AI Is Breaking Career Ladders: How to Redesign Pathways for the Future of Work

Introduction

Artificial intelligence is reshaping how work gets done, but there's a deeper structural shift happening beneath the surface. New research from Brookings Metro and Opportunity@Work reveals that AI is placing career mobility at risk, extending beyond job displacement into how individuals progress across roles. This shift has long-term implications for both workers and organizations, especially for those who are Skilled Through Alternate Routes (STARs) navigating pathways into higher-wage work.

For decades, workforce systems relied on structured pathways that connected entry-level roles to higher-wage opportunities. Entry points provided access, gateway occupations created momentum, and destination roles delivered sustained economic mobility. This structure enabled individuals to build skills over time and demonstrate capability in applied settings.

Today, that structure faces unprecedented pressure. AI reshapes tasks, redefines responsibilities, and compresses the middle layers of experience that once supported advancement. The conversation around the future of work now extends beyond which jobs change and focuses on whether the pathways that connect opportunity remain intact.

The Problem: Career Pathways Are Breaking Down

The most significant challenge centers on mobility rather than job elimination. Gateway roles function as connectors between early experience and long-term career growth. When these roles change in fundamental ways, the structure that supports advancement begins to fragment, particularly for workers who rely on experience-based progression rather than formal credentials.

A computer support specialist role offers a clear example. It has long served as a bridge into higher-level technology careers such as cybersecurity, network administration, and systems engineering. Through troubleshooting and system support, individuals build technical fluency and applied problem-solving skills. As AI assumes routine diagnostics and support, opportunities to develop these capabilities through hands-on experience decline.

Customer service roles reflect a similar shift. These positions build communication, data interaction, and decision-making skills that translate into sales, operations, and analytics. As AI platforms manage more interactions, the depth of human engagement decreases, limiting development of these transferable skills.

Retail supervisors represent another key gateway. These roles build leadership, coordination, and operational oversight capabilities. As AI optimizes scheduling, inventory, and decisions, responsibility narrows, reducing experiential learning for broader leadership roles.

Across these examples, jobs remain, yet pathways weaken.

The Cause: AI Reshapes Gateway Occupations at Scale

The underlying cause of this disruption lies in how AI operates across work. Rather than targeting isolated jobs, AI reshapes clusters of tasks that span multiple roles. Gateway occupations face particularly high exposure because they include repeatable, process-driven activities that AI systems can augment or perform with increasing efficiency.

Recent analysis from BCG Henderson Institute reinforces the scale and urgency of this shift. Over the next two to three years, 50% to 55% of jobs in the United States will be reshaped by AI. Many employees will remain in similar roles while facing fundamentally new expectations for how work gets executed and how output gets produced.

Research shows that 15.6 million workers skilled through alternative routes (STARs) hold experience-based roles with high AI exposure, including nearly 11 million in gateway occupations. Only 51% of transitions from gateway to destination roles avoid high AI exposure, meaning nearly half of traditional advancement pathways now face disruption, disproportionately affecting Rising STARs at a critical stage of progression.

The Solution: Redesign Pathways, Not Just Jobs

Addressing this challenge requires a shift in perspective. The focus must move from preserving individual jobs toward redesigning the pathways that connect them. AI strategy must evolve from tool adoption to system design, where organizations intentionally shape how individuals progress through roles and embed skills-first logic into hiring, advancement, and workforce systems.

The first step involves redefining gateway occupations. Rather than allowing these roles to diminish, organizations can redesign them to include higher-value responsibilities such as AI oversight, interpretation of outputs, exception handling, and decision support. This approach preserves the developmental function of gateway roles while aligning them with emerging work requirements.

The second step centers on aligning education and training with clear pathway progression. Micro-credentials, apprenticeships, and work-integrated learning models establish structured entry points into emerging roles. Skills deliver greater value when tied directly to advancement opportunities.

The third step requires coordination across workforce ecosystems. Employers, educational institutions, and public agencies must align efforts to maintain visible, accessible pathways. Mobility emerges through systems that connect learning, work, and advancement.

The Benefits: Stronger Mobility and Sustainable Talent Pipelines

Rebuilding career pathways generates measurable value across the workforce by restoring clarity to how individuals progress and succeed. Workers gain structured opportunities to build skills in applied contexts, demonstrate capability through real work, and advance with a clearer sense of direction and purpose.

Organizations benefit through the development of more resilient and predictable talent pipelines. Clearly defined pathways create a continuous flow of prepared candidates for higher-level roles, reducing reliance on external hiring and minimizing gaps in critical functions.

This approach improves retention by signaling investment in employee growth while also reducing hiring friction, onboarding time, and overall talent acquisition costs. Over time, it strengthens institutional knowledge and creates a workforce that evolves in alignment with organizational strategy.

AI investments deliver stronger returns within this type of system. Employees develop the capabilities required to operate effectively in AI-enabled environments, allowing organizations to move beyond tool adoption toward sustained performance improvement.

As individuals build skills in oversight, interpretation, and decision-making, technology becomes fully integrated into workflows rather than remaining underutilized. At a broader level, stronger pathways contribute to economic resilience by expanding access to opportunity, supporting inclusive growth, and reinforcing regional talent ecosystems.

The next phase of the AI era will be defined by who builds the most effective systems for human progression. As roles evolve and expectations rise, the real differentiator becomes the ability to move people forward with clarity, consistency, and purpose.

Career pathways now represent strategic infrastructure. They determine how quickly individuals develop capability, how effectively organizations fill critical roles, and how well talent adapts to continuous change. When these pathways remain strong, AI amplifies performance. When they weaken, even the most advanced technologies struggle to translate into sustained value.

This moment places leadership at an inflection point. Executives can focus on short-term efficiency gains, or they can invest in the long-term architecture that connects skills to opportunity through coordinated, skills-first systems change. Organizations that choose the latter will shape the future of work by creating environments where people grow as fast as technology evolves.