The Forecast by Nutanix

Whether the actual job title changes is almost beside the point. The scope and scale of the work, and the base nature of the job function, already have, whether enterprises realize it or not. Ask a CIO what their job is today and the answer would likely sound significantly different than it might have just five years ago. Data governance. AI strategy oversight. Automation architecture. Risk modeling.

Artificial Intelligence is great for mechanical tasks like summarizing content, organizing numbers and streamlining workflows. But human resources (HR) is about people, and people are nuanced and often more complicated than data. Using AI in HR processes can actually bring fairness, claims Navneet Singh, chief marketing officer at Eightfold AI, maker of an AI-powered platform for HR processes like hiring and talent management. “It's not whether AI is safer than humans,” Singh told The Forecast.

Technology As enterprises unlock value from 5G through AI, they're building the foundation for the even greater capabilities expected with 6G Article:Technology Nutanix-Newsroom:Article The race toward 6G has already begun, even though the technology itself is still years away. For forward-looking organizations, getting ready for 6G starts long before the first network goes live. According to IEEE, 6G is expected to be deployed around 2030, although research on the technology began in 2018.

It is a question that more enterprise IT leaders are asking out loud. Lieb oversees AI infrastructure partnerships. He said Dell deployed more than 4,000 AI factories as of April, evidence that demand for enterprise AI is in full swing. He said buyers are no longer just large cloud providers and hyperscalers.

Everyone is talking about the explosion of artificial intelligence and what it might mean for the future of humanity. For all the talk about algorithms and large language models, however, it might be hardware — not software — that makes or breaks this transformative technology. One piece of hardware, in particular, suggests Lucas Melo, a cloud solutions architect at Intel: the central processing unit, or CPU.

It's real. Matt Kimball, principal analyst at Moor Insights & Strategy, says that business and IT leaders want to talk to him about three things: “AI, AI, and AI.” “I can’t have a conversation with a CIO, an IT leader, even business folks, without AI being the eventual topic of the discussion,” Kimball told The Forecast at the Nutanix .NEXT event in Chicago.

He has tracked IT infrastructure shifts for 30 years, seeing new innovations disrupt the enterprise tech stack, layer by layer. But artificial intelligence blew them all up at once. These days, CEO and principal analyst at HyperFRAME Research Steven Dickens bounces between industry trade shows and media interviews, bearing witness to enterprises scrambling to embrace new AI capabilities. He said the IT industry is moving at a pace like never before.

Cloud computing has evolved for 20 years to reach its current form. Kubernetes, the container orchestration platform now regarded as critical enterprise infrastructure, has been evolving for just over a decade. The iPhone, which redefined mobile computing, shipped in 2007 and continues to shape how enterprise applications are conceived and built. Dickens places AI on that same arc that will take years to fully resolve. The maturation of Kubernetes is central to his argument.

He says that game server providers “are built in such a way as to have the compute very close to the inference capabilities,” making them ideal for tasks like token generation that require quick turnaround. Balancing capacity between multiplayer games and inference workloads is a “logistical puzzle” that requires careful management.

That blind spot can create regulatory exposure. Banks may not know what customer data employees entered into outside tools, where they were stored, or whether its use complied with privacy, retention, and governance rules. They may also struggle to document controls, explain AI-assisted decisions, or tell regulators how sensitive information was handled. Data sovereignty adds another constraint.