Introduction: What this tool helps you do
When it comes to AI, most organizations are doing something, but there’s no consensus on a “right” way to consistently define, assess, and develop AI skills across roles as AI moves from experimentation to everyday work.
This tool gives you a clear and practical starting point:
- A clear, foundational definition of practical AI skills
- Observable behavior-based rubrics tailored to different scopes of responsibility
- Question banks to help you evaluate how people use AI in their real work
- Scorecards to assess AI skill maturity at the individual level
- A consistent way to identify strengths and gaps across teams
- The structure to build an AI skills benchmark for your organization
Use the question banks, rubrics, and scorecards to assess individual AI capability, roll results up by team or function, and create a clear benchmark of AI skill maturity across your organization.
The HiBob AI Skills Framework behind this assessment tool
This assessment is built on a structured AI skills framework validated by 1,200 multi-national decision-makers. It translates vague concepts like “AI literacy” into observable workplace behaviors you can evaluate consistently.
The framework organizes AI capability into three skill sets, seven competencies, and 29 observable behaviors. Instead of measuring whether someone uses AI, it helps you assess how they use it: the judgment they apply, the risks they consider, the outputs they improve, and the outcomes they help create.
How to use the AI skills assessment tool
Use this assessment anywhere you evaluate people, including interviews, performance conversations, self-assessments, and development planning. Log scores using the rubrics to determine if a skill is developing, proficient, or advanced.
Keep these four rules in mind:
- Anchor questions in use cases. Ask about specific work tasks, not broad AI trends. Specific use cases produce stronger evidence and help you choose questions that match the person’s scope of responsibility.
- Look for behavior, not confidence. Avoid over-weighting polished language or broad claims like, “I use AI every day.” Strong answers will describe what the person actually did, what risks they considered, and what changed as a result.
- Probe for judgment in addition to skill execution. Strong AI users know when human judgment is required and how to verify outputs. Follow-up probes test the person’s reasoning, not just their final output.
- Use questions selectively. You do not need to ask every question. Choose the questions that align most closely with the behaviors that matter for the role, team, or performance conversation.
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Step 1: Map responsibilities, not job titles
It’s important not to get stuck on traditional job titles or org chart structures. In a modern job catalog, a role is simply a collection of responsibilities and goals, and skills are the abilities people need to execute them.
Before you dive into the question bank, build a profile for the person you’re assessing based on the AI-related responsibilities tied to their role. Mapping those responsibilities first will help you pinpoint which AI skills to evaluate, which questions to ask, and how to score the response.
Step 2: The assessment
Skill set 1: AI Readiness | AI Literacy
Best for: Roles that decide when AI should or should not be used and what to expect from its use.
The goal: Understand human and AI capabilities. Select appropriate AI tools. Set realistic expectations for AI-augmented work. Measure AI impact and value.
Skill set 1: AI Readiness | Continuous Learning
Best for: Roles that actively refine how AI supports their work and guide others in using it well.
The goal: Embrace continuous AI learning and improvement. Engage in peer coaching. Drive ongoing AI enablement and team adoption.
Skill set 2: Individual AI Usage | Prompting and Input Quality
Best for: Roles that rely on AI to produce high-quality outputs in their day-to-day work.
The goal: Write clear, actionable prompts. Direct AI toward reliable and relevant source material. Review prompt quality proactively. Write multi-modal prompts.
Skill set 2: Individual AI Usage | Evaluating and Improving Output Quality
Best for: Roles that use AI to create or complete their own work and to review, edit, approve, or make decisions about work others have produced.
The goal: Proactively review output quality. Interpret AI-generated analytics and evidence. Revise AI drafts for different audiences and purposes. Resist overly flattering or overconfident AI. Recognize the limits of their own expertise. Demonstrate bias and fairness awareness.
Skill set 2: Individual AI Usage | AI Safety, Ethics, and Governance
Best for: All roles, especially those responsible for guiding how people and AI agents use AI safely, ethically, and effectively.
The goal: Handle sensitive data appropriately. Use AI responsibly. Reinforce human accountability. Apply transparency and attribution.
Skill set 3: Organizational AI Usage | Workflow Evaluation and Redesign
Best for: Roles that
- Define how AI fits into team, function, or business workflows
- Build or maintain AI-enabled automations, agents, or integrations
- Coach or enable others to use AI effectively
The goal: Map workflows. Proactively evaluate workflow performance. Design efficient human–AI handoffs and standards. Partner across functions to reduce risk. Document workflow decisions for reliability. Redirect saved time or resources toward higher-value work.
Skill set 3: Organizational AI usage | Automation and Technical Integration
Best for: Roles responsible for building or maintaining AI-enabled automations, agents, or integrations.
The goal: Create reliable no-code and low-code automations. Connect AI to everyday tools to reduce manual steps. Demonstrate basic coding capabilities to connect systems and troubleshoot problems. Use API keys securely, handle common failures, and add simple logging so workflows can be monitored and fixed without guesswork.
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Step 3: Turn your scores into a benchmark
Evaluating whether a current team member or candidate has a specific AI skill is only the first half of the equation. The second half is understanding whether that skill helps create value.
To build your benchmark, average individual scorecard results across each relevant competency. Then roll those results up into team-level scores, and combine team scores into an organization-wide baseline.
That baseline is your AI skills benchmark. It gives you a clear view of where your people are prepared to use AI safely and effectively, where capability gaps remain, and where targeted development can make the biggest difference.
Use your benchmark to guide workforce decisions
A benchmarking standard gives you a clear, consistent view of AI skills that allows you to embed AI capability into the systems that already shape your people strategy:
- Hiring. Move beyond generic claims of AI familiarity and assess how candidates apply judgment, evaluate outputs, and manage risk in real scenarios.
- Performance. Evaluate AI capability based on how work is done—not just whether AI is used—using consistent, behavior-based criteria.
- Workforce planning. Identify where critical AI capabilities exist across your organization, where gaps could affect execution, and where you should invest in development.
- Learning and development. Focus on behaviors that improve real outcomes, not just tool training or general AI literacy.
From AI usage to AI judgment
AI capability is often mistakenly framed as an activity metric: Who is using AI? How often? For what tasks?
But usage alone doesn’t drive value.
Strong capability shows up in how people apply their judgment: how they verify outputs, manage risk, and translate AI-assisted work into better outcomes.
As AI skills become a baseline capability, consistency matters more than ever. A behavior-based assessment helps you define what good looks like, evaluate skills with structure, and embed AI capability into performance, hiring, development, and workforce planning.
That’s how you build an AI-fueled, human-driven organization where people lead the way, and AI supports them in delivering better outcomes.
<<Build an AI-fueled, human-driven organization with skills you can assess today. Download the AI Skills Assessment tool now.>>