Your Team Still Needs to Learn How to Judge the Work
By Suzie Thoraval
As AI becomes part of everyday work, leaders need to protect judgement and discernment
“The real problem is not whether machines think but whether men do.”
I was recently teaching strategic thinking, and I said that Artificial Intelligence had become a useful way to gather scattered data and find the significance and the thread running through it.
A young woman near the back made a face. When I asked what she thought, she said something that really struck me.
People with experience can use AI and then judge what it gives them, she said, because they spent years building that judgement before these tools were available. Someone who has used AI from their first day has nothing to judge it against, and no real way to tell whether what comes back is any good.
In other words, they are losing the opportunity to hone their skill of judgement and discernment.
Audience reaction at recent graduations
Across the US 2026 university graduation season, students booed business leaders who came to preach about the transformative power of AI.
Eric Schmidt, the former head of Google, was recently jeered at the University of Arizona when he urged graduates to embrace AI and climb aboard, comparing it to a rocketship you should simply get on without pausing to ask which seat.
To people walking into a job market already being reshaped by AI, that must have sounded less like encouragement than an instruction to accept the disruption on terms set by someone else. The audience reaction was not unique to him. Other business leaders and tech CEO speakers have met the same response across the 2026 graduation season.
My sense is that these younger audiences are tired of being told to be grateful for AI’s efficiencies by people whose jobs are safe and have had years of experience in judgement and discernment.
They must feel that they are the ones who will be most affected by AI in entering the workforce and least equipped to judge what it produces.
The real skill is judging the work
Producing the work and judging whether it is any good are two different skills. AI can write a paragraph that sounds polished and convincing. Whether it will land with this reader and move them to act is a separate question that only your judgement can answer. That’s about the quality of the ideas.
You build that judgement slowly, by making something and watching whether it draws the response you intended.
I learned it over years in government and legal work, where I had to write for the decision maker rather than for myself. The hardest lesson was that good writing gives the reader what they need in order to act. The juniors I taught learned it as I had, by writing the earnest version of what they thought needed to be said, watching it fall flat, and slowly understanding that to have impact, it must be clear in purpose and tailored for the audience.
The ironies of automation
In 1983 the psychologist Lisanne Bainbridge wrote about what she called the ironies of automation. She said that it was more important than ever to keep the human skills that were needed before the machines because when a machine takes over the routine work it leaves people only the rare, hard moments it cannot handle. Those are the situations that need the most skill, and yet, with the machine doing the everyday work, people get so little practice that their skill weakens just when they need it most.
Matt Beane found the same when robotic surgery meant that senior surgeons could operate alone and left trainees out of workplace learning.
I think this risk is also true for knowledge work. Output from AI might look good enough that juniors in the workplace are not experiencing the useful failure and rework that would have taught them nor are they often encouraged to practise the skill of discernment on the ideas behind the writing.
Where adaptive stability comes in
Leaders need to use their foresight to notice this risk and deliberately make an effort to set expectations and train their teams so they are gaining the human skills of judgement and discernment. Using adaptive stability will help them balance the need to respond to the pressure to do more faster with spending time supporting their teams to hone their human skills.
You also need the mindset to be vigilant against your own skill fading as AI use becomes integral to your work. Your resilience is in noticing any slow loss and keeping that skill and using it to support the next generation. You are staying ‘fit’ in the AI enabled workplace.
Protecting judgement and discernment your team
Question the thinking behind the words. When AI produces something polished, ask these questions: What is it assuming? What has it left out? Which claim would not be accurate if you check the source?
Make good thinking count. When you look at someone's work, ask them to explain how they reached the views and how they checked what the AI gave the. Reinforce that thinking as part of good writing. Once your team sees that sound judgement is valued as much as a quick, finished answer, they will put their effort there.
Preserve your own views before you open AI. Choose the few kinds of decisions you will always form your own view on first, perhaps the ones that reach a client or a board, the ones about people.
How might you invest in a junior person's development, and where do you most need to keep your own skills sharp so that you can keep guiding them well?
