How to futureproof your IT team in the AI era

While enterprises brace for the changes AI will make to the nature of work, IT organizations are already seeing a big impact. Traditional entry-level work is disappearing as AI automations take over functions in areas such as the IT help desk, manual testing, language programming, and security monitoring, removing the bottom rung of the IT career ladder.

A recent report from Indeed says the hiring appetite for tech workers has cratered across a wide swath of the sector, and has hit less-experienced job seekers particularly hard.

AI is also transforming the roles of experienced IT professionals and managers, creating new roles and responsibilities, and has the potential to eliminate some jobs entirely.

In a January 2025 LinkedIn research report, the company stated that by 2030, it’s expected that 70% of the skills used in most jobs will change, with AI emerging as a catalyst. “So if you want to stay adaptable, you need to adopt [AI] technology,” says Niha Mathur, VP of engineering, enterprise innovation at LinkedIn.

Demographic trends also point to a constrained long-term supply of IT talent for the foreseeable future. That’s one reason why it’s critical CIOs focus on identifying skillsets of the future and training IT professionals to meet those demands, says Will Markow, CEO at research and advisory firm FourOne Insights.

For Shamim Mohammad, EVP and CITO at CarMax, the changes have been seismic. “We’re seeing the end of the traditional IT department as we know it,” he says. “People need to be strategic problem solvers who can translate business needs into technical solutions quickly,” adding that CIOs need to lead a transformation of the current IT department structure into cross-functional teams that have a talent for collaboration, critical thinking, and problem solving.

Reengineering IT organization structures, preparing teams for the new responsibilities, and providing an onramp for IT careers is especially critical now because experienced people are in short supply. “We’re facing a senior talent exodus in the IT industry that’s creating massive knowledge gaps,” Mohammad says. “We can’t simply hire our way out of this problem.”

A destabilizing force

The challenge with AI is it’s at the same time an augmenting technology and a destabilizing one that’s forcing a change in the way work gets done, says Fiona Mark, principal analyst at Forrester. Employees fear it may replace them, and it’s for some functions, but the technology still needs human oversight. “It’s fallible,” she says. “We still need human in the loop skills and technical expertise to determine if it’s solving a problem or introducing more technical debt.”

But there’s no mistaking the fact that purely executional roles are shrinking, says David McKee, tech founder and managing partner at Counterpoint Technologies. That means a lot of routine work of coding, security monitoring, and other functions where entry-level workers in IT gain experience is going away.

“Demand has dampened for workers skilled in specific programming languages and tools,” says Markow. “For example, skills such as CSS, HTML, and C# have seen demand drop 59%, 58%, and 56%, respectively, since 2023. In fact, demand for entry-level IT roles generally has declined 15% during that time, with postings for entry-level web developers, computer support specialists, and software developers dropping by 34%, 23%, and 22%, respectively, according to a FourOne Insights analysis of job postings. “These roles emphasize basic tech support or programming skills — tasks that AI is well suited to perform,” Markow adds.

And Ann Funai, CIO and VP of business platform transformation at IBM, says what’s entry-level today won’t be tomorrow. “The knowledge and foundations are the same, but the specifics on how to build and execute are changing,” she says. For developers, for example, foundational knowledge of object-oriented programming will still be relevant, but the details of programming language syntax or deep code review will be less so. “In fact, it may become unimportant as our ability to use natural language to develop continues to evolve,” she adds.

So given how much manual and repetitive entry-level IT work is being automated, the critical question is how should those entry-level IT roles be redefined? “They’re not equipped to enter the workforce at the level that’s needed,” says Forrester’s Mark.

Elevate the entry level

AI is replacing tasks that are repetitive and lack complexity. “Instead of cutting their teeth on repetitive tasks, juniors should be learning architectural thinking, systems integration and innovation from day one,” Counterpoint’s McKee says. “That means using simulations, apprenticeships, and shadowing senior engineers so they learn how to design and solve problems, not just execute.”

CarMax is moving to an apprenticeship model for entry-level IT workers, pairing junior staff with experienced mentors. It’s also rolling out AI-powered training, and creating working environments and a culture where new hires can collaborate, learn, and experiment safely. In this way, Mohammad says, institutional knowledge gets passed on as new hires learn problem solving, prompt engineering, how to verify outputs, and other higher-level skills. Because of that new approach, what CarMax looks for in an entry-level IT hire has also changed. “We’re hiring for problem-solving ability [and] for people who are inherently curious and adaptable,” he says.

Similarly, IBM runs an annual watsonx challenge that’s open to IT and everyone else in the company. “It’s an opportunity to get hands on with products that are shaping the future of work, give real feedback, and show what others come up with,” says Funai.

Scale up on training

IT professionals need to train up for key roles directly related to AI, according to LinkedIn’s AI Labor Market Tracker. “AI agents are the fastest-growing technical AI skill in 2025 so far with AI engineers adopting the latest technologies rapidly,” the report states, adding that AI engineering hiring is up 25% year-over-year, withAI engineering job postings accounting for nearly 7% of all technical job postings on LinkedIn.

External training programs can also give staff a boost. Skillsoft, for example, offers learning programs in such areas as AI and ML, cybersecurity, and infrastructure while focusing on systems thinking, ethical reasoning, and the ability to communicate across functions, says Greg Fuller, VP of Skillsoft Codecademy. “IT professionals need to build AI literacy, develop a problem-solving mindset, and learn how to communicate technical insights to nontechnical stakeholders,” he says, while CIOs need to be more data-driven in how they assess and close skills gaps. “Gut instinct isn’t enough anymore.”

Fuller is also seeing a growing demand for professionals who can bridge technical expertise with business insight, like cybersecurity analysts who need to understand threat modeling in cloud environments, he says, or data scientists expected to communicate insights through compelling data storytelling. “To support that shift, we’re offering hands-on labs, scenario-based training, and AI-powered learning journeys that help professionals build real-world capabilities in areas like threat detection, data storytelling, and cloud-native architecture,” he says.

But when it comes to training up IT staff, CIOs shouldn’t rely exclusively on external training programs. Right now, says FourOne Insights’ Markow, skills need to evolve faster than how traditional education providers can keep up, so organizations need to be proactive and have internal continuous workplace readiness programs in place. “We’re in this really weird moment when the pace of tech change is outpacing our ability to adapt and skill up people,” Forrester’s Mark says. “Unfortunately, very few organizations are actively working on this.”

Skills in demand

Going forward, the three areas of highest demand will revolve around AI, analytics, and data; cloud management; and cyber security, says Mark. Depending on the role, it may pay to develop career-adjacent skills in those areas. With cyber security, learning how to secure LLMs and mitigate AI-driven voice phishing, which AI can do at scale, will be critical. And cloud professionals must learn to design for AI applications in a way that they’re not running up massive cloud computing costs.

Fuller at Skillsoft says data analysts need to become AI model supervisors who don’t just interpret data but validate and monitor outputs, and UX designers should be learning to design for human-AI interaction. Job roles will also become more fluid. “The only constant in this space is evolution, he says. “CIOs can support that by treating skilling as a strategic imperative.”

And AI struggles with highly contextual problems or deeply complex problems after all, so enterprises need domain experts — distinguished engineers or architects — who understand how AI technology implementations work and can step in when they don’t, Mark adds. This is a career path for senior engineers, but to keep those professionals once they attain that level, IT leaders will need to compensate them accordingly. “The role must be valued and well compensated because it’s potentially a more challenging role in terms of the difficulty of the problems they’re solving,” she says.

For Mathur at LinkedIn, the core responsibilities for IT professionals include problem solving, abstract thinking and rigor. “Skills we see on the rise are LLM and AI-enabled application development,” she says, and interpersonal skills are also vital for engineers, who increasingly need to collaborate with domain experts while focusing on business outcomes. “We’re already seeing interpersonal skills across engineering roles expand.”

Funai at IBM adds that IT professionals need four abilities to stay relevant: curiosity, a desire to learn, collaboration, and partnership. Soon, she says, it won’t be possible for a team of individuals to do work in a silo and secure a great result. LinkedIn’s Mathur concurs. “The era where you own only one part of a workflow is changing,” she says.

Successful IT professionals will be the ones most comfortable with the technology, and who have the ability to jump in fearlessly and learn quickly, Mathur adds.

In-demand new roles include digital assurance managers, AI governance leads, and hybrid engineers, says McKee, and existing roles will carry more leadership and integration responsibilities. In this new era, IT professionals with systems thinking, AI fluency, and people skills will do well.

“Since 2021, 22% of the top skills requested in IT job postings have changed,” Markow says. “Fields related to AI, automation, and regulation have seen rapid growth, while the demand for MLOps, workflow automation, and GDPR has grown 376%, 106%, and 86%, respectively.”

In-demand entry-level job postings include AI engineers, up 175%, UI/UX developers, up 40%, and data engineers, up 21% since 2023, Markow adds. But most entry-level IT roles today are either computer support specialists, software developers, or network administrators.

As for what skills IT practitioners need going forward, McKee says the big ones are “architectural thinking, integration, assurance, AI literacy and above all, the ability to communicate and lead change.”

Now’s the time for proactive leadership

How can IT leaders futureproof their teams? Reengineering IT roles is key, but too many organizations are only focused on short-term productivity gains, CarMax’s Mohammad says, including those that eliminate entry-level work. If that doesn’t change, he adds, companies will create skill gaps that’ll hurt everyone down the line.

Markow agrees, saying that supplanting entry-level roles with AI may lead to short-term savings, but it raises the specter of long-term talent pipeline challenges. To address that and to futureproof IT teams, CIOs should:

• Restructure entry-level roles around higher-level tasks less likely to be subsumed by AI, and look for opportunities to help entry-level IT professionals gain experience in areas that require human oversight. “This will mean emphasizing non-technical skills alongside technical mastery, so IT workers can move from technical execution to technical oversight earlier in their careers,” Markow says.
• Offer extended internships and apprenticeships, mentorships, and ongoing access to training,as well as skill development resources to help IT employees get up to speed and improve retention. CIOs should rethink career pipelines and build blended teams that combine automation with empathy.
• Begin those training and reskilling programs by addressing the low-hanging fruit first. “IT jobs with AI skills have an average salary premium over $30,000 compared to other IT jobs, for example, so targeted training on these high-growth, high-cost skills can maximize the ROI of reskilling efforts,” Markow says.
• Teach good communication and people skills since they’rekey parts to train and retrain. “Don’t just train for technology,” says Counterpoint’s McKee. “Invest in soft skills and assurance, and build career ladders that value both technical and human capabilities.”

Simply put, teams should be given the opportunity to experiment. “Create an environment where not only success is celebrated, but also those smart risks that didn’t work out as hoped, and the learnings that came from them,” Funai says.