How AI automation is reshaping the IT leadership pipeline

In the wake of AI, the early-talent job market is in decline across all jobs and industries, with a 10% drop since 2021, according to a recent report from SAP. When isolated for the top 10 most common entry level job titles, including software engineer, customer support, and data analyst, job openings declined 35% from 2024 to 2025.

AI is already impacting entry-level and task-based roles, leaving the question of what will happen to the future talent pipeline of IT leadership.

“Our research suggests that organizations create a gap in their future leadership pipeline if they continue reducing entry-level hiring without rethinking how early-career talent develops,” says Autumn Krauss, chief scientist for Future of Work Research Lab at SAP SuccessFactors. “Historically, people built business acumen, technical expertise, and leadership skills through the first few years of their careers. As AI becomes embedded in workflows, organizations need to be intentional about creating new ways for employees to build those skills.”

Companies have traditionally followed hierarchal processes that encourage employees to advance up the career ladder via promotions, with many taking a leadership path to IT director, CIO, or CTO. However, this process has always relied on workers starting with entry-level and routine work to create a natural first step for future leaders. But now, more companies are automating the work that entry-level and mid-level employees used to cut their teeth on, says Maruf Ahmed, CEO of IT staffing and consulting company Dexian.

For example, a junior engineer might start in QA and testing on the technical side, getting hands-on experience with how systems work. As they progress in their career, that knowledge continues to stack, creating future leaders who deeply understand the technology and the business.

“Maintaining a strong succession path starts with being honest about what AI removed from someone’s development, and then being intentional about replacing it,” says Ahmed. “Senior leaders need to spend more time actively teaching, and people need exposure to complex decisions earlier in their careers. Day-to-day work used to build that foundation on its own, and it doesn’t anymore.”

Redesigning jobs for AI and leading in uncertainty

As many have discovered, it’s not always easy to decipher quality AI outputs, especially as the technology has become renowned for hallucinating results. Current and future IT leaders need the foundational knowledge to have confidence when evaluating AI outputs, especially if they’re expecting employees to use AI. The most valuable leaders are the ones comfortable making decisions with incomplete information, and who can make calls on the spot about automated processes, no matter what may arise.

“We often see AI doesn’t stay contained in one function for long,” Ahmed adds. “Once an organization automates in one area, there’s an expectation to extend that more broadly, and leaders who built their careers inside a specific function are suddenly being asked to weigh in on AI use in areas they’ve never directly managed.”

According to recent research from Deloitte, 84% of companies haven’t done the work to redesign jobs around AI despite high expectations for automation, and 36% expect at least 10% of their jobs to be fully automated within a year, and 82% say within three years. Even with those results, fewer than half are making significant adjustments to talent strategies, with 53% saying they’re simply focusing on educating employees to raise AI fluency.

That leaves entry-level workers and those in task-aligned roles in somewhat unknown territory as automation replaces time-consuming tasks, and managers shift to overseeing human-AI teams. Deloitte points to a potential shift toward flatter structures, with more than half of businesses considering pod-based or non-hierarchal models, while 16% have already started to make a shift.

IT leaders will likely find themselves relying more on others in the company to make judgment calls around AI, opening communication and transparency as job roles evolve and structures begin to flatten. With AI adoption happening at a rapid pace, organizations need to evaluate how it’ll impact talent and leadership structures, and what the future of leadership will look like with automation.

Investing in early talent to maintain a leadership pathway

IT leaders need to avoid the trap of treating AI adoption as a technology rollout rather than a workforce development project, says Ahmed. Leaders will continue to invest heavily in new tools, services, hardware, and technology, and then expect employees to become self-taught on these platforms in their downtime.

“Our research found that leaders don’t often feel confident or equipped with the skills to lead that level of transformation. Instead, organizations often fall back on the tactic of giving employees AI tools and expecting them to figure out how best to use them on their own,” says Krauss.

If current IT leaders feel unequipped to lead through AI transformation, it’s imperative companies step back and reevaluate training and future leadership talent pools. Investments in AI should be weighed alongside the necessary investments for employee upskilling and training, and to redefine long-standing organizational structures.

Investment in early talent development programs can also be beneficial for tackling potential future leadership gaps left by AI adoption, with 86% of employees saying that an early talent program helped set them up for career success, according to the SAP report. But despite the beneficial nature of such programs, only 32% of early talent report participating in an early talent program, and 49% say their organization doesn’t offer one. Plus, only 35% of early talent employees say they’ve been given sufficient transparency into which roles in their organization may be automated in the future, while one in three express concerns their job may one day cease to exist due to AI advancements.

“As roles change, organizations need to give employees a clearer picture of where opportunities are emerging and what skills will be most important,” says Krauss. “Many employees are already uncertain about how technology will affect their careers, and that uncertainty can make it harder to stay engaged. People are more likely to invest in their growth when they see a path forward. That visibility is becoming increasingly important.”