3 ways AI is redefining jobs in IT

Like the Internet and smartphones before it, AI is radically changing how people work. No group is feeling the impact of that more directly than IT professionals.

A November 2024 study by workforce intelligence firm Revelio Labs reveals that tech jobs—particularly database administrators, IT specialists, cybersecurity personnel, and engineers—are among the most exposed to AI. Nearly 60% of the tasks in these roles could be automated, according to Lisa K. Simon, Revelio’s chief economist.

Yet rather than eliminating jobs, AI is reshaping them. IT professionals who embrace AI are becoming significantly more productive, using automation to eliminate repetitive, low-value tasks. According to Freshworks’ 2024 AI Workplace report, 85% of IT departments now use AI at least once a week, and nearly half of 7,000 surveyed employees report that AI has boosted both their productivity and work quality.

What are IT teams doing with the extra time? They’re shipping more code and closing more support tickets. They’re reducing technical debt, auditing AI-generated software for vulnerabilities, and strengthening cybersecurity defenses. In organizations that are furthest along in AI adoption, IT pros are evolving into system architects, reimagining processes to maximize AI’s potential.

“Everybody talks about using automation to reduce headcount, but it rarely works out that way,” says Neil Sahota, CEO of AI research firm ACSILabs. “95% of the companies I work with realize there's more valuable work they can assign those people to do now.”

Read also: Why IT teams are leading workplace adoption of AI

Managing AI as part of the team

IT jobs are no longer just about managing software and infrastructure; they now include managing AI as a new member of the team. The challenge isn’t simply deciding which tasks to offload to AI but rethinking workflows to align with AI’s capabilities.

Sahota emphasizes that simply automating existing processes can replicate existing inefficiencies. Instead, organizations must redesign their workflows from the ground up to maximize AI’s efficiency.

For example, AI coding assistants can dramatically shorten code review cycles, allowing engineers to debug and ship software faster. By automating lower-level troubleshooting, IT teams can shift their focus to strategic, high-value projects.

Yet even when bots are handling the bulk of the work, human oversight remains critical. Auditing AI work products and coordinating workflows between people and AI systems are becoming critical functions. In many IT organizations, that could mean hiring or training a new kind of manager.

“In the same way you manage a junior employee, you need to manage the output from ChatGPT,” says Simon. “Over the last year, big tech companies cut a lot of middle management jobs. I think we'll actually see companies hiring more managers to oversee AI.”

AI needs more than just performance oversight; it requires guardrails. As AI systems gain autonomy, IT professionals must ensure they operate within the broader business context.

"If you rely on AI to take care of everything end to end, you'll end up with a bunch of laptops you're never going to use, wasting a ton of money and resources," says Hasmukh, founder of Teqtivity, an IT asset management firm. "You'll need a human to review these decisions.”

A new model for project management 

AI’s rapid evolution is also forcing a rethink of roles in project management, says Mark Campbell, founder and principal of 3dot Insights, a consultancy on emerging tech. As AI agents grow in sophistication, he says, we’ll start to see companies offering “AI employees as a service”—intelligent bots designed for specialized tasks at a fraction of the cost of human workers.

"We're moving to a services model that's more like Indeed or LinkedIn than AWS marketplace," says Campbell. "Hiring AI agents will be more like interviewing candidates for a job than evaluating technology."

This shift presents new challenges for IT leaders, such as managing stakeholder expectations.

“Some are going to believe AI is a magic wand, others will think it's the Death Star," says Campbell. "You've got to manage all those expectations, realistic or otherwise, and aim for consensus, not unanimous consent. If you're waiting for 100% approval, you're not going to get anywhere.”

Another challenge for project management in IT: Because LLMs are advancing so rapidly, managing scope creep will be more difficult. Projects demanding the latest AI advancements risk never being completed, while those built on older models may be outdated by the time they launch. Quality control also becomes murkier: Some AI-generated outputs, such as code, can be tested objectively, but others, like AI-generated marketing copy, require subjective approval.

A shift for leaders 

Ultimately, AI’s biggest impact on IT jobs may be in leadership. Every company needs a clear AI strategy—even if that strategy is to avoid it altogether, according to Campbell.

He compares today’s AI transformation to the dot-com era, when businesses that dismissed the Internet’s significance—like traditional bookstores and video rental chains—were blindsided by digital-native competitors.

"Companies that did not understand the fundamental changes happening around them were ill-prepared to take advantage," says Campbell. "Organizations like Amazon and Google that had a strategy early on did much better than those that didn't. I think we're at the same stage with AI."

For IT professionals, AI isn’t just another technology shift—it’s a fundamental redefinition of work itself. Those who can architect new roles, manage AI alongside employees, and align it all with long-term business strategy will be in the best position to compete and grow.