Many companies using AI are unintentionally building the case for why they don’t need humans.
I’m not sure what the exact split is, but based on my work with GTM teams, it feels like AI use breaks down roughly like this:
➡︎ 80-85% focuses on speed – “Do this task faster”
➡︎ 10-15% focuses on quality – “Do this task better”
➡︎ 3-5% focuses on innovation – “Do it differently”
I put together some examples of what each approach looks like in practice. See the chart below.
Focusing on productivity is a natural starting point. The risk is when we stop there. If we only teach AI how to do our jobs faster, we risk becoming unnecessary in the workflow.
But when humans push into quality and innovation, we potentially become essential collaborators.
Companies should ask questions that go beyond how AI can make their current processes faster.
➡︎ Instead of “How can AI write our emails faster?” ask “What messaging approaches would we never consider without AI’s help?”
➡︎ Instead of “How can AI analyze our data quicker?” ask “What patterns might AI spot that change our strategy?”
Ask what becomes possible when expertise flows freely across the entire org.
