A key goal for many C-suite technology leaders in an AI-powered world is to enable technology. Understanding how AI fits into your organization’s operations may include determining what it means for your business.
“At the end of the day, we’re trying to automate things that people normally do, and it’s the same thing with cars, right? So, do you call self-driving cars AI or advanced automation?” asked Bob Friday, chief AI officer at Hewlett Packard Enterprise (HPE).
Friday recently attended NRF 2026: Retail’s Big Show and shared a little about how HPE is using AI and how they are leveraging the evolving technology.
HPE provides network, server, and containerization software and services. Mr. Friday is the co-founder of Mist Systems, an AI-powered wireless LAN startup that was acquired by Juniper Networks, which was subsequently acquired by HPE.
Where AI meets real-world constraints
Friday explained that Mist and his work in the AI space began when he tried to convince major retailers to deploy mobile experience apps on their networks.
“They said they weren’t going to do it unless they could promise that they could prevent controller crashes, innovate at least twice a year, and guarantee a great user experience,” Friday said.
AI has become part of making that happen. Friday said the retailer’s request is an early sign of a paradigm shift from traditional network support to cloud AIOps.
Introduction of AI is not just technical
There was also a cultural dimension to the change, Friday said. That meant convincing the IT support team to incorporate AI into their daily operations. Getting network support staff to embrace the change and relinquish the secure shell protocol keys used for encrypted remote access remains a challenge. “It’s like taking candy away from a baby,” he said. “They didn’t want to give up the key.”
By implementing an AI support model for retailers, we also learned on Friday that AI is not a one-size-fits-all technology.
“When I started Mist, I always believed that natural language was going to be the next user interface,” Friday said.
Networking has already moved beyond command-line interfaces to dashboards and natural language, and this is a logical step for pulling data out of databases, Friday said.
The rise of ChatGPT and agent AI opens up new possibilities. “At that time [AI] It’s much more powerful in terms of inference and generation,” he said.
Because Agentic AI is a non-linear, non-deterministic programming language, it has also changed the way developers approach their work, Friday said. “This is basically a new way to automate problems that used to be difficult.”
For example, AI could lead to networks that solve problems without a human user at the wheel. To get to that stage, IT professionals will need to trust AI to address network issues.
“It’s very similar to self-driving testing. Once you’re finally able to trust the car, you’ll let the driver out of the seat and let them go,” Friday said.
When AI needs limits
Friday warned that the use of AI could be ahead of its time. “If you have hundreds of APIs, you can’t expose them all to a large language model; it clutters the model,” he said. When introducing these APIs, hierarchy and organization are still important before LLM can process what it wants to do.
Why do people stay informed?
At least for now, the human element will also remain an essential part of leveraging AI, as long as IT professionals keep their skills up to date. In the past, programmers wrote code and tested it to verify that it worked as intended, Friday said. That linear process has changed with the advent of nonlinear AI.
Why developers struggle with change
Developers who have spent years programming in a linear manner may have a hard time transitioning to nonlinear AI, he said Friday. “They’re struggling with this new programming paradigm,” he says. “You’re better off hiring a kid out of school who isn’t set on programming a certain style, a certain way.”
