CIO Think Tank: AI-native networking

Artificial intelligence (AI) is the fastest-evolving, fastest-adopted enterprise technology — possibly ever. But how will it change IT operations and what’s needed to support the next generation of AI and machine learning applications?

Those are the questions explored in virtual CIO Think Tank roundtables held in April and May 2024. IT leaders from a variety of industries took part in two lively panel discussions, identifying AI’s potential use cases and demands; hurdles for enterprise adoption; and ways to approach the needed technology, infrastructure, and skills.

[ Download the full CIO Think Tank Roadmap Report: AI-Native Networking ]

The roundtables were facilitated by Foundry’s John Gallant, enterprise consulting director, and Barbara Call, global director of content strategy, and included experts from industry research firm IDC; editorial leadership from Foundry; and the CIO and a top engineering expert from CIO Think Tank partner Juniper Networks.

The participants drew on their own experience and knowledge to share their views on how AI will reinvent IT operations, as well as the strategic and tactical approaches to confronting the key challenges of AI today. Where is the most immediate value from AI? What infrastructure and skills will you need today and tomorrow? And how quickly will AI earn trust to operate with the most sensitive data and facilitate high-stakes decisions?

AIOps: improving network performance and intelligence

The enterprise network — already bigger, faster, and smarter than ever — is somehow still ripe for more AI-driven improvement.

For example, Harish Bhatt, head of engineering at Early Warning, noted, “In this hybrid world of cloud and on-prem, predictability of the network is very important. When we use multiple network providers, sometimes the links [between providers] kind of flicker, and in financial applications, it becomes very hard to lose even a five-second blip.” This is one sort of operational challenge that IT leaders think AI can address.

For starters, CIOs hope that AI’s ability to find patterns in huge data sets will provide a broader view of network and service performance. “In our network, a lot of people have the ability to detect areas of improvement within the application stack or the full tech stack,” said Heather Milam, VP of technology at Travelport. AI, she said, could “free up the time to actually monitor what’s going on from the top to the bottom and identify opportunities to make it more efficient throughout the whole end-to-end service, versus just within the network.”

“We manage some locally hosted energy solutions where there’s a control network, which may be feeding into a local network, which then feeds into the cloud, which then comes through another set of firewalls….” said Steven Nieland, VP of software engineering and controls at Faith Technologies. “There’s a bunch of different translations of data as it goes through that pipeline, and trying to track problems can be very time intensive. We hope AI can serve as another set of eyes there.”

Several panelists also mentioned that AI can help in scaling up the enterprise network. This is a pressing need in industries seeing lots of merger and acquisition (M&A) activity. Combining organizations presents abrupt and idiosyncratic challenges in capacity planning, equipment choices, and more.

Download the Roadmap Report to learn about the range of near- and long-term use cases IT leaders are considering and how they are laying the groundwork for success.

Read more about AI in networking:

• Should AI initiatives change network planning?
• The real risk of AI in network operations
• IT pros worry about network data being fed to AI tools