computation constitutes only a fraction of the electricity utilized by data centres, accounting for approximately 1-1.5% of the global electricity supply, according to the International Energy Agency.
Tech companies acknowledge the environmental imperative and are increasingly prioritizing efforts to mitigate their water emissions. Initiatives range from implementing monitoring systems to setting ambitious targets aimed at water neutrality by 2030. Microsoft states, “being net water positive means we will reduce water consumption across our global operations, replenish more water than we use, provide people across the globe with access to water and sanitation services, drive innovation, and engage in water policy.”
Another company that has greatly profited from investor interest in AI is Nvidia, which is a leading supplier of semiconductors powering AI models, boasting a substantial market value of approximately $2.2 trillion. This valuation situates Nvidia as one of the leading influences in the S&P 500, which saw significant boosts last year, primarily from seven mega-cap tech stocks. The company’s prominence comes with many sustainable practices. It boasts an energy-efficient supply chain, exemplifying the convergence of technological innovation and environmental stewardship. For instance, Nvidia’s products focus on accelerating the most compute-intensive workloads whilst simultaneously being energy efficient. Their GPUs, which are used to power AI models, allow for greater computational and processing power whilst using less energy than that of competitors; as such, their products have been deemed as low-carbon technology.
In conclusion, integrating AI technologies presents both challenges and opportunities in addressing water sustainability. By fostering responsible stewardship and leveraging technological advancements, stakeholders can navigate these complexities to realize a future where AI-driven progress aligns harmoniously with environmental preservation.
The statements and views expressed in this document are those of the authors as of the date of this article and are subject to change.
This article is also of a general nature and does not constitute legal, accounting, tax or investment advice.
