I’ve tried to direct more attention in this space to AI’s potential impact on the enterprise network (see here and here), and it seems clear to me that network upgrades will be a critical step in scaling AI applications. I recently had a chance to talk with one of the smartest people I know when it comes to understanding network dynamics, Sorell Slaymaker, principal consulting analyst for networking, security, Unified Communications at TechVision Research, who offered some specific areas where enterprises will need to focus.
Sorell called out five areas where network infrastructures will need to advance in order to handle the volume and nature of traffic AI will bring:
- Reliability: Five-nines (99.999% availability) won’t be optional for any enterprise that turns critical business processes over to AI-driven applications, according to Sorell. That’s because agentic workflows will be using AI assets that reside in the cloud and therefore must be accessible without interruption. Further, the more business-critical, even life-and-death the nature of the process, the greater the risk, requiring ultra-high reliability.
- Speeds: Networks will likely need to run at 100 Gbps or faster, which means enterprises are likely facing a transition from heavy use of Internet circuits in SD-WAN based networks to private optical networks. And given the previous point, these networks will need full physical redundancy end to end.
- Agility: AI-driven traffic is likely to be bursty and variable throughout the day, meaning enterprise networks will have to be highly elastic, capable of scaling up and down in capacity within minutes.
- Data replication: Most enterprises will rely on multiple LLMs, often within the same process or application. This will entail more complex networks and connectivity to more providers and hosts than basic cloud services required.
- Security and compliance: All of this networking infrastructure will of course have to be secured, in an environment where AI is being employed both as an attack tool as well as for defense.
Individually, none of these elements is new to networking professionals. But taken together, they represent major upgrades to the network, and the enterprise’s success with AI will depend directly on making all of this work together – not to mention dealing with the budget impacts.
Of course, the hope is that AI will also help to meet some of the challenges. Sorell points out that AI-enabled management tools are already helping network engineers and managers run the network more efficiently and with fewer staff in many cases. As systems continue to get more automated, IT pros will also seek to manage more proactively and avoid problems before they result in outages or other problems.
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