The claim that AI will eliminate entry-level jobs spreads quickly. But the first question HR should examine is slightly different. It is less about which jobs disappear and more about how the tasks once handled by entry-level employees are being broken apart and recombined.
A survey summary released by Cognizant and Pearson on June 18 shows this distinction clearly. It said that in India, 37% of entry-level role tasks are already performed by AI, while the global average is 33%. At the same time, 94% of HR leaders said AI will create new entry-level roles within the next five years. Replacement and creation appear in the same table.
The entry-level jobs debate should start with task composition, not replacement rates
The most striking figure in the survey summary is 37%. That is the share of entry-level job tasks in India that AI already performs. It is higher than the global average of 33%. In addition, 18% of HR leaders said AI is handling more than half of entry-level work. Looking only at the numbers, anxiety can come first.
But if HR reads these figures immediately as “reduced entry-level hiring,” its judgment becomes too blunt. Even when some tasks move to AI, the whole job does not necessarily disappear. Recruiters should instead separate the repeated data entry, drafting, information search, verification, customer response, and internal coordination tasks inside job descriptions. Some tasks will be automated, while others will require more human judgment.
Hiring criteria are moving from majors to the ability to work with AI
In the Cognizant and Pearson survey, 96% of HR leaders expected entry-level roles to evolve toward supervising or managing AI systems within five years. Another 94% said AI will create new entry-level roles that do not exist today. This point means the focus of hiring criteria is moving from “Can this person use AI?” to “Can this person review AI output and adapt it to the context?”
What is interesting is that the summary does not emphasize technical majors alone. It reported that 97% of HR professionals said soft skills have become more important, and 69% said a broad interdisciplinary background is more important for early-career talent than narrow specialization. If Korean companies revisit their entry-level hiring scorecards, they should look beyond major names, certificates, and tool experience. Problem definition, AI-output verification, and the ability to explain work collaboratively should be evaluated together.
Training demand is rising, but L&D is falling behind the pace
According to the survey summary, 91% of HR professionals said demand for AI training among employees increased over the past 12 months. Yet 60% said L&D programs are not keeping up with the pace of AI-driven job change, and the figure was presented as 63% among respondents in India. The gap between training demand and training supply has already become an operating issue.
At this point, HRD needs to create task maps by job before adding one-off AI lectures. For example, in entry-level sales, marketing, development support, and HR operations roles, HRD should separate the drafting, search, and classification tasks handled by AI from the judgment tasks people must confirm. Training indicators also cannot stop at the number of participants. Actual task-transition rates after training, manager feedback, error-review standards, and changes in onboarding time should be checked together.
Middle managers become the bottleneck in AI hiring and onboarding
In the Cognizant and Pearson survey, 95% of HR leaders said middle managers are important in ensuring employees use AI effectively. Another 92% said middle managers play an important role in redefining job roles as AI changes daily work. Even if a company hires entry-level employees, change will stop at the wording of the job posting if frontline managers cannot redistribute work between AI and people.
HR’s next diagnostic questions therefore need to be concrete. First, has the organization written down the tasks AI has taken over and the new verification tasks for each entry-level role? Second, does onboarding teach judgment standards and prohibited uses, not only how to use AI tools? Third, have middle managers been given role-redesign authority and coaching language? Fourth, for companies that maintain large-scale early-career hiring, as in Cognizant’s case of hiring 20,000 entry-level employees in 2025 and planning to exceed that number in 2026, are education, placement, and managers’ execution capabilities expanding together?
The same percentages cannot be applied directly to Korean companies. The survey covered three countries—the United States, the United Kingdom, and India—and surveyed 750 director-level or higher HR professionals at companies with more than 1,000 employees. The sample and respondent composition were collected through an online survey from March 23 to April 3, 2026. Still, the message is clear. The core question in entry-level hiring in the AI era is not “How many people can we reduce?” but “Which tasks must we redesign, and which skills must we build early?” If HR misses this question, AI becomes not the answer to workforce planning but another cause of onboarding failure.
