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Why Does AI-Generated Thought Leadership Sound So Generic?

Because AI is often being asked to invent the most important part: the point of view.

A typical request looks something like:

Write a thoughtful LinkedIn post about why leaders should embrace AI.

The model does exactly what was asked. It creates a reasonable argument. It may talk about adaptability, innovation, responsible adoption, and keeping humans at the center. Nothing is necessarily wrong. And that's the problem. Thousands of executives could publish it.

Generic inputs produce generic outputs

AI can transform information remarkably well. But many thought-leadership prompts contain almost no information about the thinker. They don't include:

• personal experience
• unusual observations
• disagreements
• trade-offs
• stories
• specific beliefs
• earned expertise
• judgment

So the model reaches for patterns common across its training. That produces something plausible rather than something distinctive.

Thought leadership requires a point of view

Strong executive communication usually contains some combination of:

• I believe X.
• Most people think Y, but I think they're missing Z.
• Here's what happened when I experienced this personally.
• Here's what leaders should do differently because of it.

AI can help express those ideas. It should not be responsible for inventing them.

"Sound more human" isn't enough

One common solution is to tell AI:

• make it conversational
• use shorter sentences
• remove jargon
• add humor
• avoid clichés

That may improve the writing. It does not create a distinctive thinker. A generic argument written casually is still a generic argument. Better prompting practice for ChatGPT runs into the same ceiling.

Start upstream

Before producing content, capture:

• What does this executive actually believe?
• What experience supports the belief?
• What do they disagree with?
• Why does this issue matter to them?
• What would they say privately that is missing from the polished corporate version?
• What do they want the audience to think or do differently?

Now AI has something worth writing. Studio's capture and synthesis process exists to produce exactly that material.

This is an input problem

That's the core Studio thesis. The explosion of AI-generated content hasn't created the need for executive voice. It has exposed how little of that voice was being captured in the first place.

When the source material is distinctive, AI becomes extremely useful. When the source material is generic, AI simply produces generic content faster.