I'm starting my fourth semester studying Information Systems Management at Auburn. During the first week of class, nearly every discussion centered on AI, including how much it will be used for coursework. Most of my classmates and professors seem enthusiastic about it, and students are being encouraged to use AI for a lot of their assignments.
I strongly dislike AI and feel increasingly out of place. I've enjoyed the major so far and still want to work in IT, possibly starting at a help desk and eventually moving into systems or network administration. However, I'm worried that opposing AI means I chose the wrong field.
Is there a relatively low-AI area of IT, or should I accept that using AI will be part of the job? I could probably tolerate heavy AI use in school for a while if I knew I wouldn't necessarily be required to rely on it throughout my career.
3 Answers
Most IT jobs probably won’t become “AI all day,” especially hands-on infrastructure work. There will still be networks, identity systems, servers, endpoint problems, hardware, outages, documentation, vendors, and users to deal with. However, employers may expect you to understand or support AI products, and tools may be built into ticketing, monitoring, scripting, and knowledge-base workflows.
A practical compromise is to use AI selectively: explain unfamiliar concepts, summarize large logs, draft documentation, or provide a first version of a script. Never run generated commands blindly, and don’t use it as a substitute for learning. Your skepticism could actually be valuable in roles involving governance, security, compliance, and safe deployment.
The answer depends on whether you dislike the marketing and careless use of AI, or whether using any AI-assisted tool is a firm ethical boundary. If it’s the first, you can absolutely stay in IT: learn how the technology works, understand its limitations, and push back when it’s being used irresponsibly. If you refuse to touch it under any circumstances, finding a job where that never matters will be very difficult.
You don’t need to become an AI enthusiast. Focus on building strong skills in operating systems, networking, troubleshooting, security, and automation. Those skills remain valuable, while familiarity with AI will help you judge when it is useful and when traditional methods are safer.
You don’t have to like the hype, but completely refusing to learn about AI will probably limit your options. IT has always involved adapting to automation, scripting, virtualization, cloud platforms, and new management tools. AI is becoming another tool in that chain.
That doesn’t mean blindly trusting it or letting it replace your understanding. Learn the fundamentals well enough to review its output, catch bad assumptions, and understand the security and operational risks. You can be skeptical without being unable to use it.
The physical tasks are still human, but more infrastructure is software-defined and accessible through APIs. AI can already help provision systems, modify scripts, analyze logs, and manage deployments. The important skill is knowing what authority to give it, how to test changes, and when its answer is wrong.