Executive Summary

Artificial intelligence is transforming the nature of work across industries, but its effects are especially significant at the entry level. As organizations integrate AI into business operations, they are also rethinking how they recruit, develop, and retain early-career talent. These changes extend beyond automation. They influence hiring practices, workplace expectations, skills development, and the relationship between higher education and employment.

The World Economic Forum’s report, Artificial Intelligence and the Future of Entry-Level Work: A Framework for Safeguarding and Reinventing Early Career Pathways, presents a structured framework for understanding these changes. Rather than focusing exclusively on technological capability, the report emphasizes the institutional choices that will determine whether AI expands or restricts opportunities for future graduates.

Part One of the report introduces the broader context of AI-driven workforce transformation and examines the first of four strategic dimensions: Job Access. Together, these findings provide important insights for educators, employers, policy-makers, and students preparing for careers in an increasingly AI-enabled economy.

Why Entry-Level Work Matters in an AI Economy

Entry-level employment has traditionally served as the primary gateway into professional careers. Beyond providing initial employment, these positions allow individuals to gain workplace experience, develop professional judgment, and acquire the practical capabilities required for long-term career progression.

The report notes that more than 500 million young people aged 15 to 24 currently participate in the global labour force. By 2030, more than 600 million additional jobs will be required, primarily in emerging economies, to accommodate new workforce entrants. Against this backdrop, preserving effective entry-level career pathways becomes an economic and societal priority.

Historically, organizations have relied on these positions to cultivate future professionals. Employees entered organizations through structured junior roles, gradually acquired expertise, and progressed through increasingly complex responsibilities. Artificial intelligence is now changing this model.

AI Exposure Is Highest Among Knowledge-Based Occupations

One of the report’s principal findings is that AI exposure is not evenly distributed across the global workforce.

Analysis conducted for the report estimates that 37 percent of young workers worldwide are employed in occupations with medium to high exposure to AI-driven task change. Regional variation is substantial. Eastern Asia records the highest exposure, where approximately 75 percent of young workers occupy AI-exposed roles. Northern America follows at 69 percent, while Europe reaches 63 percent.

The concentration of AI exposure is primarily determined by industry composition.

Knowledge-intensive sectors currently experience the greatest levels of AI-driven transformation, including:

• Financial and Insurance Activities
• Information and Communication
• Professional, Scientific and Technical Activities
• Real Estate
• Education
• Public Administration

By comparison, industries such as Agriculture, Construction, Transportation, and Accommodation and Food Services presently demonstrate lower levels of AI exposure because many of their core activities continue to rely heavily on physical tasks and human interaction.

Importantly, the report does not characterize lower exposure as permanent insulation from technological change. Rather, it illustrates that AI adoption will occur differently across industries depending on the nature of work performed.

AI Is Changing How Organizations Think About Entry-Level Hiring

Much public discussion surrounding AI focuses on job displacement. The World Economic Forum presents a more nuanced assessment.

Recent labour-market research cited in the report indicates that hiring slowdowns have been most pronounced among entry-level positions within occupations that exhibit higher AI exposure. However, the report cautions against attributing these developments exclusively to artificial intelligence.

Evidence demonstrates that declines in entry-level job postings began before the public release of ChatGPT in late 2022. Interviews conducted with business leaders similarly suggest that broader economic conditions, organizational cost management, and hiring uncertainty remain significant contributing factors. AI frequently becomes the most visible explanation, even when multiple forces influence hiring decisions simultaneously.

Consequently, the report argues that current labour-market changes should not be interpreted through a single technological lens. Artificial intelligence represents one element within a broader transformation of organizational strategy.

Entry-Level Opportunities Are Being Redefined Rather Than Eliminated

Despite current hiring pressures, employer expectations regarding AI remain divided.

Several organizations anticipate that AI will reduce demand for routine administrative activities traditionally assigned to junior employees. Others expect AI to expand entry-level hiring by allowing new professionals to contribute earlier to analytical, creative, and collaborative work.

This divergence reflects a broader uncertainty regarding how organizations will redesign work itself.

Rather than predicting widespread elimination of entry-level employment, the report recommends that organizations intentionally preserve structured pathways into the workforce. Specifically, employers are encouraged to incorporate entry-level hiring directly into strategic workforce planning rather than allowing AI adoption alone to determine recruitment decisions.

Maintaining these pathways is presented not simply as a matter of employment policy but as an investment in future organizational capability.

AI May Reinforce Existing Inequalities Without Deliberate Action

A significant contribution of the report lies in its examination of unequal access to AI-enabled opportunities.

The report emphasizes that AI is not introduced into a neutral labour market. Existing disparities in education, digital literacy, socioeconomic background, and workplace exposure influence who is best positioned to benefit from technological change.

Among the issues identified are:

• unequal access to AI tools and training;
• differences in digital confidence across generations;
• financial barriers associated with premium AI platforms;
• varying levels of institutional support for AI adoption.

Without deliberate intervention, these differences risk reinforcing existing inequalities in career access and capability development.

Accordingly, the report encourages organizations and governments to establish support mechanisms that expand access to AI literacy, digital skills, and early-career opportunities across diverse populations.

Education and Employment Can No Longer Operate Independently

The report also highlights a long-standing challenge that predates artificial intelligence.

Employers have consistently identified skills mismatches as one of the principal barriers to recruiting entry-level talent. Many graduates struggle not because they lack academic knowledge, but because they have limited opportunities to demonstrate practical application within professional environments.

Artificial intelligence accelerates this challenge by increasing the pace at which workplace tasks, required skills, and organizational expectations evolve.

As a result, the report calls for stronger collaboration between higher education institutions and employers. Rather than relying solely on traditional academic delivery, education systems are encouraged to expand:

• work-integrated learning;
• employer partnerships;
• project-based education;
• experiential learning;
• alternative pathways into employment.

These approaches allow students to develop workplace capability alongside disciplinary knowledge, strengthening their readiness for increasingly dynamic professional environments.

Preparing Graduates for an AI-Enabled Workforce

A central message emerging from the report is that future competitiveness depends less on technological replacement than on institutional adaptation.

Artificial intelligence will continue reshaping occupations, but the long-term outcomes for graduates will depend largely on how organizations design entry-level work, how educators prepare students, and how policy-makers support labour-market participation.

The report therefore frames AI not simply as a technological challenge but as a workforce development challenge.

Preparing graduates for this environment requires educational models that combine academic knowledge with practical application, expose students to evolving workplace technologies, and cultivate the capacity for continuous learning throughout professional life.

The first section of the World Economic Forum’s framework establishes an important foundation for understanding AI’s impact on early careers.

Artificial intelligence is influencing entry-level employment across multiple dimensions, including industry exposure, hiring practices, workforce planning, and educational alignment. Yet the report deliberately avoids deterministic conclusions. Instead, it argues that the future of entry-level work will be shaped by choices made by employers, educators, governments, and workers themselves.

For higher education institutions, these findings reinforce the growing importance of experiential learning, industry engagement, and curricula that evolve alongside workplace transformation. For students, they underscore the value of developing adaptable capabilities that extend beyond technical proficiency alone.

As AI continues to redefine the world of work, preserving meaningful pathways into employment will remain essential not only for organizational performance but also for economic mobility, workforce resilience, and long-term societal prosperity.