Are We Losing Our Drive for Mastery?
I’ve been knee-deep in Daniel H. Pink recently, revisiting the ideas in Drive: The Surprising Truth About What Motivates Us and the underlying research on Self-Determination Theory developed by Edward Deci and Richard Ryan.
Their research suggests that human motivation rests on three core psychological needs: autonomy, relatedness, and mastery (or competence).
When these are present, people tend to work harder, learn faster, and feel more fulfilled. When they are absent, motivation becomes fragile and dependent on ever increasing external rewards.
Autonomy and relatedness get a lot of airtime in leadership conversations (and I may well give them more in the coming weeks…). But, most recently, I’ve been wondering about the third one.
Mastery.
The deep human satisfaction that comes from getting really good at something.
Not quickly or effortlessly, but through repetition, frustration, failure, iteration and refinement.
And I’m starting to wonder whether, we might be eroding it slowly and unintentionally. I speak for myself just as much!
The subtle outsourcing of craft
I noticed it first in my own work.
I still do the thinking when I write. The ideas are mine. The perspective is mine.
But the final shaping of the sentences - the polishing, tightening, wordsmithing - is increasingly delegated to AI tools.
The output is often better, once I have taken back control of the final iteration.
Cleaner.
Sharper.
More efficient.
But something else has changed too.
When the article is finished, I feel less pride in the craft.
The ideas feel satisfying. The writing itself feels… less earned.
Which raises an uncomfortable question.
If part of the craft is outsourced, what happens to mastery?
Mastery grows in friction
Mastery rarely develops through ease.
It develops through effort.
Wrestling with a difficult paragraph.
Working through messy data.
Trying, failing, trying again.
Friction is not an obstacle to mastery.
It is the mechanism through which mastery develops.
And right now, technology is removing friction from many kinds of work.
Which is wonderful for productivity.
But potentially complicated for motivation.
Because the paradox is this: The easier something becomes to produce, the harder it becomes to feel proud of producing it.
Schools: teaching or delivering education?
Education offers a powerful example of this tension.
In many school systems, teaching materials are increasingly centralised and standardised in response to important questions about quality, consistency and workload.
Lesson plans are written centrally.
Slides are pre-designed.
Assessment questions are pre-generated.
Even feedback can now be automated.
The intention behind this is often positive:
Consistency.
Efficiency.
Reduced workload.
But there is another side to this shift.
When teachers are no longer designing lessons, crafting explanations, adapting materials, or experimenting with pedagogy, teaching risks becoming delivery rather than craft.
And teaching has always been a craft.
The mastery of teaching lives in things like:
crafting a metaphor that unlocks understanding
sensing when a class has lost attention and changing approach
refining an explanation until it lands for the tenth time that day
These skills develop through practice and iteration.
If more and more of the intellectual labour is centralised or automated, teachers may gain time - but they may also lose opportunities to develop and experience mastery in their craft.
It’s important because teachers who feel mastery tend to feel professional pride.
Remove the craft, and the job risks feeling more like execution than expertise.
Research and analysis
A similar pattern is emerging in analytical work.
Historically, researchers and analysts developed expertise through slow investigation.
Collecting data.
Cleaning it.
Exploring patterns.
Testing assumptions.
These steps were part of the journey towards mastery. They built judgement and discernment.
Today, AI tools can:
summarise research papers
generate literature reviews
analyse datasets
produce draft insights
Again, the outputs may be faster and sometimes better.
But the process of developing analytical mastery may be shortened or bypassed.
The risk is that we lose the internal capability that produces good judgement.
Mastery in research is not simply knowing the answer. It is knowing how the answer was discovered.
Writing and communication: the disappearing struggle
Writing is another area where the tension is becoming visible.
Many professionals now rely on AI to:
draft emails
structure articles
rewrite paragraphs
summarise ideas
The result is often more polished and more accessible communication.
But writing has always been more than communication.
It is also a tool for thinking.
The struggle to articulate something clearly often forces us to clarify what we actually believe or mean.
When the articulation is automated, that cognitive struggle can disappear.
The writing becomes easier but the thinking may become shallower. Fast forward in time and you have leaders who haven’t fully articulated and internalised what they want/need for themselves, making it impossible for anyone else to meet their expectations and drive the organisation forward.
Creative fields: skill versus output
Design, illustration, coding and music are experiencing similar shifts.
Generative tools allow people to produce impressive outputs without necessarily developing the underlying skill.
An image can be generated in seconds.
A functional piece of code can appear instantly.
But creative mastery historically developed through:
thousands of small experiments
mistakes and revisions
refinement of taste and judgement
When output becomes effortless, the temptation is to stop developing the underlying craft and the pride that then ensues.
The deeper psychological cost
This is not just about skill and productivity, it’s about identity.
Mastery gives people a sense of who they are.
“I’m a good teacher.”
“I’m a strong analyst.”
“I’m a writer.”
These identities are built through effort and improvement over time.
If technology removes too much of the path to mastery, people may still produce work - but they may feel less connected to it.
Less ownership.
Less pride.
And I’m guessing, eventually, less motivation.
The paradox of progress
None of this means that automation or AI are bad.
Many of these tools genuinely reduce unnecessary labour.
But they also create a new leadership challenge.
If technology removes the friction that used to build mastery, organisations may need to intentionally create new pathways for mastery to develop.
Otherwise we risk drifting toward a world where:
outputs are faster
processes are easier
but work feels less meaningful
And motivation drifts - and we know, thanks to Dan Pink and Co, that when motivation drifts, productivity tanks.
And, mastery has always been one of the most reliable ways humans experience satisfaction, pride and meaning in their work. If that tanks, what happens to happiness and contentment?
Choosing where mastery still matters
We are where we are and we can’t reverse the tide but we can choose where and how to keep mastery alive.
Not everything needs to be mastered.
But some things probably should.
For teachers, it might be the craft of explanation and human connection.
For researchers, it might be judgement and curiosity.
For leaders, it might be the deeply human skills that cannot be automated: presence, courage, compassion.
And for writers, it may mean deciding when to let technology help - and when to wrestle with the sentence ourselves.
Because mastery is about the slow satisfaction of becoming someone who can do something really well.
And I definitely want to intentionally protect that for myself. Do you?