Will AI erode IT talent pipelines?

Generative AI is transforming functions throughout the enterprise, including in IT where its use has showcased the power of the technology.

Take, for example, how gen AI is speeding service delivery and improving the accuracy of services provided by the IT help desk by “looking at the history of the call logs and then providing a perfectly contextualized response based on what has worked in the past,” says Nate Suda, senior director analyst for AI strategy at research firm Gartner and its CIO AI Ambassador.

Such AI success stories have many executives — and workers overall — believing that AI will make many jobs obsolete, or at least eliminate workers’ need to know how to perform fundamental tasks, eroding key skills and experience within the talent pipeline.

AI coding assistants in particular are viewed by some as having the potential to eventually be meaningful substitutes for junior-level developer talent. With the possibility of AI-native software engineering on the horizon, how might the high-level skills necessary to guide future coding processes be attained if entry-level work is replaced by AI?

Research, Gartner’s Suda says, doesn’t bear such scenarios out. Rather, it shows that well-planned uses of gen AI, where the technology supports rather than replaces human workers, teaches workers how to do their jobs better and does so faster than other learning methods.

“If you are someone with zero experience and getting an AI prompt every time you do a task, you’re going to get really good really, really fast,” Suda says.

According to Suda, Gartner researchers found over the course of a six-month study that the addition of gen AI to places like the help desk boosted productivity. And researchers also found that employees retained those elevated levels of productivity and customer satisfaction when gen AI was offline.

“That strongly suggests that generative AI is teaching people to do their jobs better. And because it’s teaching them to do their jobs better, with that knowledge they then become more productive,” Suda explains.

He concludes: “Gen AI is a teacher, not a doer.”

Concerns over skills persist

There is, however, evidence that AI will indeed result in lost skills.

Studies show that increased AI use is linked to the erosion of critical thinking skills. Among them is a 2025 study from Microsoft and Carnegie Mellon University researchers, which found that the more an individual used AI tools to complete tasks, the less critical thinking they’re required to do, making it harder for the individual to muster those skills when needed.

Needed skills aren’t only at risk of disappearing; they also have a high likelihood to change.

The World Economic Forum in its 2025 Future of Jobs Report says workers can expect 39% of their existing skill sets to be transformed or become outdated over the 2025-2030 period.

The impact of AI in the IT workforce may be even more pronounced, with most IT professionals saying they expect a high percentage of their skills will be made obsolete by AI. One 2024 study found that 74% of IT professionals are worried AI tools will make “many of their day-to-day skills obsolete” and 69% of IT workers believe they’re at risk of being replaced by AI.

And a 2024 report from the AI-Enabled ICT Workforce Consortium found that 92% of IT jobs will see a high or moderate transformation due to AI.

AI’s impact on jobs, skills

AI’s perceived ability to automate tasks has workers and business leaders alike seeing human workers being replaced by AI in the years to come.

Nearly one third (32%) of workers surveyed by Pew Research Center believe AI’s use in the workplace will lead to fewer job opportunities for them in the long run. And according to the World Economic Forum’s 2025 report, 41% of employers globally — and 48% in the US — plan to downsize their workforce due to AI.

That, though, is mostly not happening, Gartner’s Suda claims.

“That’s what some are thinking: that AI will save us time and we can have headcount reduction. But that straight line to headcount reduction, we’re just not seeing that,” he observes.

Moreover, Suda says Gartner’s research shows AI does not benefit all workers equally. “Gen AI holds the potential to revolutionize productivity, but benefits are not uniform across workers,” he says. In fact, for some, generative AI actually increases time on task, Suda says.

More specifically, Gartner research shows that workers with low experience preforming tasks that are low in complexity are one of two groups that get the biggest boost. Highly experienced workers performing highly complex tasks is the other group that gets that biggest boost.

Workers in the middle — such as less experienced workers doing tasks that have a higher level of complexity — “see a marginal increase in value and productivity,” he says.

In IT, workers seeing the highest productivity gains are senior developers.

“It’s not that AI is doing the work for the senior developers, rather it’s that AI is a thought partner for these individuals,” he explains.

Meanwhile, the less experienced workers on the IT help desk who typically handle the less complex problems likewise get a big boost, with AI guiding and teaching them.

Replacement for tasks and some skills, but not workers

“The pervasive belief that gen AI is an automation technology, that gen AI increases productivity by automation, is a huge fallacy,” says Suda, though he admits it will eliminate the need for certain skills — including IT skills.

“Losing skills is fine,” he says, adding that machines have been eliminating the need for certain skills for centuries. “What gen AI is helping us do is learn new skills and learn new things, and that does create an impact on the workforce.

“What it is eroding is the opportunity for junior IT staff to have the same experiences that junior staff have today or yesterday,” he says. “Therefore, there’s an erosion of yesterday’s talent pipeline. Yesterday’s talent pipeline is changing, and the steps to get through it are changing from what we have today to what we need [in the future].”

Steven Kirz, senior partner for operations excellence at consulting firm West Monroe, shares similar insights.

Like Suda, Kirz says AI doesn’t “universally make everybody more productive. It’s unequal across roles and activities.”

Kirz also says both research and anecdotal evidence show that AI is replacing lower-level, mundane, and repetitive tasks. In IT, that tends to be reporting, clerical, data entry, and administrative activities.

“And routine roles being replaced [by technology] doesn’t feel new to me,” he adds.

He, too, says this won’t impact the IT talent pipeline. Having AI replace those lower-level tasks — and erode the skills associated with them — doesn’t mean IT workers will be unprepared to advance in their careers. After all, he says, the tasks and skills being eliminated by AI aren’t the kind of talents that create senior-level technologists, IT managers, and CIOs.

Moreover, Kirz says AI’s potential to erode certain skills is not where the technology will have its biggest impact on talent. AI’s impact on the workforce is more about how swiftly it will make lower-level workers into experts, as well as how it will shift what skills are valuable for workers overall, he says.

For example, AI enables some entry-level IT workers such as programmers and system designers to work at higher levels putting them very quickly on par with mid-career and midlevel professionals, Kirz claims. In other words, lower-level talent using AI can do what middle managers do. That, Kirz says, will drive “explosive demand for young talent” because they can do the same work at a lower cost.

Kirz also says research indicates AI will create demand for new skills, as well as new types of work.

CIOs would do better to focus on ensuring up-and-coming talent have or can develop the skills needed for the organization’s future rather than seeking skills that had been valuable in the past.

That means looking for entry-level IT workers who have prompt engineering skills, even if they may not have much coding experience, for example — a dramatic shift, for sure, in IT talent management.

AI’s impact on the tech workforce

Sanjeev Vohra, chief technology and innovation officer at IT services and consulting firm Genpact, sees synergy between AI and IT professionals driving significant value going forward.

But to make good on the promise of AI, IT pros will need to change the way they work.

“IT professionals will now need to focus more on interpreting AI outputs, ensuring accuracy, and making strategic decisions based on AI insights,” he says. “This shift calls for stronger problem-framing abilities, a deeper understanding of AI ethics, and expertise in managing AI-driven workflows. Instead of routine coding, developers will play a greater role in system design, advanced debugging, and optimization.”

To ensure they are able to get there, “entry-level IT professionals must master AI-assisted coding, debugging AI outputs, and prompt engineering while strengthening core programming and problem-solving skills. Adaptability, critical thinking, and ethical AI awareness are equally essential in this evolving landscape,” he says.

And IT leaders will have to establish training pathways to help lay the groundwork for new career paths.

“AI is clearly reshaping IT career paths, shifting focus to dynamic, skills-based growth,” Vohra says. “For IT organizations, this demands a new approach to talent development — one that prioritizes AI fluency, problem-solving, and cross-functional collaboration.”

Like previous evolutions in IT work requirements, some current critical skills may quickly become irrelevant as AI and its use cases advance in the workplace. IT leaders who consider the impact this will have on their talent development strategies and pipelines will have a leg up in ensuring their organizations are primed to make the most of what’s to come.