AI won’t take over everyone’s jobs overnight, but some careers in the tech industry are at a greater risk than others.
Although imperfect, generative AI tools like ChatGPT and Google’s Gemini are improving faster than many of us can keep up. However, this progress stands to threaten some of the most skilled jobs out there, including many tech industry-adjacent roles. Some would argue this transition has already kicked in, given the persistent rounds of layoffs that have resonated throughout 2023 and 2024. So on that somber note, let’s take a clear-eyed look at the specific tech jobs most likely to be disrupted by AI, and what skills will be essential in this evolving landscape.Will AI replace tech jobs and which ones are at risk?
Contrary to popular belief, artificial intelligence isn’t going to replace all of us or our jobs overnight. History has proven that automation tends to create new opportunities rather than causing mass unemployment. More importantly, though, the AI of today often requires human intervention to correct obvious mistakes. All of this suggests that generative AI is more likely to augment existing jobs than replace them altogether.
If you’ve ever looked behind the scenes of a website or app’s development, you’ll know that much of the process involves repetitive tasks. Developers have to write dozens of lines of boilerplate code, sift through badly written documentation, and test their products under a variety of conditions. Each one of these tasks can become simpler with AI, while still requiring human input or supervision. Likewise, many tech roles demand skills in risk assessment, critical thinking, and decision-making — areas where current generative AI capabilities fall woefully short.
So with that in mind, here’s a list of tech jobs that AI could upend, and potentially replace, in the coming years.
AI poses a significant threat to data entry and analysis roles, across nearly all skill levels. Case in point: even the most difficult and manual kind of data entry jobs that involve porting information from paper to a digital database can now be performed using a combination of optical character recognition (OCR) and natural language processing (NLP).
