Questioning the Value of a Leader's "Questions" in the AI Era

Hello, I am Mitsunori Kimura, an expert in Smile Engineering. Please see this article for more on "Smile Engineering."

If you are asked a blaming question like, "Why did you make such a mistake? Whose fault is it?" people will likely shrink away and become unable to speak about the true causes or information.

Conversely, if you are asked, "What can we learn from this failure?" you should be able to speak frankly and with peace of mind.

This difference in how questions are asked has a major impact on organizational productivity and costs. Especially in the modern era where AI has developed, a leader's "way of asking questions" is becoming an increasingly important key.

The difference between concealment and learning created by "questions"

The psychological safety that allows team members to speak their true feelings with peace of mind is an element directly linked to management.

Regarding psychological safety, I would like to introduce the following article as it provides an easy-to-understand explanation.

In workplaces with low psychological safety, members tend to remain silent even when problems occur, and knowledge sharing and problem discovery stall. As a result, rework occurs due to delayed responses, leading to a decline in organizational performance and an increase in employee turnover.

On the other hand, in workplaces with high psychological safety, members can share failures and weaknesses without hiding them, allowing problems to be discovered early and dealt with quickly.

When there is a meaning-seeking question from a leader—that is, a constructive question such as "What is the cause, and how can we improve it?"—members can share ideas and concerns with peace of mind, increasing the learning speed of the entire organization and making it easier for innovation to occur.

Summarizing these differences, the following gaps arise between inquisitorial questions and meaning-seeking questions.

• Inquisitorial questions (e.g., "Who failed?") → Induce information concealment, leading to delayed problem discovery and increased rework. They impair psychological safety and lead to lower productivity and increased turnover.

• Meaning-seeking questions (e.g., "What is the cause? How can we apply this next time?") → Failures and issues are shared early, and countermeasures can be executed quickly. Through dialogue, the learning and improvement cycle accelerates, leading to innovation and preventing turnover.

In short, depending on the leader's questions, it can turn into either "increased costs due to concealment" or "promoted learning through sharing."

This is not just a matter of mental attitude, but an important policy that affects organizational performance and talent retention.

Leave monitoring and control to AI, and humans create value through "questions"

While AI and RPA handle routine monitoring and management tasks, leaders should focus their energy on "questions" that read context and create meaning.

AI can perform log monitoring and anomaly detection more accurately and quickly than humans, and such tasks are better suited for machines.

On the other hand, there are "questions" that only humans can ask. For example, posing a question like "What is the true purpose of this project?" and generating new perspectives is a role unique to humans.

Also, AI cannot ask questions that empathize with members' emotions to draw out motivation, nor can it tell the organization's vision as a story.

By automating tasks that can be left to AI, leaders can focus on roles unique to humans, such as fostering creativity and cultivating team culture.

Spending too much human effort on monitoring and control is like trying to compete in areas where machines excel. Maximizing human creativity, empathy, and the power to create meaning is the stance required of leaders in the AI era.

Summary

Rather than 'Who/What/Where' type questions that merely record the past or facts like a log, questions that open up the team's next narrative are the skills required of leaders from now on.

In an era where AI can provide many answers, leaders should strive to be individuals who can present high-quality questions that guide the next move.

The quality of questioning can be trained. As a partner in training the quality of those questions, AI can be of help in this area as well. I covered this in
a recent article, so please take a look if you are interested.

Start by consciously reducing status-quo-seeking questions and increasing future-oriented inquiries in your daily meetings and 1-on-1s.

'What is the true significance of this project?' When such a question is asked, the atmosphere of the team changes completely. If members can exchange opinions with peace of mind and start thinking and acting on their own, the organization will become a living learning organization.

What is being questioned in the AI era is what kind of questions the leader themselves asks and what kind of narrative they can weave. That stance is what determines the future of the team.

Thank you for reading until the end.

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