When AI Gets in the Way of Thinking: Two Stories Worth Reading
- Vidhya Logendran
- 7 days ago
- 3 min read
Anna
Anna wanted to avoid a repeat of past frustrations. The cleaner was coming the next day, and she knew from experience that vague instructions led to vague results. Things got done—just not always the things that mattered most.
This time, she decided to be clear. She opened an AI tool and asked it to help her create a cleaning task list.
The response surprised her. Instead of a simple list, the tool suggested using a shared workspace and task management setup. That wasn't what she needed.
She tried another AI. This one gave her a list—but it came wrapped in formatting symbols and technical structure, as though the cleaner were a project team, not a person.
By the third tool, she finally got something usable: a neat, categorised checklist.
Anna read it once. Then again. It wasn't wrong. It just didn't reflect her home—what had been missed before, what she cared about most this time, what she would normally emphasise if she were explaining it herself.
She closed the app, rewrote the list in two minutes, and moved on.
Her conclusion was quick and decisive:
"AI isn't that useful for real life."
What Anna didn't notice was this:
She had never clarified—even to herself—what "a good list" meant in this situation. The thinking stayed implicit. The AI filled in the gaps as best it could.
She dismissed the tool—and with it, the chance to use it as a thinking partner rather than a shortcut.
Bianca
Bianca had the opposite experience.
She was planning a holiday with friends and had recently attended a prompting class. She knew to give context, describe preferences, and ask follow-up questions. She did everything "right".
The AI responded with thoughtful suggestions, clear trade-offs, even a draft itinerary. Bianca was impressed. It felt efficient. Smart.
She shared the plan with her friends.
As they talked it through, questions came up.
"Why this destination?" "What made this option better than the others?"
Bianca hesitated. She had answers—but they didn't quite feel like hers. The reasoning sounded right, but she couldn't fully stand behind it. She noticed a quiet unease she couldn't articulate.
Eventually, the discussion fizzled. The plan stalled.
Bianca walked away thinking:
"AI is powerful… but somehow this still doesn't feel right."
She didn't reject the tool. She followed it—right up to the point where her own judgement quietly disengaged.
The Parallel
Anna dismissed AI too quickly. Bianca relied on it too smoothly.
One stepped away from the tool. The other stepped behind it.
Both missed the same thing.
AI wasn't the problem in either case. The problem was how thinking was handled.
Anna treated AI as a replacement for thinking and found it wanting. Bianca treated AI as a guide for thinking and stopped challenging it.
In both cases, the human stayed either outside the process or got quietly absorbed into it.
The Bigger Picture
The real risk with AI isn't that it gives bad answers.
It's that we either:
Dismiss it when it doesn't immediately fit our needs, or
Over-trust it when it sounds fluent and confident
Both responses lead to the same outcome: we stop actively shaping our own thinking.
Used well, AI is neither a shortcut nor an authority. It is a thinking partner—one that needs clarity, direction, and judgement from us to be useful.
That requires us to stay mentally present:
To surface what we actually care about
To interrogate outputs, not just accept or reject them
To notice discomfort instead of ignoring it
This is not about better prompts. It's about better thinking with AI.
From Everyday Decisions to Strategic Judgement
This pattern shows up everywhere—not just in personal tasks, but in the work that matters most: complex decisions, strategic planning, professional judgment calls.
That's why we conducted a year-long research initiative exploring how professionals across sectors are navigating AI adoption. We worked with senior leaders, decision-makers, and knowledge workers to understand what's actually changing in how we think, decide, and lead.
The findings reveal a more nuanced challenge than most organisations recognise—and point toward practical approaches that preserve judgement while leveraging AI's capabilities.
Read the Executive Summary:
Explore our signature solutions:
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