The continuous rise of artificial intelligence has had a major impact on many types of jobs, particularly entry-level positions, and roles that include many automation in particular. And while AI may not rule out most of its early career jobs, it certainly changes them significantly as recent headlines declare.
“AI is restructuring entry-level roles by automating routines and manual tasks,” said Fawad Bajwa, Global AI, Data and Analytics Practice Leader at Russell Reynolds Associates, an executive search and leadership advisory firm. “Instead of drafting emails, cleaning basic data, or adjusting meeting schedules, early career experts have begun curating AI-enabled outputs and applying judgement.”
For example, people working in entry-level marketing jobs are using generated AI to create the first draft of promotion or campaign documents, while early career data analysts rely on AI to prepare their datasets, Bajwa said.
“AI is restructuring everything's work,” said Zanele Munyikwa, an economist at labor analytics firm Revelio Labs. He noted that employment for entry-level jobs is generally declining, regardless of AI exposure. “While there is a significant drop in demand for entry-level jobs exposed to AI, there is a slight difference between jobs that are not exposed,” he said.
Evaluation of employee role AI exposure
What AI is doing is to force “professional change” between entry-level roles, Munyikwa said. For example, a company's research shows that the tasks performed by junior-level experts are shifting towards less revealing features.
According to Munyikwa, the jobs most exposed to AI tend to be technical jobs, such as data engineers, database administrators, IT specialists, cybersecurity personnel and financial workers such as auditors. And with an interesting twist, he said he also employs the most exposed jobs, making them more productive.
In some of these occupations, a study by Levelio Labs shows that for those using these tools, up to 30% of workers already use AI to perform their daily tasks.
“Increasing productivity could ultimately lead to fewer staffing in certain employed families, but could also create jobs elsewhere,” Munikwa said. “AI may be more productive right now, but to be consistently used across most organizations, it must be applied and used consistently.”
According to Munyikwa, there is a need for investment in AI tools training and thoughtful restructuring of job requirements and capabilities. “This takes a lot of time and careful leadership and even achieves some major cost savings,” he said.
Jobs with less AI exposure often include tasks that are difficult to automate, a Revelio Labs study says. These roles include manufacturing, hospitality roles, or interpersonal relationship manual work, which requires a stable pipeline of human workers. Compared to 2010, the study says the demand for these roles is growing faster than the high-exposed roles.
The repetitive work is ongoing, but not overnight
Certainly, AI has already eliminated some entry-level capabilities in the enterprise. “In general, repetitive, rule-based, easily codified work is at the most risk,” Bajiwa said. Many have not disappeared overnight, but rather have been radically transformed and reconstructed with more surveillance and less manual work, he said.
Although there is little to be a major impact on entry-level jobs in the short term, Bajiwa said: “Without basic tasks, it is difficult for people to build experiences, leading to a fundamental gap in how new professionals build judgment, confidence and flow.”
In fact, 54% of the 3,000 executives in Russell Reynolds' global network, who are concerned that the company surveyed is eroding critical thinking, are worried that AI will mislead the quality of its products/services and the quality of critical internal processes.
More and more leaders across the industry are concerned about AI-driven layoffs, according to a survey by RRA. Last year, 20% said they were concerned, compared to 40% in the latest survey.
CIOs and other technology leaders need to prepare for the impact of AI on current and future entry-level jobs within their department, especially considering how aggressively many people are launching AI initiatives.
“It will change both talent strategy and team design,” Bajiwa said. “Technology leaders must rethink how they develop junior talent and build a pipeline for the future. The goal is not just efficiency. They will enable AI-enabled teams to grow, learn and lead,” he said.
Muniykwa said there could be a more top-heavy team structure as some entry-level technology positions could be reduced. “Technology leaders need to redesign their workflows and roles when implementing AI,” he said.
Businesses need new “on-ramps” such as apprentices and AI-assisted bootcamps, so early career talent can learn and advance even if some traditional entry-level tasks disappear, Munyikwa said. “Leaders must plan on continuous upskills rather than one-off training sessions to keep their teams productive with rapidly evolving AI tools,” he said.
