AI-powered infrastructure and management platforms are making their way into enterprise networks. I say “beginning” because despite a lot of AI-washing marketing efforts over the past few years, much of what has been described as “AI-driven” or “AI-powered” hasn’t really materialized. It’s not that these systems don’t do what the marketers say they do, as much as they don’t do it the way they suggest they do.
Even some of the tools that really use AI in meaningful ways, with results that are distinctly different from what’s possible without it, don’t feel qualitatively different than they did before. They might be better, for example by dramatically reducing the number of false positives in the alert traffic, but it’s no different.
This is starting to change now. AI tools that feel different to handle, that are changing the way network administrators work with their tools, are beginning to enter the market. A strong example is the introduction of virtual assistants who can have meaningful conversations about what is happening in the network, and can (if allowed) take actions that change the function of the network. This shift from just another tool to kind of a co-worker will show network teams that real change is happening in a way that better spec sheets and user interfaces can’t. They will make it profoundly clear that information technology is entering a new territory.
Not a moment too soon. The population in the Land of the Grid is beginning to feel a little shrinking and aging, with long-time engineers and administrators retiring or moving on to other types of work and not being replaced by legions of eager young newcomers. Networking has never been the most attractive of jobs, and most of the excitement in enterprise IT hasn’t focused on networking for many years now. People entering technology are likely to be drawn to areas like robotics, metaverse programming, data science, and (yes) AI.
Network employee demographics being what they are, it is inevitable that any medium to large sized network will end up with AI-powered tools in the near term, as they will be seen as easier to get and use than new employees. each network of any Size will do so in the next seven or eight years, as AI will be increasingly integrated into the platforms themselves.
AI dynamics in network organization, as with many other forms of automation, will focus on four modes of interaction: offloading, reskilling, desktopization, and displacement.
Offloading AI means putting AI tools under the leadership of trained and experienced networking professionals to help them do their work. The idea is to make networking professionals more efficient by allowing them to offload tasks that are repetitive, complex, time-sensitive, or that require extremely high levels of focused attention, but are not creative. This should free up these scarce and precious resources to do other high-level work instead, with minimal supervisory attention to what the AI does. (Human attention is the most valuable resource in any IT store.) The network team does not shrink, and its suite of services can even grow without the team also having to grow to make this possible.
Reskilling allows network staff to be trained to move to other parts of IT or to completely different types of jobs. It also includes the idea of using artificial intelligence to help train new network employees until they reach proficiency. The network team may shrink or see more sales, but its ability to get work done is not diminished.
Deskilling is a different kind of result, the one we saw at work in tools and dies in the aftermath of World War II. (Check out David Noble’s production forces For details.) New tools are being brought in to allow less skilled employees to do the work of more skilled employees, with no intention or allowance for them to become more skilled as they work. Entire areas of expertise will transition to silicone and fall out of the job requirements for most positions. This shift in skills to software or firmware makes it easier for the organization to find suitable employees to network because the requirements are lower.
Displacement is the end point of the office whirlpool, with AI tools in the hands of IT professionals simply replacing networking professionals. This may be something that has been done to me Network team proactively, by having management try to rid itself of the burden and cost of hiring, or something might be done by Grid team for itself, using artificial intelligence to enable the soft landing of an organization that can no longer hire and retain employees skilled enough to do the work.
Network engineers and administrators and IT leaders really need to think and plan about why and when to adopt AI tools, how to use them to best effect, and how to reshape enterprise networks in their wake.
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