AI is already reshaping the IT job landscape, with layoffs and demand for AI skills creating a mismatched market for IT skills. But the technology is also contributing to possible contraction for IT workforces as enterprises IT leaders find themselves redefining IT roles in the wake of AI’s rise.
According to the Indeed 2025 Tech Talent Report, overall tech job postings were down 36% in July 2025 compared to early 2020, with postings for senior- and manager-level IT jobs down 19% and standard and junior tech titles down 34%.
“We’re seeing two forces at work here: the broader tech cooldown and a structural shift driven by AI. As routine tasks get automated, the bar for entry is rising; companies want fewer hands-on coders and more people who can oversee, integrate, and scale AI systems,” says Linsey Fagan, global client strategist at Indeed.
The rise of AI has created a shift in the skills companies look for, as well as how they train workers to establish new mindsets around embracing AI for their work. As a result, roles across the IT spectrum are poised to change, including software engineering, QA, data analysis, project and product management, and IT service management, Indeed reports.
Evolving roles and redeployments
Generative AI has shifted the skills requirements of IT roles, with increasing emphasis on prompt engineering, AI integration, and complex problem-solving, says Manu Sood, senior vice president of technology at AvidXchange.
“I strongly feel every single level of role in software engineering as we know it today is going to change, and we will have to redefine the roles,” says Sood, who gives the example of junior engineers who typically focus on writing “boilerplate code, debugging, and documenting” — all tasks now largely automated by AI. As a result, employers are now looking for junior engineers with more diverse skills such as problem-solving, problem-framing, and reviewing AI code.
According to Indeed, 37% of tech professionals say their role has been “redefined or restructured due to gen AI in the past two years.” The majority of survey respondents (52%) say that IT positions have been reassigned at their organization, and 26% say they’ve seen layoffs or role elimination related to AI adoption. While only 23% expect to be impacted by AI-related layoffs, 41% say that they’d start looking for a new role if layoffs happen within their company, even if they weren’t impacted. As a result, companies need to have a strong messaging strategy around AI to avoid an excessive drain of talent.
“Redesigning entry-level roles is key. Instead of narrow tasks, rotate early talent through hands-on work in data quality, AI output evaluation, systems thinking, and responsible AI. Pair that with strong mentorship to build breadth and leadership potential early,” Indeed’s Fagan advises.
Among those organizations already redeploying IT talent, Indeed reports that cybersecurity, data analytics, and AI teams are the top areas where reskilled IT pros land.
Upskilling takes center stage
Training is integral to easing the transition for companies and IT pros alike.
While the majority of respondents (54%) to Indeed’s survey said their organization offered technical courses or training, 33% said they don’t feel as though they are receiving enough training from their organizations, and 64% feel a moderate to very high pressure to upskill. IT leaders would be wise to revisit their training strategies given these sentiments.
At AvidXchange, Sood says they’ve introduced a mandatory prompt engineering course for the entire organization. She points to prompt engineering as one of the most important skills for working productivity and efficiency with generative AI. Since introducing the course, AvidXchange has seen an increase in employee adoption of AI, as well as the quality of AI prompts and AI-generated work, she says.
Sood adds that the company has been intentional about creating a “culture where humans still feel empowered, like they’re in the driver’s seat,” emphasizing that “AI is a co-pilot, not the other way around.” AvidXchange’s leadership has also worked to ensure all employees can practice and experiment with AI, learning alongside AI as the technology evolves.
“AI is also a technology, right? Technology is going to keep evolving, but what’s going to make companies resilient is how they nurture that adaptability, continuous learning, and inclusivity in the workforce — across all the generations and all levels of talent — because that is what is going to sustain long-term innovation,” Sood says.
Mentorship key in AI adoption
When it comes to trusting AI, midlevel career professionals are the most comfortable with AI adoption, according to data from Dice’s 2025 Trust Gap in Tech Hiring report. Entry-level and early career professionals, along with senior experts, are the most likely to reject AI-heavy processes, Dice reports.
Sood saw this trend in her own organization, with midlevel workers more “willing to embrace and experiment with [AI],” while more senior workers expressed skepticism, or “felt they had to do more work, because AI was producing garbage code or didn’t understand the context, sometimes going in loops trying to auto-correct itself.”
Sood says that in the past 12 to 18 months, however, AI tools have become smarter, more efficient, and better at “understanding broader context,” which has increased the comfort levels for more senior IT pros using AI at AvidXchange.
To better prepare AvidXchange’s IT workforce for the future, the company has also channeled the AI adaptability of midlevel workers into a mentorship program, Sood says. Employees who are more comfortable with AI are paired with more hesitant or entry-level workers who need to gain more confidence and experience with using AI.
Employees can also play around with AI tools, with space and time to practice and gain skills through enterprise platforms. As a result, more employees are “now more receptive to using [AI], embracing it and putting it in their daily workflow of writing software code,” she says.
The key to AI adoption, while maintaining talent retention, comes down to a realistic vision for AI, transparency regarding how AI will be deployed within the organization and how roles will be impacted, and establishing an environment of learning and experimentation around AI.
“The smart play is balance: Use AI to boost productivity, but reinvest that capacity into mentorship, upskilling, and growing the next generation of builders. Ignore that, and you’re not just alienating younger workers, you’re sidelining your future. Long-term winners will be those who use AI to amplify people, not alienate them,” Indeed’s Fagan says.
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