{"id":11888,"date":"2025-05-15T16:13:11","date_gmt":"2025-05-15T15:13:11","guid":{"rendered":"https:\/\/mspglobal.com\/blog\/?p=11888"},"modified":"2025-06-18T12:57:24","modified_gmt":"2025-06-18T11:57:24","slug":"ai-sustainability-msp-opportunities","status":"publish","type":"post","link":"https:\/\/mspglobal.com\/blog\/ai-sustainability-msp-opportunities\/","title":{"rendered":"AI, Sustainability and MSPs: What are the Opportunities?"},"content":{"rendered":"\n

There\u2019s no denying AI\u2019s warp-speed integration into most digital workflows over the last few years. Its ability to drive efficiency, innovation and competitive differentiation are just a few of its advantages. For MSPs, it transformed customer-facing services through automation, threat identification and predictive maintenance through real-time data collection and analysis. So far, so good.<\/p>\n\n\n\n

But as AI grows in scale and power, so does its environmental impact, because while AI may live in the Cloud, its carbon footprint\u2014data centers and their energy and cooling needs\u2014is very much on Planet Earth. <\/p>\n\n\n\n

MSPs are prime facilitators as customers take advantage of AI-powered solutions. But, as 100 Spider-Man reboots have told us, with great power comes great responsibility. MSPs now have a unique opportunity to lead from the front and create competitive advantage while defining a new stage of AI\u2014a future where AI is not only powerful, but also more environmentally responsible. <\/p>\n\n\n\n

Powering AI<\/h2>\n\n\n\n

AI and sustainability have\u2026 let\u2019s call it a complex relationship! The MSP GLOBAL community already knows the huge advantages it offers in terms of driving efficiency and optimizing resources: <\/strong>energy use, streamlining supply chains, and intelligent management of natural resources, for example. <\/p>\n\n\n\n

But AI\u2019s biggest and most immediate problem is its own environmental footprint, spanning raw-material extraction for chips and data  centers to operational energy consumption. <\/p>\n\n\n\n

AI is HUNGRY!<\/h2>\n\n\n\n

The manufacturing cycle for AI hardware\u2014especially GPU microchips and specialized accelerators\u2014requires rare-earth elements and critical minerals like lithium, cobalt and nickel, which are often extracted through mining processes that are harmful to both the environment and communities. A 2kg computer requires 800kg of raw materials<\/a>. Some of those raw materials also serve as geopolitical levers in ways that can be unpredictable. At Cloud-level scale, that\u2019s just not a pretty picture.<\/p>\n\n\n\n

Then there\u2019s the energy required by training and running AI models, and how to cool them. In 2023, AI alone consumed 4.5 gigawatts globally \u2013 around 8% of all data center energy use<\/a>. According to the International Energy Agency<\/a>, electricity demand from AI-optimised data centers is set to quadruple by 2030. And when it comes to water use for cooling data centers, global AI is predicted to account for 6.6 billion cubic meters<\/a> of water withdrawal by 2027\u2014roughly the same annual water withdrawal of half the UK. And if that wasn\u2019t enough to raise eyebrows, a single ChatGPT question uses 10 times more energy than a Google search (yes, that includes when users send a \u201cthank you\u201d message). With up to a billion prompts a day, that burns through 2.9 million kilowatt-hours of energy every day\u2014around 100,000 times more power than an average US household. <\/p>\n\n\n\n

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Photo by Brett Sayles<\/a><\/figcaption><\/figure>\n\n\n\n

So we see that high performance can mean some seriously high consumption\u2014even more than many may realize. While GPUs offer the parallel processing capabilities that are ideal for AI tasks and can be more energy-efficient per operation compared to CPUs, scaling via GPU clusters can lead to significant total energy consumption. The balance between performance and environmental cost is a critical factor for MSPs to consider when deploying AI services for customers: not just in terms of optics and company ethos, but your actual bottom line. <\/p>\n\n\n\n

Why the focus now, and what legislation is coming?<\/h3>\n\n\n\n

While legislation and regulation differ from region to region, governments and regulatory bodies are increasingly focusing on sustainable technology practices, including those related to AI. <\/p>\n\n\n\n