D2L has released new research suggesting generative AI is beginning to reshape entry-level employment in ways that may weaken long-term workforce development pipelines. The report, developed with Morning Consult, found that many HR leaders believe AI automation is reducing foundational learning opportunities traditionally associated with early-career roles.
The findings highlight growing concern that organizations pursuing short-term AI productivity gains could unintentionally create future leadership and skills shortages.
As generative AI becomes embedded across enterprise workflows, companies are increasingly rethinking how entry-level work is structured — and whether some traditional junior responsibilities are still necessary.
A new report from D2L, titled The Future of Work and Learning: GenAI Impact on Entry-Level Work, suggests those shifts are already changing hiring strategies, workforce expectations, and talent development pathways inside U.S. organizations.
The survey, conducted by Morning Consult among 546 HR and talent acquisition decision-makers, found that 30% of respondents say their organizations are shifting toward hiring fewer entry-level employees while relying more heavily on mid-level workers using AI to complete tasks traditionally handled by junior staff.
At the same time, 56% of respondents said generative AI is already reducing the number of foundational tasks delegated to early-career professionals.
The implications extend beyond hiring volume. HR leaders surveyed expressed concern that AI automation may be disrupting the developmental experiences that historically helped employees build expertise, institutional knowledge, and leadership capabilities over time.
“The risk isn’t simply that AI changes aspects of entry-level hiring,” said Sandy Rezendes, Head of Corporate Learning and Development at D2L. “It’s that it may reduce some of the foundational on-the-job learning that people need to grow into experienced subject matter experts and future leaders.”
The report reflects a growing tension emerging across enterprise HR and workforce planning discussions. While AI systems are improving operational efficiency, many organizations are still determining how to preserve experiential learning opportunities for junior workers.
Traditionally, entry-level employees developed problem-solving, communication, and operational expertise through repetitive administrative and analytical tasks. Increasingly, those tasks are being automated by generative AI systems.
According to the survey, 48% of HR leaders say AI is already increasing productivity expectations for entry-level workers even when hiring levels remain unchanged.
That shift could have long-term consequences for workforce pipelines. Among respondents planning to reduce entry-level hiring over the next two years, 56% identified AI automation as the primary driver, ahead of budget constraints and organizational restructuring.
More notably, 58% expressed concern that shrinking entry-level opportunities could contribute to a shortage of qualified senior leaders within five years.
The findings align with broader concerns emerging across enterprise workforce strategy discussions. Companies including Microsoft, Google, and Salesforce have rapidly expanded AI productivity tools aimed at automating routine work across organizations.
However, many HR leaders are now confronting a secondary challenge: if AI absorbs the repetitive work traditionally assigned to junior employees, how will organizations develop future managers, specialists, and executives?
The report suggests many enterprises are not yet prepared to address that transition. According to the survey, 74% of organizations do not currently have active upskilling or employee development programs designed to replace the experiential learning being lost to automation.
That gap could become increasingly significant as AI adoption accelerates.
Research from McKinsey & Company and Gartner has similarly warned that organizations failing to invest in continuous workforce development may struggle to sustain long-term productivity gains from AI transformation.
The D2L findings also point to growing concerns around soft skills deterioration among newer workforce entrants. Survey respondents reported perceived declines in communication skills, interpersonal capabilities, and problem-solving abilities among recent entry-level hires compared with cohorts entering the workforce several years earlier.
Those concerns are reshaping enterprise learning strategies.
The report recommends that organizations invest more heavily in structured learning programs, rotational assignments, AI-enabled simulations, internal apprenticeships, and skills-based hiring models focused on critical thinking and AI literacy.
The changing landscape could also reshape higher education and corporate training ecosystems. Learning management systems, workforce intelligence platforms, and AI-powered training technologies are increasingly being positioned as strategic infrastructure for long-term workforce resilience.
Companies operating in enterprise learning and workforce technology markets are already adapting. Platforms focused on skills analytics, personalized learning, digital credentialing, and AI-assisted training are seeing rising enterprise demand as organizations attempt to balance automation with workforce development.
According to IDC, spending on AI-enabled workforce transformation technologies is expected to rise sharply over the next several years as enterprises modernize learning and employee development systems.
For HR leaders, the D2L report underscores a critical reality of the AI era: workforce transformation is no longer only about adopting new technology — it is increasingly about redesigning how organizations develop human expertise itself.
Market Landscape
The enterprise learning and workforce development sector is rapidly evolving as generative AI reshapes employee workflows and hiring strategies. Organizations are increasingly investing in AI-powered learning platforms, workforce analytics systems, digital credentialing technologies, and personalized training infrastructure.
Major enterprise software vendors including Adobe, SAP, and Workday are expanding investments in AI-driven employee learning and skills intelligence platforms.
Research from Forrester suggests organizations are prioritizing continuous learning ecosystems as AI accelerates changes to workforce capabilities and operational requirements.
Top Insights
- D2L’s latest workforce study found many HR leaders believe generative AI is reducing foundational learning opportunities traditionally associated with entry-level work.
- Thirty percent of surveyed organizations report shifting toward fewer entry-level hires while relying more heavily on mid-level workers augmented by AI technologies.
- Most respondents lack structured upskilling programs capable of replacing experiential learning lost through workplace automation and AI-driven task reduction.
- HR leaders surveyed expressed concern that declining entry-level opportunities could create future leadership shortages and weaken long-term workforce development pipelines.
- Enterprise learning platforms and AI-enabled training systems are becoming increasingly strategic as organizations attempt to balance automation with human capability development
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