AI is designed to give answers. But should AI ask more questions?
We analyzed 904 responses from ChatGPT using a simple framework to explore how AI communicates:
- Advocacy means asserting a point of view
- Inquiry means asking a question
Here’s what we found:
- 65% of responses were advocacy only
- 3% were inquiry only
- 32% included both advocacy and inquiry
In other words, AI mostly talks. It rarely asks.
That finding mirrors a challenge many leaders face. Under pressure, it’s natural to default to advocacy. Leaders drive decisions, share their view, and push for clarity. But that style comes at a cost. Without questions, there’s little room for reflection, learning, or debate.
So we started wondering: Should AI ask more questions?
Why questions matter—for leaders and for AI
The best leaders do not just communicate clearly. They create space for others to think. They ask open-ended questions. They surface hidden assumptions. They invite multiple perspectives. In doing so, they foster stronger decisions and better problem solving.
If AI is going to support better thinking and decision-making, it may need to do the same.
What happens when AI only advocates?
When AI sticks to delivering answers, it risks reinforcing whatever assumptions the user brought into the conversation. It becomes a mirror, not a catalyst. That may be helpful in simple situations, but it falls short when the task requires nuance, creativity, or learning.
The same is true for human teams. When no one asks questions, you lose insight. You lose buy-in. You lose the chance to adapt.
What if AI coached more like a leader?
Imagine if your AI paused and asked:
- “What assumptions are you making here?”
- “What would someone who disagrees say?”
- “What’s another way to look at this?”
The goal isn’t to slow things down. It’s to get better thinking and stronger results.
If AI prompted inquiry more often, could it help your team move past groupthink, deepen understanding, and make smarter choices?
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