That's a key point in Gartner's analysis of workplace trends for 2024 and beyond: the "collapse of traditional career paths." Linear career progression is giving way to trajectories that are more hybrid, discontinuous, and constantly evolving.

In practice, employees now move more freely between roles, combine varied skill sets, and adjust their path in step with how AI keeps changing the work itself.

For HR leaders, the challenge is no longer just anticipating tomorrow's job titles — it's understanding and supporting these new professional trajectories.

AI Is Reshaping Career Paths More Than It's Eliminating Jobs

Career Paths Are Becoming Less Linear

Recent work on the future of work — Gartner's among it — is shifting the conversation: the real issue isn't jobs disappearing, but career paths transforming. Where careers once followed a fairly linear progression — climbing in expertise, moving up the hierarchy, specializing — they're now becoming more fluid, more cross-functional, and less predictable.

Career paths are steadily drifting away from "pre-mapped" models, largely because of technological change.

Work Is Being Recomposed at the Task Level

This shift comes down to how AI actually integrates into work. Rather than a simple replacement story, AI mainly acts as a lever that recomposes tasks: within a single job, some repetitive or standardized activities get automated, while others shift toward more analysis, coordination, or decision-making.

That's the level at which to understand what's happening: it isn't jobs disappearing, it's tasks evolving, getting redistributed, and recombining in new ways.

Concretely, this shows up as a change in what a role actually involves:

some tasks become marginal;
others get accelerated by AI;
new responsibilities emerge, particularly around overseeing, controlling, and operating the tools themselves.

Career Paths Are Becoming More Differentiated Between Individuals

This dynamic creates gaps even within the same job. Two people in similar roles can see their responsibilities evolve very differently, depending on how well they adopt AI tools and grow their skills.

Career paths are no longer shaped only by experience or seniority — they're also shaped by how well someone adapts to technological change. This introduces a form of individualization: each person increasingly builds their own place based on the skills they develop.

Employees themselves have mixed feelings about all this. A recent Eurobarometer survey found that 62% of Europeans hold a positive view of AI at work, and 70% believe it improves productivity — while still voicing concerns about how their skills, workload, and job security will be affected. The nature of work itself is shifting: AI automates a share of production or predictive tasks, while value moves toward interpretation, judgment, and interaction.

The Rise of Hybrid, Evolving Career Paths

It's in this context that more hybrid career paths are emerging. Professional journeys increasingly take shape through successive adjustments, at the intersection of several skill sets:

A developer might move into data-related or MLOps functions.
A marketing professional might pick up analytical and technical skills.
Support functions increasingly take on more tool oversight and coordination.

In other words, career paths are no longer built solely through job changes — they're built through the gradual transformation of a role and the skills it draws on. That's exactly what makes them harder to anticipate — and more strategic for organizations to support.

The Shift Toward a Skills-Based Economy

Career Paths Are Less and Less Structured Around Job Titles

If career paths are being reshaped, it's because the central reference point is changing. It's no longer just jobs that structure a career — it's skills.

For a long time, careers were built around fairly stable job titles. An employee moved through one role, then another, following a logic of progression, specialization, or increased responsibility. AI is disrupting that approach by breaking jobs down into blocks of skills that can be deployed across different contexts.

In other words, what's changing today isn't only the roles themselves, but the combination of skills needed to perform them.

Which Skills Are Gaining Value in the Age of AI?

Three broad dynamics are emerging:

First, some skills are being augmented by AI — tool proficiency, data analysis, automation, and the ability to make good use of what AI systems produce.

Others are becoming complementary to AI. The more tools automate certain tasks, the more value shifts toward interpretation, judgment, decision-making, creativity, and collaboration.

Finally, some skills are becoming more vulnerable — mainly those tied to repetitive, standardized, or easily modelled tasks, which tools can absorb more quickly.

According to McKinsey Global Institute analysis, by 2030, roughly 27% of hours worked in Europe and 30% in the United States could be automated as a result of generative AI. That figure doesn't mean 30% of jobs will disappear — it mainly shows that the transformation plays out at the level of tasks and daily activities, and therefore at the level of the skills being used.

Mobility Is Opening Up — and Getting Harder to Read

This shift is opening new mobility paths. The same core set of skills can now be valued across several different roles, while a given role might require very different skill combinations depending on how exposed it is to AI.

Career paths are becoming more open, but also harder to read. For employees, it's less obvious what a "natural" progression looks like. For organizations, it's harder to plan around job descriptions alone.

Recent OECD research points to why a skills-first approach is becoming essential: as much as 40% of workers may need to significantly adjust their skill set to stay employable by 2030, driven by technological change, AI included.

The question is no longer just what tomorrow's job will look like, but which skills will let someone move from one role to another. Career paths increasingly resemble evolving assemblages — built out of transfers, hybridizations, and bridges between roles.

A Strategic Challenge for HR: Anticipating and Structuring Career Paths

Moving from Managing Positions to Managing Skills

Faced with these shifts, the role of HR is changing at its core. It's no longer just about managing headcount or filling open positions — it's about understanding and structuring increasingly fluid career paths.

Talent management is progressively becoming a more precise discipline: managing the skills portfolio present within the organization.

Mapping Skills to Make Career Paths More Legible

In this context, skills mapping becomes a central lever. This exercise is highly useful for:

identifying gaps;
spotting potential;
and building more coherent mobility paths.

It also helps move away from reactive management. Instead of waiting for a role to change or a hiring difficulty to surface, an organization can identify ahead of time:

transferable skills;
upskilling needs;
and possible career transitions.

In other words, skills mapping isn't just about hiring better. It's also about guiding people better, training them better, and making their career paths more secure.

Supporting Transitions Instead of Just Reacting to Them

The other major challenge is upskilling and requalification. Adapting to AI can't rest on individuals alone. It calls for structured programs — training, coaching, and internal mobility — capable of keeping pace with the speed of change.

A survey from France's LaborIA program, run jointly by the Ministry of Labour and Inria, found that a large majority of professionals already using AI systems say these tools are changing their tasks, skills, and day-to-day know-how.

For HR, the challenge is to organize clearer, more secure transitions starting now. That means: