Why progress in AI doesn’t have to come at the expense of the environment
While the pressure on companies and government departments to meet NetZero’s carbon targets cannot be sugar-coated, most IT leaders have the added pressure of meeting the demand for new technologies. It’s an ongoing balancing act to enable people to work and perform better, while addressing ESG compliance and not blowing IT budgets.
Automation now dominates IT buyer thinking. New products and tools are being added all the time. For example, recently Microsoft founder Bill Gates spoke about the enormous potential of AI assistants, suggesting that the race is on for organizations to develop powerful AI assistants that could reshape the digital landscape, putting companies like Google and Amazon at risk come. He suggested that these AI assistants could radically change behaviors that impact daily life and work. We’ve already seen an element of this with ChatGPT, while Microsoft has already taken a step in this direction with the announcement of its Copilot AI assistant for 365.
It is a fact that automation is attractive to organizations for its productivity, efficiency and overcoming skills shortages, but this can come at a cost, both financial and environmental. As Gartner warned in its 10 strategic forecasts for 2023, AI comes with greater sustainability risk. By 2025, the report says, “AI will consume more energy than the human workforce, which will significantly offset carbon neutrality gains.” With this in mind, something certainly needs to be done now to enable AI without undermining environmental efforts.
Achieving ESG targets is, at least according to Deloitte, a more prominent issue in boardrooms this year, so how organizations balance this with increased automation needs will be key. Cloud computing is obviously central to enabling AI tools in organizations. Digital transformations to implement platforms that unite organizations and therefore data are driving cloud adoption.
As Gartner recently revealed, global cloud spending is expected to reach $600 billion this year, driven primarily by emerging technologies such as generative AI. Sid Nag, vice president analyst at Gartner, says generative AI “requires powerful and highly scalable computing capabilities to process data in real time,” with the cloud “providing the perfect solution and platform.”
Cloud bursts
And yet the cloud is still dogged by claims that it is bad for the environment and does not help organizations achieve their ESG compliance goals. In fact, the cloud industry has been one of the most active in trying to increase efficiency and reduce environmental impact. The demand for cloud services is so high that it will inevitably become difficult to keep up. Stacking more racks in a data center is a short-term solution, but not really a long-term solution, especially given the high demand for power to manage increased automation.
In our Enterprise Cloud Index survey, 85% of 1,450 IT decision makers recognized that meeting companies’ sustainability goals is a challenge for them. While almost everyone (92%) said sustainability is a much more important topic than it was a year ago, there is a clear gap between what organizations want to achieve and how they go about it. What we’ve seen is that major challenges arise due to a combination of complexity and IT budget constraints.
Our research shows that most organizations use more than one type of IT infrastructure, whether it is a mix of private and public clouds, multiple public clouds or an on-premise data center, along with a hosted data center. This will only grow, but mixed infrastructures pose new management challenges. With increased complexity, organizations need a single, unified place to manage applications and data across their diverse environments, to reduce costs but also measure impact.
Increasing the efficiency of data processes is an important step in reducing hits to IT systems, but this is only part of the solution. The real step change for any organization operating in the cloud is looking at the underlying infrastructure. Measuring and then managing the impact of data centers will remain critical to reducing the carbon impact of computing in organizations. Like a car, if you have a smaller yet more powerful and efficient engine, you will not only reduce emissions, but also create room for growth and better performance, through tools like AI.
Reframing the image
As Atlantic Ventures suggests in its report Improving Sustainability in Data Centers, the required energy demand at data centers is still very high and results in large amounts of carbon dioxide emissions. Energy consumption is an important factor in measuring the environmental performance of data centers, but one traditional method is now being questioned.
Fundamentally, changes need to be made to the rack. Infrastructure modernization starts with hyper-converged infrastructures (HCI), which reduce the ‘moving parts’ and therefore energy needs. This also means less complexity, both in terms of cloud structures and data management. This is what will yield the most immediate results.
As Atlantic Ventures says, “in the EMEA region, HCI architectures have the potential to reduce up to 56.68 TWh between 2022 and 2025 and save up to €8.22 billion in electricity costs over the same period for enterprises and data center providers running a full transformation to HCI.” This, combined with next-generation liquid cooling, is a huge step towards creating a low-impact platform for the future.
For any organization looking to embrace AI and related automation applications, addressing infrastructure complexity is now critical. Running data centers is an increasingly specialized business (especially given continued high energy prices) and as more and more real-time data is required, the challenges for organizations are only increasing. With the right partners and the most efficient infrastructure, any organization can consider itself AI-ready without sacrificing ESG objectives.
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