Gartner: Sustainability and digital sovereignty will be the primary criteria for selecting public cloud generative AI services

Gartner predicts that by 2027, 70% of enterprises adopting generative artificial intelligence (generative AI) will regard sustainable development and digital sovereignty as public choices. The primary consideration for cloud-generated AI services.

According to Sid Nag, research vice president at Gartner, cloud technology has become the first choice for the development of generative AI applications and common basic models due to its scale and shared service model. However, for organizations to put generative AI applications into operation, they must address issues such as digital sovereignty and sustainable development.

The role of digital sovereignty in public cloud decision-making

Fundamental models (FM) and large language models (LLM) are key components of generative AI capabilities, and their advancements drive generative The rapid development of AI functions and application scenarios. Enterprises will face many regulatory challenges when using generative AI, including the data involved in LLM and the compliance of application FM and LLM, which will all attract the attention of regulatory agencies.

Nag pointed out that as enterprise organizations need to expand their cloud services to different locations and application scenarios, professional cloud service providers will become a key factor in the cloud architecture of many enterprises. The rise of digital sovereignty will drive demand for cloud service providers who must ensure they can meet the ever-changing and unique sovereignty business requirements in any region.

The role of sustainable development in public cloud decision-making

In order to deploy generative AI services, organizations need to rely on public clouds to meet infrastructure scale requirements. In addition, enterprises are asking cloud service providers to address non-technical issues related to sustainability.

Business organizations face pressure from investors, customers, regulators and governments to achieve environmental sustainability goals. In order to manage and optimize IT carbon emissions, they introduce new processes, functions and tools to monitor and manage the energy consumption and carbon emissions of generative AI workloads in the cloud. These initiatives help companies achieve more sustainable operating models and comply with growing environmental sustainability standards. By adopting greener technologies and strategies, companies can reduce carbon emissions and improve resource efficiency. Monitoring and managing IT carbon emissions also helps businesses identify and reduce energy waste, thereby reducing operating costs and improving overall efficiency. These initiatives not only help enterprises

Nag pointed out that cloud computing plays an important role in driving sustainable development and generative AI business applications because of its ability to provide scalable infrastructure, support environmentally friendly practices, and Enable efficient resource management. This is why most IT leaders will rely on cloud platforms to support their sustainable development journey when fully adopting generative AI.

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