How to Measure “AI Literacy”

AI literacy is becoming a major consideration in employment. More employers are seeking candidates who understand AI and can use it effectively. However, just because a person uses AI frequently, that doesn’t necessarily mean they have high AI literacy. Like any other skillset, AI literacy is about knowing which tool to use for the task at hand. A recent Fisher Phillips memo breaks down AI literacy into four competencies:

“Awareness: Knowing AI’s strengths, weaknesses, and risks, including bias, hallucination, and privacy implications.

Application: Using AI tools to draft content, analyze data, or streamline workflows while maintaining human oversight.

Adaptability: Staying curious, experimenting safely, and learning as tools evolve.

Accountability: Knowing when to question, verify, or override AI output.”

AI literacy isn’t about throwing AI at every task and producing “AI workslop.” It’s about understanding when AI can assist with or automate a task. AI literacy is also specific to job roles and responsibilities. Just because an employee can use AI to create a grocery list doesn’t mean that the same employee can use AI to analyze a dataset. AI is a tool, and like any tool, it is only as useful as the context of the situation allows. Therefore, there is no blanket one-size-fits-all test for AI literacy. Instead, a candidate or employee should be evaluated on their knowledge of how AI can be applied to their specific situation. Equally important, they should know when not to use AI and be familiar with the specific risks that AI brings to their role so they can mitigate them.