AI is speeding up work while quietly eroding the early-career experiences that shape future leaders. As entry-level roles decline, judgement, emotional intelligence and organisational fluency have fewer places to form. Leena Rinne argues succession strength must be measured in capability, then rebuilt through deliberate practice, feedback and engineered development pathways.
There’s a shift happening inside organisations right now that doesn’t show up on any succession plan. As AI absorbs more entry-level and early-career work, organisations are gaining speed but losing a critical development layer. Research shows that in roles most exposed to AI, junior positions have already declined by nearly 6%, a shift concentrated almost entirely at entry-level.
That’s where emotional intelligence, judgement and organisational fluency are built
These foundational roles have traditionally functioned as informal leadership apprenticeships, but not for the skills most people assume. The technical parts of early-career work are often the easiest to replace. What’s harder to replicate is what happens around the work: the junior employee who sits in on a tense client call and watches how their manager de-escalates it, or the new hire who learns to navigate competing priorities by observing how trade-offs get made in real time. That’s where emotional intelligence, judgement and organisational fluency are built, through repetition, observation and gradual exposure.
As AI systems increasingly take on the tasks that once created those moments, productivity gains are clear, but the developmental experiences that shape future leaders quietly fade. On paper, the talent pipeline may look healthy, but in practice, it is steadily losing capability, creating a succession risk that most organisations have yet to properly recognise or measure.
Succession risk today is about capability, not headcount
Succession risk is no longer defined by whether organisations have enough people in the pipeline, but by whether those people have developed the leadership capabilities required to succeed in increasingly complex roles.
Many succession plans still appear robust because roles are mapped and potential successors are identified. What they often fail to account for is how leadership capability is actually built. A persistent weakness is the reliance on time-in-role as a measurement for readiness, rather than evidence of demonstrated skill. Even as AI reshapes work and accelerates apparent performance, tenure and progression are still too often treated as indicators of capability.
As AI takes on more foundational work, employees have fewer opportunities to build skills such as emotional intelligence and decision making under real constraints. These are the conditions in which leadership is traditionally formed. Without them, capability can appear to progress while remaining under-tested in the areas that matter most in complex leadership environments.
The result is succession risk that shifts from visible gaps in roles to hidden gaps in capability. An organisation can have every role on its succession plan filled and still find itself exposed when those leaders are asked to scale decisions or manage ambiguity.
The deeper structural issue is the erosion of formative early-career experience. As entry-level roles shrink or become more automated, organisations lose the environments where people learn how work actually gets done, how relationships are navigated, how trade-offs are made and how judgement is developed over time.
Addressing this requires a deliberate mindset shift: rebuilding formative experiences through intentional development, structured practice and clear visibility into how leadership skills are actually progressing, not assuming capability will accumulate on its own. Without that, it won’t keep pace with the roles people are asked to fill.
How AI distorts perceptions of readiness
AI is fundamentally changing how readiness is perceived inside organisations. By accelerating productivity and improving the quality and polish of outputs, it can make individuals appear more capable and more senior earlier in their careers. I see this regularly: traditional indicators of readiness (speed, confidence, and delivery quality) are increasingly influenced by AI-assisted output rather than the development of underlying leadership skills.
Consider a mid-level manager who uses AI to produce polished strategy documents and well-structured presentations. The work looks senior. But when that person is asked to lead a difficult conversation with a struggling team member or make a judgement call with incomplete information, the gap becomes visible.
As a result, readiness can no longer be inferred from progression or performance alone. When organisations rely on these metrics, they risk overestimating bench strength and accelerating promotions beyond the underlying capability base. Assessing leadership potential requires a more direct focus on power skills, like the ability to make the right decisions, influence others and lead effectively, rather than assumptions based on role progression or output quality.
What it takes to intentionally rebuild leadership experience
When formative leadership experiences no longer happen organically, organisations must rebuild them deliberately. Leadership capability doesn’t disappear overnight, but it does atrophy without practice.
This means creating structured opportunities for practice: exposing individuals to ambiguity, accountability and interpersonal challenge at every career stage, not just at the senior level. It also requires consistent feedback that focuses on how decisions are made, how communication is received and how trust is built, not solely on outcomes.
In AI-enabled environments, technical execution is increasingly automated. What differentiates effective leaders are power skills that AI cannot replicate: problem solving, resilience, communication, time management and the ability to lead through complexity. These are the skills that determine whether someone can hold a room, rebuild trust after a setback or make the call when the data doesn’t give a clear answer. These skills must be developed intentionally across career stages, rather than deferred until senior roles.
This is also where organisations need a systems-level approach. A skills supply chain, one that connects how capabilities are identified, built, applied and measured across the employee lifecycle, is what turns individual learning moments into sustained leadership readiness, rather than leaving development to chance.
Rebuilding the leadership pipeline before the gap widens
AI is not removing the need for leaders, but it is quietly reshaping how leadership capability is developed. As organisations gain speed and efficiency, they are also losing the early experiences that once made employees knowledgeable and efficient. The greatest risk is not an empty pipeline, but one that appears strong until leaders are asked to operate under real complexity, uncertainty or scale.
Organisations that succeed will recognise that leadership readiness must now be intentionally engineered. They will design development pathways that deliberately build human capability alongside evolving work structures, ensuring future leaders are equipped to lead people as effectively as they manage technology. Leadership development can no longer be treated as a passive outcome of work and must be treated as an imperative tied directly to workforce readiness and long-term resilience.
Leena Rinne is VP of Leadership Solutions at Skillsoft
