ChatGPT launched publicly in November 2022 and by February 2023 there were approximately fifteen hundred articles per week either predicting the end of IT jobs or debunking that prediction. I have been watching this conversation carefully because I teach IT professionals for a living and the anxiety was real enough that it was showing up in my classrooms.
Here is what I actually think after a few months of paying close attention to what AI tools can and cannot do in IT practice contexts.
The doom scenario, that large language models are going to automate away IT jobs at scale in the near term, underestimates the complexity of real IT work. Yes, ChatGPT can write a Bash script. Yes, it can explain a networking concept. Yes, it can draft documentation. What it cannot do is understand your specific environment, your organizational constraints, your undocumented tribal knowledge, or the context behind why things are configured the way they are. IT work at any level of seniority is not primarily about performing discrete tasks with known inputs and outputs. It is about making judgment calls in messy, contextual situations. Language models are not good at that yet.
The complacency scenario, that AI is just a toy and IT professionals can safely ignore it, misses the real story. The professionals who are going to be most valuable over the next five years are not the ones who ignored AI tools but the ones who figured out how to use them effectively to do more work with less effort. AI-assisted scripting, documentation generation, log analysis, and troubleshooting support are becoming part of the practical toolkit for IT work. Knowing how to use these tools effectively is becoming a real differentiator.
There are also new job categories emerging around AI infrastructure. Organizations deploying large language models in enterprise contexts need people who understand the infrastructure requirements, the data pipelines, the access controls, and the governance considerations that come with AI systems. That is infrastructure work. It is security and governance work. It is a career opportunity that did not exist in the same form two years ago.
The Microsoft certifications around Azure AI services represent one path for IT professionals who want to formalize their AI infrastructure skills. The AI-900 Azure AI Fundamentals provides a baseline and the AI-102 Azure AI Engineer Associate goes deeper into implementation. Microsoft’s certification details are at Microsoft Learn.
The honest career advice is to engage with AI tools actively rather than avoiding them out of anxiety or dismissing them out of skepticism. Use them in your work. Understand where they help and where they fall short. Develop opinions about them based on experience rather than coverage. That practical familiarity is going to matter more than any specific certification in how you navigate the next few years.
Brian Rhoades is a Senior VMware Instructor and IT veteran with more than 15 years of hands-on experience in virtualization, systems engineering, and cloud infrastructure. He has trained thousands of IT professionals to confidently work with VMware vSphere, vSAN, and NSX, and has authored multiple books and study guides for outlets across the industry. Brian has a habit of being somewhere new every few weeks, which if you've ever tried to pin down a good VMware instructor, explains a lot.