Bryq’s AI Proficiency Assessment is a scenario-based evaluation that measures how candidates actually work with AI tools in realistic workplace tasks. It’s tool-agnostic, takes approximately 15 minutes, and produces a five-dimension proficiency profile scored 0 to 100, not a pass/fail result. The assessment is built on six peer-reviewed research frameworks: the UNESCO AI Competency Framework, SFIA (Skills Framework for the Information Age), OECD AI Principles, and three additional academic competency models spanning workforce research and policy-grade standards. It measures practical AI capability across any role, any industry. Not what someone knows about AI. What they can actually do with it.

75% of knowledge workers now use AI at work (Microsoft Work Trend Index, 2024). But most organizations have no way to distinguish between someone who uses AI as a force multiplier and someone who pastes everything into a chatbot without checking the output. Self-reported AI skills on resumes are unreliable. LinkedIn reported a 142x increase in members adding AI skills to their profiles (LinkedIn Workforce Report, 2024), with no way to verify what any of it means in practice. Meanwhile, 63% of employers say skills gaps are their primary barrier to workforce transformation (World Economic Forum Future of Jobs Report, 2025). A validated, scenario-based assessment closes that gap. You learn who can actually work with AI before you hire them, not six months later.

Now. Three forces are converging. First, AI adoption among knowledge workers has reached 75% (Microsoft Work Trend Index, 2024), meaning the vast majority of new hires will be expected to work with AI tools from day one. Second, regulators are moving: Article 4 of the EU AI Act (Regulation 2024/1689) requires organizations to ensure adequate AI literacy among staff who develop, deploy, or use AI systems. Third, uncritical AI users produce worse results than non-AI users, meaning a bad AI hire is costlier than a no-AI hire. Waiting another year to measure this skill is a risk, not a strategy.

The assessment scores candidates across five research-validated dimensions: AI Task Strategy measures whether someone can decide what to delegate to AI versus retain for human judgment. Poor delegation wastes time or creates dangerous automation. Prompting and Interaction Quality measures how effectively they communicate with AI tools and iterate when results miss the mark. Prompt quality is the number-one determinant of AI output quality. Critical Evaluation tests whether they spot errors, hallucinations, and gaps in AI output. Uncritical AI users produce worse work than non-AI users. Ethical and Responsible Use evaluates understanding of privacy, bias, intellectual property, and regulatory risks. Adaptive Learning measures how quickly they pick up new AI tools without hand-holding. Each dimension is scored 0 to 100 across three proficiency levels: Foundational, Functional, and Advanced.

Three levels, matched to different role requirements. Foundational covers entry-level and support roles: basic AI awareness, simple task completion, avoiding common pitfalls. Functional is designed for marketing, finance, operations, and HR roles: effective prompting, critical evaluation of output, and workflow integration. Advanced targets strategy, leadership, and AI-adjacent roles: complex multi-step workflows, governance considerations, and the ability to guide others in responsible AI adoption. You select the level that matches the role when configuring the assessment.

Yes. It’s included in all Bryq plans at no additional cost. You activate it from your dashboard and add it to any role in two clicks. No IT project, no new vendor meetings, no separate pricing conversation.

No. The assessment is deliberately tool-agnostic. It measures transferable skills that apply regardless of which AI tools a candidate has used. Testing for a specific tool creates a narrow, perishable result. Testing for proficiency across task strategy, prompting, critical evaluation, ethics, and adaptive learning gives you a durable picture of how someone works with AI today and how quickly they’ll adapt as tools evolve.

Self-reported AI skills are unverifiable claims. LinkedIn reported a 142x increase in AI-related skill listings (LinkedIn Workforce Report, 2024), but there’s no way to distinguish real capability from keyword padding. Asking about AI in interviews measures how well someone talks about AI, not how well they work with it. It’s the difference between describing how to swim and actually swimming. Bryq’s assessment puts candidates in realistic scenarios that test real-world capability: task delegation, prompt quality, critical evaluation of AI output, ethical judgment, and workflow integration. The result is a five-dimension proficiency profile based on what candidates do, not what they claim.

Article 4 of the EU AI Act (Regulation 2024/1689) requires organizations that develop, deploy, or use AI systems to ensure adequate AI literacy among their staff. The regulation doesn’t mandate a specific test. But a validated, scored assessment is the most defensible way to demonstrate compliance. Without documented measurement, proving “adequate literacy” becomes an opinion exercise with regulatory risk. Bryq’s AI Proficiency Assessment provides auditable, dimension-level evidence of candidate evaluation: exactly the kind of documentation regulators expect.