{"id":30805,"date":"2025-07-23T08:36:12","date_gmt":"2025-07-23T08:36:12","guid":{"rendered":"https:\/\/www.newsbeep.com\/us\/30805\/"},"modified":"2025-07-23T08:36:12","modified_gmt":"2025-07-23T08:36:12","slug":"restraining-ais-energy-guzzling-ways-rtinsights","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/us\/30805\/","title":{"rendered":"Restraining AI’s Energy-Guzzling Ways – RTInsights"},"content":{"rendered":"

\"\" <\/p>\n

Addressing AI\u2019s energy-guzzling nature all comes down to using artificial intelligence thoughtfully, according to a recent Accenture report.<\/p>\n

Artificial intelligence, which gobbles up data center power, is running away with available resources. \u201cThe infrastructure fueling the AI revolution is consuming unprecedented amounts of electricity and water at rates that rival entire nations,\u201d according to a new analysis<\/a> out of Accenture. Such energy-guzzling by AI is likely to grow if not addressed. <\/p>\n

Over the next five years, AI data centers could consume up to 612 terawatt-hours, which is equivalent to Canada\u2019s total annual electricity consumption, the report\u2019s authors, led by Stephanie Jamison, state. AI\u2019s share of global power consumption is set to rise from 0.2% in 2024 to 1.9% by 2030, an extraordinary pace of 48% CAGR, outpacing the expected 1.5% growth rate in overall electricity demand growth in this period.<\/p>\n

There\u2019s another critical resource at risk as well: \u201cthese data centers are predicted to guzzle more than 3 billion cubic meters of water annually \u2013 more than the total annual freshwater withdrawals of countries like Norway or Sweden.\u201d\u00a0<\/p>\n


\n \"PTC
\n <\/a><\/p>\n

The Accenture team recommends AI itself as an effective approach to reigning in AI consumption. \u201cWith AI\u2019s energy footprint growing relentlessly, AI governance-as-code \u2014 embedding sustainability into automated compliance systems \u2014 is key to reducing risks, lowering costs and building resilient, future-proof AI ecosystems,\u201d they advise. <\/p>\n

AI-driven automation \u201ccan help enforce sustainability policies and manage environmental risks in real time,\u201d they continue. \u201cAutomation can also make it easier to select the most sustainable infrastructure for each model deployment.\u201d<\/p>\n

Tools and platforms such as the Cloud Native Computing Foundation\u2019s Kepler project (Kubernetes-based Efficient Power Level Exporter) can help \u201csupport energy-aware AI scheduling.\u201d In addition, intelligent workload orchestration tools such as Karmada (Kubernetes-based Multi-Cloud, Multi-Cluster Orchestrator) can help \u201coptimize AI workloads across regions based on carbon intensity.<\/p>\n

Accenture also developed what it calls a Sustainability-Adjusted Intelligence Quotient (SAIQ), a measure of how efficiently AI systems convert money, electricity, water and carbon into actual performance.\u00a0\u00a0SAIQ is a composite efficiency score that measures the environmental and economic performance of AI systems, weighing factors such as costs, electricity consumption, carbon emissions, and water intake.<\/p>\n

See also: AI Model Mimics Brain Neurons to Reduce Energy Costs<\/a><\/p>\n

Curbing AI\u2019s Energy-Guzzling<\/p>\n

The Accenture authors offer numerous suggestions for bringing AI energy consumption under contreol, including the following:<\/p>\n

Deploy AI at the edge: This \u201ccuts down on cloud use and improves performance by reducing latency. Edge AI applications are especially well-suited to industries that rely on real-time data processing, such as manufacturing, healthcare, retail and financial services.\u201d<\/p>\n

Adopt dynamic scaling and smart load balancing: \u201cMatch energy use to AI workloads.\u201d Design AI infrastructure \u201cwith energy proportionality in mind, drawing on principles like dynamic efficiency scaling to optimize power use across AI workloads. Reduce peak energy demands by using adaptive scheduling to shift AI processing to times when power is cheapest and cleanest.\u201d<\/p>\n

Choose right-size AI models: \u201cInstead of defaulting to large-scale LLMs, deploy
task-specific AI models. Techniques like Retrieval-Augmented Generation (RAG) can
reduce inference costs by accessing data only when needed,\u201d<\/p>\n

It all comes down to using AI thoughtfully, the Accenture team states. \u201cThe paradox of AI is that it can be used both more selectively and more broadly to reduce its impacts. Businesses that get it right can drive sustainability, profitability and competitiveness to new heights.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"Addressing AI\u2019s energy-guzzling nature all comes down to using artificial intelligence thoughtfully, according to a recent Accenture report.…\n","protected":false},"author":2,"featured_media":30806,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[46],"tags":[191,25886,74],"class_list":{"0":"post-30805","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-computing","8":"tag-computing","9":"tag-energy-consumption","10":"tag-technology"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/30805","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/comments?post=30805"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/30805\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media\/30806"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media?parent=30805"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/categories?post=30805"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/tags?post=30805"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}