What does it mean to be 'good' at AI?

Good at prompt engineering? Able to use an AI tool well? An expert at deploying AI systems? Able to build and train a foundation AI model from scratch?

Perhaps none of these things. Not for most people, in most jobs.

Being good at AI could be both simpler, and harder.

Stephen Tracy and I built Job AQ as an experiment to think about this. A free and short behavioural assessment to understand how well you actually work with AI, not what you know about it. In contexts that are relevant. The scenarios are drawn from archetypes that match your job.

Here's what you get from it.

Before: A feeling. "I'm pretty good with AI."
After: A score, and blind spots likely to trip you up.

Before: No real idea where you stand.
After: Your 4 behaviours side by side, where you are strong and where you are weak.

Before: Guessing where AI would even help in your work.
After: A skills map with the opportunities.

Before, for a team: Adoption numbers that tell you nothing.
After: Who can be trusted with AI, and where the blind spots are.

Take it once and you have a baseline. Take it again in a quarter and you have a before-and-after.

Free. Fast. Try it at jobaq.me.

The free ebook below explains "The Whole Elephant" (based on my old illustration). In the carousel below.

#AI #AIFluency #FutureOfWork #AIRiskManagement

Jobaq Ebook Extended

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