Sustainability and Digital Sovereignty Shape genAI Choices

By 2027, most organizations will prioritize environmental sustainability and data control when choosing cloud services for AI.

By Sunil Sonkar
2 Min Read
Sustainability and Digital Sovereignty Shape genAI Choices

In the coming years, a significant shift is expected in how organizations choose their cloud services for adopting generative artificial intelligence (AI). Analysts predict that by 2027, over two-thirds of these organizations will prioritize factors like environmental sustainability and digital sovereignty when selecting public cloud services.


According to Sid Nag, a VP analyst at Gartner, the public cloud stands out as the ideal technology for developing foundational models (FMs) and deploying generative AI (genAI) applications at scale due to its scalability and shared-services model. However, some worries about sustainability and controlling data need to be sorted out to make genAI work well.

Nag says that cloud computing is important for helping sustainability and genAI because it gives us big, flexible systems, eco-friendly ways of doing things as well as saves money on managing resources. Consequently, it is the platform most IT leaders rely on for their sustainability journey in genAI implementation.

Gartner forecasts that 70% of organizations will base their cloud decisions on sustainability factors by 2027. These things like using renewable energy, how much power is used and water use all add up to how much pollution cloud computing makes.

While the scale of public cloud infrastructure attracts organizations deploying genAI applications, cloud providers must address sustainability issues to maintain market share. Investors, clients, and rules from governments will push companies to cut down on the pollution caused by their tech stuff. This will make companies come up with new ways to keep an eye on and control how much energy and pollution is made by genAI stuff in the public cloud.

Foundation models and large language models (LLMs) are crucial to genAI capabilities but deploying genAI in an enterprise environment brings forth significant regulatory challenges concerning the data within these models and applications.

Specialty cloud providers are likely to be favored as they can address unique requirements of sovereign operations regardless of the region they operate in, according to Nag.

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