When the career ladder breaks: Rethinking growth and performance in the AI era

The rules of career progression are being rewritten in real time. As AI takes over tasks once reserved for humans at every level, organizations face fundamental questions about what job levels mean, how to measure growth, and whether traditional performance metrics still make sense.

In a recent Lepaya webinar, Dr. Dieter Veldsman, Chief HR Scientist at the Academy to Innovate HR, Daria Rudnik, Team Architect at aidra.ai, and Milda Bayer, VP Marketing & GTM at Lepaya, explored how companies must rethink everything from entry-level pathways to performance evaluations. Here's what emerged from their conversation.

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The vanishing entry point

The most immediate disruption is happening at the bottom of the career ladder. Recent data indicate a significant decline: postings for entry-level jobs in the United States have decreased by approximately 35% since January 2023. 

The reason? AI is now capable of handling much of the foundational work that once served as a training ground for young talent.

"Companies tend to hire more experienced people because those people know processes, they know what a good process should look like, and they know where AI can bring value," Daria explained. "While junior people are not familiar with the process yet. They can use AI, but they cannot optimize the process with the help of AI."

However, this creates a troubling paradox for talent development. Organizations need experienced workers who understand quality and can direct AI effectively. But without entry-level positions, how do people gain that experience in the first place?

"With AI being able to do what juniors can do, what does it mean for organizations?" Daria posed.

"Does it mean that you don't need juniors anymore? Or does it mean that any junior developer can fast-track to middle developer because they can learn faster with the help of AI?"

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The answer likely varies by function. What works for developers may differ dramatically from what works for marketers, HR professionals, or financial analysts. But the urgency of solving this puzzle is undeniable - organizations that can't develop their own talent pipelines will find themselves competing fiercely for an ever-shrinking pool of experienced workers.

Middle management's moment of truth

While junior roles are shrinking, middle management faces an even more existential challenge. Research from Harvard Business Review studying GitHub Copilot's impact revealed a surprising finding: while developers could accomplish more work with AI assistance, managers actually had less work to do.

"The traditional command-control-delegate cycle didn't work because AI could take those tasks," Daria shared. "All this admin stuff that line managers or middle managers usually do, which takes most of their time, is now redundant."

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Nowadays, AI can excel at repetitive, predictable tasks, pattern identification, and consolidating large information sets. For middle managers, this means:

• Automated reporting and budget tracking
• Task monitoring and progress updates
• Routine administrative coordination

This automation leaves middle managers at a crossroads. The time freed from administrative burden creates an opportunity for them to focus on what truly matters: strategy, collaboration, and developing people and teams. But at the same time, it also exposes those whose primary value was tied to oversight and control.

To overcome this shift, Dieter emphasized that organizations need to rethink what management fundamentally means:

"I think AI can play a critical role in helping us redefine what a manager really is, because we've blended managing people, managing work, and managing tasks and activities, when these should be distinct."

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As AI handles the bureaucratic load, managers who embrace development, coaching, and strategic thinking will become more valuable, not less. But organizations must actively redesign these roles rather than waiting for them to organically evolve.

Career frameworks for an AI-driven world

Traditional career progression assumed a vertical ladder: start at the bottom, work your way up through defined levels, and eventually reach leadership. But with both entry-level and middle management roles undergoing radical changes, frameworks built on hierarchical progression no longer hold. 

"I think the traditional career ladder still exists," Dieter explained. "But it's not the only way to think about career progression. We think a lot more about what we call a career lattice, which is more of a 360-based approach."

This lattice model acknowledges multiple dimensions of growth:

• Vertical: Traditional promotions up the hierarchy
• Horizontal: Moving across functions or departments
• Diagonal: Stretching into adjacent areas that leverage transferable skills

But implementing this requires solving a dual challenge: Organizations often don't clearly define the skills they need, while employees frequently can't articulate the transferable value they possess. 

Dieter noticed this gap in conversations with HR professionals: "I ask them, what is your core skill? They'll say recruitment. I'm saying no, that's not your durable skill, that's your functional skill. Durable skills are things like critical thinking and planning - those you can apply in various different areas."

This distinction matters because AI works horizontally, not vertically. 

"If you understand what your durable skill is and what you can transfer to another domain, all of a sudden the traditional career path is just one of the options available," Dieter noted.

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For career lattices to work in practice, organizations need:

1. Skills-based work design: Define roles by tasks, activities, and required skills rather than rigid job descriptions
2. AI-powered matching: Use technology platforms to connect people's existing skills with opportunities across the organization
3. Cultural shift: Help employees redefine career success beyond vertical progression, whether that means meaning, balance, wealth, or status

"AI can create platforms for learning and identifying where skills are needed," Daria added. "That will help you grow in your career, whether it's vertical, horizontal, or whatever direction makes sense."

Performance reviews: From activity to impact

When AI can complete tasks faster than humans, traditional performance metrics face a crisis. If output no longer correlates with effort, how do organizations evaluate contribution?

The problem runs deeper than choosing better metrics. Annual reviews assume work stays relatively stable, but that assumption no longer holds. Goals set in January may be obsolete by April. Projects morph mid-stream. Priorities shift weekly.

"I don't believe in a traditional performance management approach where you sit with the employee and tick boxes about goals when the world has shifted three times since the previous evaluation," Daria explained, reflecting on why she abandoned annual reviews years ago.

This volatility demands a rethink of how organizations evaluate and develop talent:

• Shift from backward to forward: Replace annual assessments with regular developmental conversations focused on future capabilities, not past activities
• Measure value, not volume: Focus on tangible impact delivered rather than tasks completed or hours worked
• Emphasize collective impact over individual tasks: Team outcomes often reveal more about value creation than isolated metrics

"I'm a big supporter of splitting out performance and development into separate conversations," Dieter noted.

"Have a performance process that fits with your culture, but make it dialogue-driven, not a checklist or checkbox exercise."

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AI can help by consolidating data and surfacing insights for better conversations. But the quality of performance management ultimately depends on managers developing the human skills to coach, give feedback, and have meaningful dialogues about value and growth - capabilities that no algorithm can replace.

Designing for what comes next

As AI reshapes work at every level, organizations face a choice: cling to legacy frameworks that no longer serve them, or embrace the complexity of redesigning career and performance systems from the ground up.

The companies that will thrive are those that:

1. Reinvent entry-level development through meaningful apprenticeships rather than task-based roles
2. Redefine management as enablement and coaching rather than oversight and control
3. Reimagine careers as lattices of skills and opportunities rather than vertical ladders
4. Refocus performance on value creation and team outcomes rather than individual activity metrics

The career ladder isn't just getting shorter; it's being replaced by something more complex and fluid. And for both organizations and individuals, learning to navigate this new landscape may be the most critical skill of all.

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