When people are asked to reskill, they are not just learning new tools. They are relearning how to feel competent.
As AI accelerates the pace of workplace change, experienced professionals face a particular challenge: the skills that earned them credibility over years or decades offer little advantage in mastering unfamiliar technology.
Research suggests many older workers actually want AI training, but the deeper struggle is rarely about willingness. People who have spent years as the expert often find beginner status frustrating, humbling and even threatening.
That feeling can be especially strong when the learning curve is public and moving fast. The resistance is often less about age and more about identity, status and safety. Employees in established roles are the most vulnerable because they have built their professional self-worth around competence.
Without support, time and psychologically safe learning conditions, that vulnerability leads to avoidance, defensiveness, or disengagement, even when the deeper feeling is embarrassment or fear of falling behind. The organisations that help employees the most are the ones that make beginnerhood safe.
People who have spent years as the expert often find beginner status frustrating, humbling and even threatening
Why competent people struggle to learn
The “expectation disconnect”, the gap between what people expect of themselves and what actually happens when they start learning, can feel like a massive chasm.
Experienced professionals carry an implicit assumption: I am a capable person, so I should pick this up quickly. The learning curve has other plans.
When reality collides with that assumption, the emotional fallout can be severe enough to derail the entire learning process.
The rollercoaster nobody warned them about
Most people imagine the learning curve as a steady upward climb. In reality, it functions more like a rollercoaster. The early phase feels electric: everything is new, progress comes fast and confidence soars. Then comes the plunge.
The learner knows enough to realise how much they do not know, and the gap is vast. This can feel like a “pit of despair”, and it is where most reskilling journeys die.
When employees hit that inflection point, predictable fear responses take over. Some freeze: they dabble without committing, hedge their efforts or disengage before the discomfort deepens.
Others deflect: they blame the programme design, the technology or their manager for the struggle. Still others power through with brute determination, grinding through the motions but never pausing to reflect or actually internalise the lessons.
All three responses share a common root: an expectation disconnect so painful that the brain defaults to self-protection rather than growth.
Most people imagine the learning curve as a steady upward climb. In reality, it functions more like a rollercoaster
Three strategies HR can deploy today
These patterns are predictable, which means they are addressable. The following three approaches can be embedded into any reskilling initiative to support the human experience of becoming a beginner again.
1. Normalise the learning curve explicitly
Before a programme begins, share the learning curve model with the participants. Show them the initial excitement, the inevitable plunge and the slow, uneven climb back up.
When learners can see the dip coming, they experience it as a normal developmental phase rather than evidence of a terrible mistake.
Naming the struggle removes the isolation that often accompanies it. Employees who understand the shape of the journey are far less likely to interpret a setback as a signal to quit.
2. Celebrate imperfection with a beginner’s mindset
The Japanese idea of wabi sabi is about finding beauty in imperfection. Kintsugi takes that even further, showing how broken pottery can become more beautiful after it’s repaired with gold.
HR leaders can borrow that same mindset by treating visible struggle as part of learning, not proof of failure.
Add in ganbatte, the idea of keeping going with grit and resourcefulness and kata, which is about learning through repetition and reflection, and you get a much healthier view of growth.
Together, these ideas make room for people to learn out loud instead of pretending they have to get it right immediately.
3. Design reskilling as small experiments
Instead of asking employees to commit to a full certification right away, break reskilling into small, manageable steps. Each one gives people a chance to try, learn, and adjust without making the stakes feel too high. If it works, great, you build on it. If it doesn’t, the lesson still has value and the person hasn’t been left feeling defeated. Over time, those small wins build confidence and make the new skill stick.
Making beginnerhood safe
The same pattern shows up with AI adoption and with any unfamiliar territory for high performers: the resistance usually comes from identity, not ability. It’s less about whether they can learn and more about what it means to be a beginner again.
Experienced workers are not rejecting learning itself. They are protecting the sense of competence they have spent careers building. When organisations treat reskilling as a content delivery problem, they overlook the emotional landscape that determines whether learning actually takes hold.
Making the learning low-stakes, normalising trial and error, and explicitly valuing curiosity over speed or polish: that is how HR transforms the experience of beginnerhood from something professionals endure into something they can embrace.
Read another article by Dr Melisa Buie: Framework: Four steps for turning failure into fuel
