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HOW AIOPS CAN HELP IN SUSTAINABILITY ROAD MAPS
Modern AIOps platforms monitor emissions at the workload level, providing granular insights into which applications, processes, or services are the most carbonintensive. They integrate with energy meters, cloud providers, and hardware sensors to calculate emissions using industry-standard models like the Greenhouse Gas Protocol, explains Bharani Kumar Kulasekaran at ManageEngine.
The technology industry ' s grand promises about AI and sustainability have hit a wall. While organisations trumpet AI solutions for climate change, the technology itself consumes a staggering amount of energy. reduce environmental impact or merely serve as a strategic narrative for organisations keen on PR. But amid this crisis of credibility, a solution is emerging from an unexpected quarter: Artificial Intelligence for IT operations, AIOps.
Bharani Kumar Kulasekaran, Product Manager, ManageEngine
According to the International Energy Agency, data centres, AI, and cryptocurrency collectively consumed 460 terawatt-hours, TWh of electricity in 2022, about 2 % of global demand. By 2026, this number is expected to more than double to 1,000 TWh, surpassing the annual electricity consumption of entire countries like Germany or Japan.
This situation has led to growing scrutiny, with some questioning whether AI’ s sustainability efforts genuinely
By embedding real-time carbon tracking and automated optimisation directly into IT infrastructure, AIOps is transforming sustainability from a marketing buzzword into a measurable metric. For the first time, companies cannot just claim their AI is green, they have to prove it.
Beyond the staggering electricity consumption, the true environmental cost of AI extends deeper into our infrastructure. Each new breakthrough in AI capability demands more powerful hardware, more extensive
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