How to Assess AI Competency in Non-Technical Roles | Bryq

How to Assess AI Competency in Non-Technical Roles

TL;DR: In our view, the strongest AI competency assessment for non-technical roles watches people do real work with an AI assistant. It doesn't ask them to rate themselves or quiz them on tools. Look for four things: a simulation of everyday work, scores across several skills rather than one number, levels matched to what each role needs, and a tool-agnostic design, so results don't depend on one product.

AI fluency matters in marketing, finance, HR, operations, sales and support, not only in technical roles. Microsoft and LinkedIn's 2024 Work Trend Index found that "75% of knowledge workers use AI at work today". So the question for these roles is what good use looks like in each job.

Why tool quizzes and self-report miss non-technical work

In our view, they mostly measure recall and self-image, not the work itself. A quiz checks whether someone remembers how a tool works. A self-rating checks how they see themselves. Neither shows whether a person can turn AI output into work you'd send to a client.

Non-technical work is full of judgement calls. A finance analyst has to notice when a summary invents a number. An HR partner has to know which employee details should never go into a prompt. A support agent has to rewrite a confident but wrong answer before the customer sees it. A multiple-choice question about features shows little of that.

Self-report has a second problem: in our view it captures confidence more than skill. A self-rating can reflect how often someone uses AI rather than how well. Tool-specific quizzes also date as products change.

So what does show up? Behaviour. Give someone a realistic task, a live AI assistant and a short time limit, then look at what they delegate, how they prompt, what they catch and what they hand in. That's evidence of how they actually work with AI, not what they say about it.

That's the approach behind Bryq's AI Fluency Assessment: a simulation with a live AI assistant.

What good AI fluency looks like by role family

Good AI fluency looks different in each function, so in our view the assessment should too. The table below is Bryq's practical guidance. Use it to decide what to probe in interviews and development conversations.

Notice the pattern. In our view, the skill that matters most in every row is the finishing: reviewing, correcting and owning the result. Treat AI output as a draft.

→ To measure this across functions, see our AI skills assessment page. Bryq's AI Fluency Assessment is role-universal and tool-agnostic.

How the Aware, Functional and Advanced levels map to roles

Not every role needs the same depth. We use three fluency levels matched to role requirements, with no pass/fail. Each person gets a fluency profile, and you compare it with the level the role calls for.

Two practical notes. First, these are typical mappings, not rules. A support team lead who designs how the whole team uses AI is doing more than Aware work. Second, sales isn't in the standard mapping, so set its level from what the role does with AI day to day.

A low Critical Evaluation score for a Functional-level role is a development gap with a clear next step, not a label on a person. That matters when you assess current employees as well as candidates. You're calibrating, not gatekeeping.

→ For the five dimensions in more depth, see our AI competency assessment framework.

A buyer's checklist for non-technical roles

Use these questions with any vendor, including us.

• Does the person work with a live AI assistant? Writing prompts, reviewing and correcting output, not just answering questions about it.

• Is it tool-agnostic? Skills should transfer across products.

• Does it fit every role family above? Or does it assume a technical job?

• Do you get several scores, not one? A single number hides where the gap is.

• Can you set the bar by role? An entry-level admin and a finance analyst shouldn't be held to the same level.

• Can you see the evidence? A transcript of what the person did makes a score something you can discuss, not just accept.

• How is open-ended work scored, and can you check it? Ask how the vendor keeps scores consistent across people and over time.

• Does it work for current employees too? Using the same instrument for hiring and development keeps results comparable.

• What research is it built on? Ask for the named frameworks behind it. In our view, a proprietary question bank alone isn't enough.

• How long does it take? Long enough to watch real work, short enough that people finish it.

• Does it sit alongside other signals? AI fluency should be one input among several.

Where Bryq fits

Bryq's AI Fluency Assessment is a roughly 15-minute, simulation-based assessment in which the candidate or employee works with a live AI assistant. It's tool-agnostic and role-universal, so the same assessment works for a marketer, a controller or a support agent.

Scores cover five dimensions on a 0 to 100 scale: AI Task Strategy, Prompting & Interaction, Critical Evaluation, Ethical & Responsible Use and Workflow Integration. Our AI fluency interview questions and scoring rubric covers each one in detail.

Every score comes with the full chat transcript and visible AI-reviewer notes. It's built on six peer-reviewed research frameworks, including UNESCO, SFIA and the OECD. Results sit in one profile alongside cognitive ability and personality traits. We don't claim AI fluency predicts job success on its own.

For more research and tools, browse the AI fluency hub.

Set the right level for each role. The AI Fluency Assessment is included in your Bryq plan. Book an AI fluency demo and we'll walk through which fluency level your roles call for, from Aware to Advanced.

FAQ

What is the best way to assess AI competency in non-technical roles?

In our view, the best way is to watch people do realistic work with an AI assistant and score what they do. A simulation shows how they delegate, prompt, check and finish work. Self-ratings show confidence and tool quizzes show recall. Neither shows how someone actually works with AI.

Is an AI literacy test enough for non-technical staff?

In our view, an AI literacy test is a start, not an answer. It typically checks understanding of concepts and risks. For roles that use AI every day, you also need to see applied skill: whether someone catches errors and turns a draft into finished work. Our guide to AI literacy, proficiency and fluency explains how the terms differ.

Should every role be held to the same AI fluency level?

No. Admin, entry-level and support roles typically need Aware level. Marketing, finance, operations and HR typically need Functional. Strategy, leadership and AI-adjacent roles typically need Advanced. Set the bar from what the role does with AI.

Can the same assessment be used for current employees?

In our view, yes. One instrument for candidates and employees lets you compare a new hire with the team they're joining, and spot development gaps across the workforce on the same scale. Bryq's AI Fluency Assessment uses the same instrument for both.