Why Might AI Take IT Engineers' Jobs?
Before looking at what IT engineers can do to protect their jobs from AI, let's discuss why AI potentially threatens workers in IT.
The main reason is obvious enough: Generative AI technologies are capable of helping automate a lot of complex work that could previously be handled only by human engineers. It can write code to configure cloud security policies, for example, or help interpret and process help desk tickets. AI also stands to help streamline monitoring and incident response workflows, reducing the number of humans needed for these tasks.
Again, reasonable people can debate whether and to what extent AI might actually totally supplant humans in IT operations roles. Generative AI technologies remain relatively young, and it's not yet clear how good they'll prove to be in the long run at performing complex IT work. On the other hand, it's not crazy to imagine many companies looking to cut their IT teams and replace them with AI-powered tools, especially during economically turbulent times.
How to Protect Your IT Operations Career Against AI
If you work in IT and are worried about how AI could negatively impact your career, there are steps you can take now to help ensure you remain employable even in the event that AI does end up becoming capable of automating a lot of IT work.
Master less common technologies
Learning less common technologies might not seem like good career advice in general. But it makes sense if you want to prevent AI from taking over your work.
The reason why is that in most cases, AI tools can only work with technologies that are widely documented. After all, their algorithms train on existing data, so if there isn't much publicly available data about how to use a given IT tool, operating system, or so on, AI probably doesn't know much about it.
By learning more obscure technologies, IT engineers can gain a degree of confidence that they'll always know things that AI doesn't.
I'm not suggesting, by the way, that you go out and master the most obscure technologies you can find. If they're that obscure, chances are no one is using them or will pay you to work with them. Instead, look for technologies — like alternative clouds, for example — that are relevant to many businesses but are not as widely known as more popular technology.
Sharpen your cybersecurity skills
AI is good at managing IT workflows that are predictable. One thing that makes workflows unpredictable is cybersecurity problems.
On top of that, there is likely to be a lot of concern among businesses about whether the configurations or code that AI tools generate for them is actually secure. AI lacks the contextual knowledge or expertise necessary to prevent security risks.
For both of these reasons, IT engineers who are good at cybersecurity, and who can work through nuanced security issues that AI isn't primed to handle well, will likely become especially attractive in an AI-dominated world.
Become a hardware expert
One thing AI will probably never be able to do is maintain hardware. Short of the introduction of armies of robots that are smart and dexterous enough to perform complex tasks like replacing hard disks, plugging in network cables, or setting up new server racks, hardware-related work will always require humans.
Become a people person
There's a good argument to be made that the very most important skill in IT doesn't involve technology. Instead, it's learning how to interact with people. To be a good IT operations engineer, you need to be able to figure out what the people you support actually want, as well as to communicate with them effectively.
These are tasks that AI might be able to handle in a superficial sense. But because AI lacks true human emotion, it's unlikely to be able to navigate complex social relationships.
This means that the better your people skills, the more important you'll remain in an AI-centric IT industry.
Learn to support AI technology
Last but not least, IT engineers who are capable of maintaining and supporting AI technology will probably always be in demand. Someone has to understand what it takes to deploy, monitor, and manage AI services, which are different from other types of workloads in many respects. You need massively scalable compute infrastructure to train AI models, for example.
So, go out and learn about how large language models actually work, how they operate, which types of infrastructure they depend on, and so on. You'll set yourself apart from the typical IT engineer and become an essential resource for any business that wants to deploy its own AI technology.
AI may end up making some IT jobs obsolete. But it will amplify the importance of certain IT skills or expertise, creating opportunities for IT engineers who want to ensure that they remain relevant even if AI upends the IT industry.
About the authorChristopher Tozzi is a technology analyst with subject matter expertise in cloud computing, application development, open source software, virtualization, containers and more. He also lectures at a major university in the Albany, New York, area. His book, “For Fun and Profit: A History of the Free and Open Source Software Revolution,” was published by MIT Press.