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

In this HCI Webinar, I talk with Luis Garcia about personalized adaptive workplace learning and assessment. Luis Garcia is a seasoned international executive with over 25 years of experience in technology, digital media, and education. He specializes in driving new ventures and products to rapid growth by building effective teams that harness innovation, technology, and creativity to solve complex problems. He is the president of PETE, an Orlando-based tech startup that offers a suite of cost-effective and customizable solutions that enable organizations to deliver personalized workforce learning at scale. The PETE team is dedicated to harnessing the power of AI to help organizations of all sizes optimize their training initiatives, spanning from onboarding to regulatory compliance, product knowledge, technical skills, and more, without hiring additional training resources.

Since late 2022, entry-level job opportunities in key sectors such as technology, finance, and marketing have declined sharply in countries like the US, UK, and Canada. The proportion of these roles awarded to early-career professionals has dropped by up to 11 percentage points. This decline is not a temporary downturn but rather a structural shift in hiring practices. Employers are increasingly seeking candidates who can contribute immediately with minimal training, favoring experienced workers over fresh graduates. Highlights 🧑‍💼 Entry-level jobs in tech, finance, and marketing have declined by up to 11 percentage points since late 2022. 🏠 Remote work reduces informal mentorship opportunities, pushing companies to favor experienced hires. 🤖 AI automates traditional entry-level tasks, shrinking roles available for junior employees. 🔄 The interplay of remote work and AI raises the bar for newcomers, requiring immediate productivity and advanced skills. 🚫 Fewer entry-level jobs limit young workers’ experience and growth, with negative long-term effects on talent pipelines. 💸 Poaching mid-level talent raises salaries and destabilizes hiring ecosystems, risking future workforce sustainability. 🌟 Companies are adapting with hybrid onboarding, AI-assisted roles, flexible degree requirements, and apprenticeships. Key Insights 🧠 Structural hiring shift fueled by AI and remote work: The trend away from entry-level hiring is not temporary but an enduring change. Organizations now demand new hires capable of adding value immediately, largely due to reduced training capacity in remote settings and AI automating routine functions. This recalibration emphasizes readiness and experience over potential, reshaping the labor market entry dynamics. 🤝 Impact of diminished informal learning: Remote work disrupts the informal knowledge transfer that traditionally occurs through spontaneous, in-person interactions. Junior employees depend heavily on mentorship to acquire tacit knowledge and soft skills; without this, their onboarding becomes inefficient, which motivates employers to minimize hiring juniors altogether. 🤖 AI as a labor multiplier and disruptor: Tools like ChatGPT have effectively taken over many tasks once reserved for entry-level roles, such as email drafting, data handling, and basic programming. This efficiency gain means fewer juniors are needed, but it also shifts job descriptions to include more advanced, AI-complementary competencies. 📉 Career bottleneck and talent pipeline risks: As companies increasingly recruit mid-level or senior talent instead of juniors, early-career professionals face a “catch-22” situation: without experience, they cannot move up, and with fewer entry points, they cannot gain experience. This bottleneck undermines the development of future leadership and innovation capacity within firms. 💰 Economic repercussions of talent poaching: The reliance on experienced hires drives competition and salary inflation at mid-levels, which disadvantages recent graduates and startups unable to compete. The result is a talent ecosystem imbalance: short-term gains for some companies, but increased labor costs, inefficiencies, and instability overall. 🌐 Hybrid and redesigned onboarding as a solution: Successful adaptation involves reimagining entry-level recruitment and onboarding through hybrid models that combine remote work benefits with focused in-person mentoring. Structured onboarding programs, comprehensive documentation, and AI-augmented roles maintain productivity while supporting junior staff development. 🚀 Inclusive talent strategies for future resilience: Dropping rigid degree requirements and expanding apprenticeships open new pathways for early-career individuals, fostering diversity and accessibility. Companies that proactively invest in these approaches can create a sustainable talent pipeline, better equipping themselves to navigate the evolving demands of technology-driven workplaces.

This research examines a significant decline in early-career hiring across advanced economies, investigating whether generative AI or remote work is the primary cause. While AI automates entry-level tasks, remote environments create mentorship friction and higher supervision costs that discourage firms from recruiting inexperienced talent. Research suggests these two forces often overlap, making it difficult for analysts to isolate a single culprit for the shrinking opportunities available to new graduates. To combat this "broken ladder," the research advocates for intentional organizational shifts, such as structured virtual onboarding and AI-augmented training programs. Ultimately, the research argues that proactive management choices and redesigned career pathways are essential to preserving long-term workforce development in a changing technological landscape.

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 examines the methodological foundations underpinning claims about AI versus remote work impacts on entry-level employment. Drawing on labor economics, organizational behavior, and technology adoption research, we argue that univariate explanations oversimplify a multifaceted phenomenon involving measurement challenges, correlated exposures, and context-dependent mechanisms. The evidence suggests both forces 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 examines a significant decline in early-career hiring across advanced economies, investigating whether generative AI or remote work is the primary cause. While AI automates entry-level tasks, remote environments create mentorship friction and higher supervision costs that discourage firms from recruiting inexperienced talent. Research suggests these two forces often overlap, making it difficult for analysts to isolate a single culprit for the shrinking opportunities available to new graduates. To combat this "broken ladder," the research advocates for intentional organizational shifts, such as structured virtual onboarding and AI-augmented training programs. Ultimately, the research argues that proactive management choices and redesigned career pathways are essential to preserving long-term workforce development in a changing technological landscape. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This research examines a significant decline in early-career hiring across advanced economies, investigating whether generative AI or remote work is the primary cause. While AI automates entry-level tasks, remote environments create mentorship friction and higher supervision costs that discourage firms from recruiting inexperienced talent. Research suggests these two forces often overlap, making it difficult for analysts to isolate a single culprit for the shrinking opportunities available to new graduates. To combat this "broken ladder," the research advocates for intentional organizational shifts, such as structured virtual onboarding and AI-augmented training programs. Ultimately, the research argues that proactive management choices and redesigned career pathways are essential to preserving long-term workforce development in a changing technological landscape. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This research examines a significant decline in early-career hiring across advanced economies, investigating whether generative AI or remote work is the primary cause. While AI automates entry-level tasks, remote environments create mentorship friction and higher supervision costs that discourage firms from recruiting inexperienced talent. Research suggests these two forces often overlap, making it difficult for analysts to isolate a single culprit for the shrinking opportunities available to new graduates. To combat this "broken ladder," the research advocates for intentional organizational shifts, such as structured virtual onboarding and AI-augmented training programs. Ultimately, the research argues that proactive management choices and redesigned career pathways are essential to preserving long-term workforce development in a changing technological landscape. 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 Tom Ulbrich about the intersection between for-profit and non-profit organizations and leadership. Tom Ulbrich is an entrepreneur, educator, speaker, author, social sector CEO at Goodwill of Western New York, a member of the Forbes Non-Profit Council and Executive in Residence for Entrepreneurship at the University at Buffalo School of Management. He is an entrepreneurial leader with broad-based management experience in both the for-profit and non-profit sectors. His passion for social innovation is focused on nurturing strong relationships and building consensus across diverse groups of stakeholders in the academic, for-profit, non-profit and government sectors.