From AI Fluency to AI Competency
A research-based perspective on what AI changes in your competency model
JST People Strategy benchmarked 50 competency models. Nearly all of them are silent on what AI competency requires.
That silence matters because CEOs are already telling employees to build AI skills. When the competency model doesn’t say what those skills look like on the job, hiring, performance, and development keep measuring the work as it used to be. Output volume starts to stand in for performance, and it overstates who is doing well.
Research to date has focused mostly on AI fluency: what a person understands about AI and its tools (see AI Fluency, Defined). Competency is different. It is the judgment people apply once AI is part of their role, and it shows up inside the competencies you already have.
At JST People Strategy, we believe AI doesn’t add a new competency to your model. It raises the bar on every competency you already have. Take a common Decision-Making competency. “Makes sound decisions based on available information” becomes “Judges which AI-generated analysis to trust; can defend the ultimate analysis.”
That’s why we created From AI Fluency to AI Competency, a point of view for leadership teams updating their competency models for AI. It covers:
Fluency versus competency: what each is built on, how people build it, and how to measure it
Nine judgment calls: the decisions employees make before, during, and after AI-assisted work, and when leading others
Durable human capabilities: the five that become differentiators as AI changes what competence means
Implications for your people systems: what changes in hiring, performance, and development
Train for fluency. Apprentice for competency. Judgment transfers when people do real work alongside experienced colleagues.