Featuring scholarly and practitioner insights from HR and people leaders, industry experts, and researchers.

The landscape for entry-level jobs has drastically changed since 2022, with a significant decrease in opportunities, particularly in sectors such as technology, finance, and professional services. This shift stems from structural changes amplified by two key trends: remote work and generative AI. Remote work eliminates the informal, onsite mentoring and learning that previously helped juniors grow, while AI automates routine tasks that once served as stepping stones for beginners. Consequently, companies increasingly prefer hiring experienced workers over newcomers, creating a paradox where young professionals need experience to get hired but can't gain experience without a job. Highlights 🔍 Entry-level jobs dropped 8 to 11 percentage points since before the pandemic in key global markets. 💻 Technology, finance, and professional services are the hardest-hit sectors for junior roles. 🔄 Remote work and generative AI together disrupt informal learning and automate routine tasks, reducing entry points for juniors. 🚧 The "experience paradox": you need experience to get a job, but can't get experience without being hired. 🤝 Hybrid work models and structured onboarding can mitigate challenges in training new hires remotely. 💡 Companies like IBM, Google, and Bloomberg innovate by dropping degree requirements, offering apprenticeships, and augmenting juniors with AI. 📈 Investing in junior talent is essential for long-term innovation, leadership, and business success. Key Insights 💼 Structural Decline in Entry-Level Jobs: Data from multiple countries (US, UK, Canada, Australia) signal that the drop in entry-level jobs is a lasting structural shift instead of a temporary post-pandemic blip. Sectors traditionally serving as launchpads for careers—technology, finance, and professional services—are particularly affected, which threatens the future talent pipeline. This suggests that companies must rethink how they cultivate their next generation of leaders and innovators. 🔄 Remote Work Removes Informal Learning Opportunities: Remote work hinders the informal learning process where junior employees gain knowledge by observation and spontaneous interactions at the workplace—often referred to as "learning by osmosis." This loss increases companies’ costs and complexity for effectively onboarding and training new hires, which consequently discourages them from hiring juniors. 🤖 AI Automates Entry-Level Tasks, Shrinking Junior Roles: Generative AI tools like ChatGPT automate routine and repetitive tasks that previously helped entry-level employees prove their value and build experience. As a result, companies question the need for as many junior roles, especially those centered on tasks now efficiently handled by AI. This dual force of AI and remote work compounds the scarcity of entry jobs, creating a "Remote Work AI Paradox." 🧩 Hybrid Approaches Foster Junior Development: Successful organizations blend structured onboarding, remote work, AI augmentation, and periodic in-person interactions to support junior hires. For example, Microsoft schedules collaboration hours, HSBC redesigns offices for mentorship, and firms like Boston Consulting Group use AI to handle low-level tasks so juniors can focus on skill development. These hybrid models increase engagement, productivity, and learning outcomes despite the remote work environment. 📉 Long-Term Costs of Skipping Junior Hires: Cutting back on hiring new graduates may reduce immediate costs but incurs long-term risks including talent pipeline erosion, innovation stagnation, and loss of future leaders. Economically, young workers who lack early career opportunities experience "scarring effects," characterized by lower lifetime earnings, delayed career progression, and greater debt burdens from pursuing additional education to compensate for missed experience. 🎓 Alternative Pathways to Build Early Career Skills: Companies adopting new methods—such as dropping degree requirements (IBM), offering paid apprenticeships combining on-the-job tasks with formal learning (Google, EY), and training juniors to collaborate with AI (Bloomberg)—demonstrate promising alternatives. These models prioritize skills over credentials and proactively support juniors in gaining relevant experience in a changing work environment, enhancing equity and inclusion. 🔄 Adaptability and Continuous Learning Are Essential for Juniors: For young professionals navigating this disrupted entry-level market, success depends not only on securing jobs but on continuously updating skills and embracing reskilling opportunities. Transparency in career progression pathways and employer support, as seen at companies like Shopify and Seammens, help juniors remain competitive and leverage AI tools to accelerate their development. This dynamic underscores the growing importance of lifelong learning in the modern workforce.

This research investigates the sharp decline in hiring for entry-level positions since 2022, a trend that threatens long-term career growth and organizational health. The analysis evaluates two primary causes: the rise of generative AI automating junior tasks and the challenges of remote work in providing necessary mentorship and supervision. While some recent research suggests that virtual work environments are the leading driver of this shift, this text argues that both forces likely work together in complex ways. To address these challenges, the research suggests that companies should adopt intentional onboarding, use AI to enhance rather than replace junior staff, and create structured hybrid models. Ultimately, the research emphasizes that managerial choices and organizational adaptation are more important than technological trends in determining the future of early-career employment.

Abstract: Recent evidence shows significant declines in early-career hiring across advanced economies since 2022, prompting urgent questions about workforce development and productivity. While emerging research attempts to isolate generative AI as the primary driver, the relationship between technological change, organizational structure, and junior talent acquisition remains poorly understood. This analysis critically examines a recent working paper by Lambert and Schindler (2026) that challenges AI-centric narratives by highlighting remote work as a competing explanation. Drawing on labor economics and organizational behavior research, we argue that univariate explanations oversimplify a multifaceted phenomenon involving measurement challenges, correlated exposures, and context-dependent mechanisms. The evidence suggests both forces likely operate simultaneously through distinct channels—AI through task automation and skill polarization, remote work through supervision costs and learning friction—with their relative importance varying by occupation, firm capability, and implementation approach. Practitioners and policymakers require more nuanced frameworks that acknowledge uncertainty, emphasize organizational adaptation, and avoid premature dismissal of either explanation. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This research investigates the sharp decline in hiring for entry-level positions since 2022, a trend that threatens long-term career growth and organizational health. The analysis evaluates two primary causes: the rise of generative AI automating junior tasks and the challenges of remote work in providing necessary mentorship and supervision. While some recent research suggests that virtual work environments are the leading driver of this shift, this text argues that both forces likely work together in complex ways. To address these challenges, the research suggests that companies should adopt intentional onboarding, use AI to enhance rather than replace junior staff, and create structured hybrid models. Ultimately, the research emphasizes that managerial choices and organizational adaptation are more important than technological trends in determining the future of early-career employment. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This research investigates the sharp decline in hiring for entry-level positions since 2022, a trend that threatens long-term career growth and organizational health. The analysis evaluates two primary causes: the rise of generative AI automating junior tasks and the challenges of remote work in providing necessary mentorship and supervision. While some recent research suggests that virtual work environments are the leading driver of this shift, this text argues that both forces likely work together in complex ways. To address these challenges, the research suggests that companies should adopt intentional onboarding, use AI to enhance rather than replace junior staff, and create structured hybrid models. Ultimately, the research emphasizes that managerial choices and organizational adaptation are more important than technological trends in determining the future of early-career employment. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This research investigates the sharp decline in hiring for entry-level positions since 2022, a trend that threatens long-term career growth and organizational health. The analysis evaluates two primary causes: the rise of generative AI automating junior tasks and the challenges of remote work in providing necessary mentorship and supervision. While some recent research suggests that virtual work environments are the leading driver of this shift, this text argues that both forces likely work together in complex ways. To address these challenges, the research suggests that companies should adopt intentional onboarding, use AI to enhance rather than replace junior staff, and create structured hybrid models. Ultimately, the research emphasizes that managerial choices and organizational adaptation are more important than technological trends in determining the future of early-career employment. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this HCI Webinar, I talk with Dr. Meghan Grace about generational differences in the workforce and how leaders can better understand and balance the different needs and interests of their workers. Dr. Meghan Grace is a leading generational expert whose research on Generation Z spans the last decade and has helped companies, universities, and associations understand generations to work better together. In speaking with groups around the world, Meghan prioritizes understanding the human experience while providing data-informed insights about generations. Guided by multiple studies, Dr. Grace helps connect the dots between getting to know a generation and knowing what makes them tick. She is the host of the podcast, #GenZ and has co-authored three books on Generation Z with a new book on generations in the workplace coming later this year. When she isn’t researching, speaking, writing, or podcasting about generations, she co-leads the Institute for Generational Research and Education.

This research reinterprets Don Miguel Ruiz’s classic principles to address the psychological and ethical challenges posed by artificial intelligence. The research argues that excessive cognitive offloading and uncritical reliance on algorithms can lead to unconscious engagement, which threatens human judgment, creativity, and neurological health. By applying reimagined versions of the Four Agreements, individuals and organizations can maintain metacognitive awareness and ensure that technology serves as a partner rather than a replacement for human thought. Furthermore, the research introduces a fifth practice focused on embodied presence, urging users to stay connected to physical sensations and intuition to counter digital dissociation. Ultimately, the research highlights that human sovereignty and wisdom are essential for navigating an increasingly automated world while avoiding automation bias and skill atrophy. Through evidence-based frameworks, the research demonstrates how cultivating conscious interaction preserves the unique human capacities that AI cannot replicate.