Has AI Ever Asked You a Question?
This is why, at times, you might prefer a curious human over AI. But Wait!
Last weekend my friend asked me - “What dog should I get?”
Instead of answering her question, I asked her this “Why do you even want a dog?”
That question led to a long soulful conversation rather than discussing different breeds of dogs.
If she had asked the same question of ChatGPT, it would have simply given her a hundred different dog breeds to choose from.
And that’s where lies the fundamental shortcoming of AI systems today - the inability to ask questions rather than only answering them.
I will give you another example which is more HR related…
My colleague, Anita attended a Leadership conference last year. Inspired by the conference, she was determined to create a “Mentorship program” at her company.
She had drafted a comprehensive plan with all the juicy details she was excited about sharing with her manager.
Before presenting it to leadership, she shared it with her manager over coffee. Instead of immediately reviewing the implementation details, her manager asked her this ONE unexpected question:
What specific gaps are we trying to address?
This question changed everything. Anita realized her plan, while technically sound, was actually solving the wrong problem.
Why Answers Without Questions Fall Short
Today's AI operates fundamentally as a response engine. They're trained to pattern-match against previous data and generate outputs based on what they're given.
What they cannot do—at least not yet—is recognize when information is insufficient and proactively seek clarification.
This creates what I call the "Helpfulness Trap": The people who most need guidance (those who don't know what factors to consider) receive the least helpful recommendations because they don't know what information to provide when asking the question.
Going back to our “dog” example, a human advisor would start probing: "Have you owned a dog before? How much time can you commit to spend with the dog? Do you live in an apartment or house? What's your budget? Are you looking for emotional support or physical protection? or even a deeper question “Why a dog?”
We need this human inquisitiveness to take a step back and re-think our options.
AI, however, simply processes your limited input and produces a response based on general associations between dogs and companionship.
It might recommend a Labrador because they're "friendly" or a Border Collie because they're "engaging"—without considering whether these high-energy breeds match your lifestyle, living situation, or budget.
This isn't because AI is unintelligent. It's because questioning requires a different kind of intelligence.
Why Does it Matter?
It matters to us folks in HR, because in use cases like “Candidate Shortlisting”, AI might recommend candidates based on keywords in resumes without asking about team dynamics or long-term developmental goals.
I heard this from a Talent Acquisition specialist I met with recently, she told me they are implementing an AI resume screening tool.
"It was efficient but…" she explained. "It never pushed back when hiring managers had unrealistic expectations. It would simply search for candidates matching impossible criteria instead of flagging the problem."
This highlights perhaps the most valuable aspect of humans: they
Challenge assumptions
Reframe problems.
So How Can You Solve This Today?
The simplest answer - Better Prompting!
Generate a good prompt using a tool like gudprompt.com
Ask AI to ask you questions. Here’s how you can do it:
Reframe the question to ask AI to ask you questions:
Building Better Human-AI Partnerships
Rather than positioning AI as an “Oracle” with answers, we should frame it as a detective like “Sherlock Holmes”.
Second, we need to train ourselves and our teams to be better AI users. This means developing the habit of providing comprehensive context and questioning AI outputs with the same rigor we would apply to human advice.
As one chief learning officer put it: "We're not just training our people to use AI—we're training them to supervise AI."
The Future of Questioning AI
The good news is that AI research is moving toward systems that can identify information gaps and request clarification. Some experimental systems can now detect when they don't have enough context to provide reliable answers.
However, true questioning ability—the kind that challenges premises and reframes problems—remains a distinctly human capability. It requires not just detecting missing information but imagining alternative perspectives and approaches.
Until AI evolves this capacity, the most effective human-AI partnerships will be those where humans maintain responsibility for question-asking and problem framing, while AI amplifies our analytical capabilities once the right questions are established.
Takeaway
As you implement AI across your organization, consider:
Are your teams using AI as a thought partner or treating it as an oracle?
Have you built processes that ensure critical context isn't omitted when consulting AI?
Are you measuring AI success by the quality of decisions it supports, not just efficiency metrics?
Most importantly, remember that in a world where answers are increasingly automated, the ability to ask the right questions becomes our most valuable skill.
The next time you consult an AI system, pause and ask yourself: "What would a thoughtful human advisor want to know before answering this question?" Your answers to that question might be the missing piece that transforms artificial intelligence into actual wisdom.
Comment below if you want more cute dog gifs :)