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Generative AI and metaspace are redefining the cloud

End-user spending on public cloud services will increase by about 20% annually through 2026 (photo: CC0 Public Domain)

End-user spending on public cloud services will grow 21.7% to a total of $597.3 billion in 2023, up from $491 billion in 2022, Gartner predicts. Accelerating new technologies such as generative AI, Web3 and metaspace (or virtual reality) are among the factors that will contribute to the increased use of public cloud services, the analysts found. Gartner further predicts a steady increase in spending until 2026, when 75% of organizations will use a cloud-based digital transformation model.

Conventionally, Gartner divides the cost of public cloud services into several sectors. The infrastructure-as-a-service segment will enjoy the highest growth in end-user spending in 2023, up 30.9% from 2022. For platform-as-a-service, investment will grow at 24.1%. SaaS, the largest segment of the cloud market in terms of consumer spending today, will continue to grow at a rate of 17.9% to reach $197 billion in 2023.

Application-layer vendors are seeing their customers want to “reengineer SaaS offerings for increased productivity using cloud capabilities, embedded AI, and composability,” says Sid Nag, vice president of analytics at Gartner. Economic uncertainty may also be a factor in today’s purchasing decisions. Still, it doesn’t seem to have slowed investment in the cloud much, Nag adds.

Growth Factors

“The next phase of IaaS growth will be driven by user experience, digital and business outcomes, and the drive to bring services first into the virtual world,” Nag said. “New technologies that help businesses interact more closely and in real-time with their customers, such as chatbots and digital twins, rely on cloud infrastructure and platform services to meet increasing demands for computing power and storage capacity “.

“Web3 and the metaspace ultimately need a massively scalable infrastructure to work. That’s the only way they can deliver the end-user experience for apps that use these technologies,” Nag explained. Organizations looking to take advantage of these new technologies should “calibrate their cloud spending based on how extensively they plan to use the technologies in question for their applications and workloads,” he said.

Technological developments are changing purchasing decisions

Today, innovative organizations are looking for technology that can:

  • to optimize their activities or trust in the relationship with customers;
  • to expand the possibilities of delivery of products and services;
  • to allow them to be pioneers in implementing new ways of interacting with the audience.

All of these aspects can be implemented through cloud-supported software, depending on the company’s needs.

“Seize the opportunity to get a step ahead of the competition by increasing cloud spending in targeted areas in a well-thought-out way to roll out digital transformation initiatives – both externally from a B2B and B2C perspective, and from a modernization perspective … internal IT”.

Analysts point out that because technology purchases are often made by business leaders outside of IT, it can sometimes be difficult to predict who will “bring” what to the organization. However, the IT department is often involved somewhere in the implementation and deployment process, so it is still a key audience when it comes to acquiring new technologies.

Generative AIs

Generative AI is now a major factor in companies’ purchasing decisions for given new IT systems. The technology requires a lot of computing power and also faces a “trust barrier”. Privacy remains a key issue when it comes to generative AI, but organizations today shouldn’t hold back if they plan to implement it, said Gartner analyst vice president Aviva Litan.

Because hyperscalers are equipped to handle the infrastructure required for large language models, they are keeping a particularly close eye on developments in this space. They will continue to improve the capabilities of their cloud systems to be able to meet the needs of these AI models,” says Nag.

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