AI is radically changing entry-level jobs, but not eliminating them

• Artificial intelligence is having a significant impact on many types of jobs — particularly entry-level positions and especially on roles that benefit from use of automation.
• While AI might not be eliminating a large percentage of early career jobs, as recent headlines have proclaimed, it certainly is changing them in a big way.
• People working in entry-level marketing jobs are using generative AI to create first drafts of promotional or campaign documents, and early career data analysts are relying on AI to prepare datasets.

The ongoing rise of artificial intelligence is having a significant impact on many types of jobs, particularly entry-level positions and especially on roles that involve lots of automation. And while AI might not be eliminating a large percentage of early career jobs, as recent headlines have proclaimed, it certainly is changing them in a big way.

“AI is reshaping entry-level roles by automating routine, manual tasks,” said Fawad Bajwa, global AI, data, and analytics practice leader at executive search and leadership advisory firm Russell Reynolds Associates. “Instead of drafting emails, cleaning basic data, or coordinating meeting schedules, early-career professionals have begun curating AI-enabled outputs and applying judgment.”

For example, people working in entry-level marketing jobs are using generative AI to create first drafts of promotional or campaign documents, and early career data analysts are relying on AI to prepare datasets, Bajwa said.

“AI is reshaping all jobs,” said Zanele Munyikwa, an economist at labor analytics firm Revelio Labs. He pointed out that hiring for entry-level jobs is down in general, regardless of AI exposure. “AI-exposed entry-level jobs are seeing bigger drops in demand, but the difference to non-exposed jobs is small,” he said.

Evaluating employee role AI exposure

What AI is doing is forcing an “occupational transformation” among entry-level roles, Munyikwa said. For example, the firm's research has shown that tasks performed by junior-level professionals are shifting toward less AI-exposed functions.

The most AI-exposed jobs tend to be technical, such as data engineers, database administrators, IT specialists, and cybersecurity personnel, as well as financial workers such as auditors, Munyikwa said. And in an interesting twist, the most exposed jobs are also adopting AI the most, making them more productive, he said.

In some of these occupations, up to 30% of workers are already using AI to perform their day-to-day tasks, according to Revelio Labs' research, and for those who use these tools, the productivity gains can be significant.

“Increases in productivity may eventually lead to fewer headcounts in certain job families, but also create jobs elsewhere,” Munyikwa said. “While AI may currently have some productivity boosting capabilities, it needs to be applied and used consistently across large parts of the organization to take effect.”

That requires investments in AI tool training and thoughtful restructuring of job requirements and capabilities, Munyikwa said. “This will take a lot of time and careful leadership to even partially achieve big cost savings,” he said.

Jobs with low AI exposure frequently involve tasks that are difficult to automate, the Revelio Labs' research noted. These positions include manual jobs in manufacturing, hospitality roles, or interpersonal work, which still require a steady pipeline of human workers. Compared with 2010, demand for these roles has grown more quickly than for high-exposure roles, the research said.

Repetitive jobs are going, but not overnight

To be sure, AI is already eliminating some entry-level functions in companies. “Generally, jobs that are repetitive, rule-based, and easily codified are most at risk,” Bajwa said. Many are not disappearing overnight but rather are being fundamentally transformed and restructured to involve more oversight and less manual work, he said.

Although it is highly unlikely that there would be a significant impact on entry-level jobs in the short term, Bajwa said, “organizations must redesign how early talent is onboarded, developed, and integrated in order to navigate the decade ahead,” he said. “Without foundational tasks, it's harder for people to build experience, leading to a fundamental gap in terms of how new professionals will build judgment, confidence and fluency.”

In fact, 54% of the 3,000 executives from Russell Reynolds' global network that the company surveyed are concerned that AI reliance is eroding critical thinking, and one-quarter are worried about AI inadvertently undermining product/service quality and critical internal process quality.

A growing number of leaders across industries are also concerned about AI-driven layoffs, according to the RRA research. Last year 20% said they were concerned, compared with 40%in the latest survey.

CIOs and other technology leaders need to be prepared for the impact of AI on current and future entry-level jobs within their departments, especially considering how aggressively many are launching AI initiatives.

“It changes both talent strategy and team design,” Bajwa said. “Tech leaders must now rethink how they develop junior talent and build future pipelines. The goal isn't just efficiency; it's ensuring AI-augmented teams can still grow, learn and lead,” he said.

With the possible reduction in some entry-level technology positions, there is a potential for more top-heavy team structures, Muniykwa said. “Tech leaders need to redesign workflows and roles as they implement AI,” he said.

Businesses will need new “on-ramps”, for example, apprenticeships and AI-assisted boot camps, so early-career talent can still learn and advance even as some traditional entry-level tasks disappear, Munyikwa said. “Leaders must plan for continuous upskilling, not one-off training sessions, to keep teams productive alongside rapidly evolving AI tools,” he said.