- 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.
Numerous job kinds are being significantly impacted by the continuous development of artificial intelligence, notably entry-level employment and those that require a lot of automation. AI is also significantly altering early career occupations, even though it may not be displacing many of them as recent headlines have stated.
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According to Fawad Bajwa, global practice leader for AI, data, and analytics at executive search and leadership consultancy firm Russell Reynolds Associates, “AI is reshaping entry-level roles by automating routine, manual tasks.” “Instead of drafting emails, cleaning basic data, or coordinating meeting schedules, early-career professionals have begun curating AI-enabled outputs and applying judgment.”
For instance, early career data analysts are depending on AI to prepare datasets, and those in entry-level marketing positions are employing generative AI to produce preliminary versions of promotional or campaign materials, according to Bajwa.
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“AI is reshaping all jobs,” economics researcher Zanele Munyikwa of labor analytics company Revelio Labs stated. He noted that regardless of exposure to AI, recruiting for entry-level positions is generally declining. “AI-exposed entry-level jobs are seeing bigger drops in demand, but the difference to non-exposed jobs is small,” he stated.
Evaluating employee role AI exposure
According to Munyikwa, AI is causing a “occupational transformation” in entry-level positions. According to the firm’s study, junior-level workers are increasingly performing activities that involve less AI exposure.
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According to Munyikwa, technical occupations like data engineers, database administrators, IT specialists, and cybersecurity staff, as well as financial professionals like auditors, are typically the ones with the highest exposure to AI. In an intriguing turn of events, he added, the most exposed jobs are also the ones that are implementing AI the most, increasing their productivity.
According to data by Revelio Labs, up to 30% of workers in several of these occupations currently utilize AI to do their daily duties, and the productivity improvements for those who use these tools can be substantial.
“Increases in productivity may eventually lead to fewer headcounts in certain job families, but also create jobs elsewhere,” added Munyikwa. “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.”
According to Munyikwa, this calls for careful reorganization of job requirements and competencies as well as expenditures in AI tool training. “This will take a lot of time and careful leadership to even partially achieve big cost savings,” he stated.
According to the Revelio Labs’ research, jobs with little exposure to AI often involve tasks that are challenging to automate. These jobs include manual labor in manufacturing, hospitality, or customer service, all of which nevertheless need a consistent supply of human labor. According to the study, the demand for these positions has increased faster than that of high-exposure positions since 2010.
Repetitive jobs are going, but not overnight
Undoubtedly, AI is already displacing certain entry-level positions in businesses. “Generally, jobs that are repetitive, rule-based, and easily codified are most at risk,” Bajwa stated. According to him, many are not going away suddenly but are instead undergoing a fundamental transformation and restructuring that involves less manual labor and more control.
Bajwa stated that “organizations must redesign how early talent is onboarded, developed, and integrated in order to navigate the decade ahead,” despite the fact that there is very little chance that entry-level positions would be significantly impacted in the near future. “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.”
Indeed, out of the 3,000 executives from Russell Reynolds’ global network surveyed by the company, 54% are worried that reliance on AI is destroying critical thinking, and 25% are concerned that AI may unintentionally compromise the quality of essential internal processes and products and services.
According to the RRA research, an increasing number of industry leaders are also worried about layoffs caused by AI. In the most recent survey, 40% of respondents expressed concern, compared to 20% last year.
Given how quickly organizations are starting AI programs, CIOs and other technology leaders must be ready for how AI may affect entry-level positions in their departments both now and in the future.
“It changes both talent strategy and team design,” Bajwa stated. “Tech executives now need to reconsider how they create future pipelines and nurture young talent. Making sure AI-augmented teams can continue to develop, learn, and lead is more important than efficiency, he stated.
More top-heavy team structures could result from the eventual elimination of some entry-level technical jobs, Muniykwa stated. “Tech leaders need to redesign workflows and roles as they implement AI,” he stated.
According to Munyikwa, companies will require new “on-ramps” like AI-assisted boot camps and apprenticeships to ensure that early-career talent can continue to grow and learn even as certain traditional entry-level jobs become obsolete. “Leaders must plan for continuous upskilling, not one-off training sessions, to keep teams productive alongside rapidly evolving AI tools,” he stated.
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