Assessment
Artificial Intelligence Skills Assessment
An artificial intelligence test for candidates: AI fluency at work, prompting, checking AI output, data privacy and workflow judgement, with sample tasks.
The short answer
An artificial intelligence skills assessment for hiring typically runs 25-40 minutes, ai-assisted work task, output review and correction, scenario judgement and short written explanation, at 3 difficulty levels. Give it after the first screen and before interviews, and score it on the areas below, fixed before you see any answers, so every candidate is judged the same way.
- Prompting with context, constraints and examples to get usable output
- Verifying AI output: catching invented facts, wrong figures and missing caveats
- Knowing the limits of AI tools and when not to use them
- Protecting confidential and personal data when using AI tools
Cohesyve tests Artificial Intelligence inside an AI job simulation of the role, after finding and contacting candidates. Ten candidates free, no card.
About to take an Artificial Intelligence test? Practise it free →An AI skills assessment tests how well a candidate uses AI tools to do their job: giving a tool clear context and constraints, checking its output for errors and invented facts, deciding when not to use it, protecting confidential data, and building AI into a workflow that still produces reliable work. The phrase 'artificial intelligence test' is also used for tests of AI systems themselves, such as the Turing test or model benchmarks; this page is about testing people. AI fluency is relevant to many office roles, from marketing and support to finance and engineering, and the best assessments give candidates an AI tool and a realistic task, then score the result and the judgement behind it.
Format
What it measures
- Prompting with context, constraints and examples to get usable output
- Verifying AI output: catching invented facts, wrong figures and missing caveats
- Knowing the limits of AI tools and when not to use them
- Protecting confidential and personal data when using AI tools
- Integrating AI into a workflow with appropriate human review
- Explaining AI-assisted work honestly to colleagues and customers
- For technical roles: evaluating model output systematically and using AI APIs
Test Artificial Intelligence on the real work
Cohesyve builds an AI job simulation from your job description that covers Artificial Intelligence as the role uses it, finds and contacts candidates, and returns a ranked shortlist. Ten candidates free, no card.
Who takes it
Topics covered
Prompting
- Giving context and constraints
- Providing examples
- Breaking a task into steps
- Iterating on weak output
Verification
- Checking facts and figures against sources
- Spotting invented citations
- Detecting missing caveats
- Consistency checks
Responsible use
- Confidential and personal data
- Company AI policies
- Disclosure of AI assistance
- Bias in outputs
Workflow design
- Where AI saves time
- Human review steps
- Measuring quality
- Knowing when to stop using AI
Sample questions
Using the AI tool provided, summarise these 30 customer support tickets into the top five themes, with one example ticket for each. Then tell us how you checked the summary.
Everyday userLook for A prompt with clear structure and constraints; themes that match the tickets; and a real check, such as sampling tickets against the themes, rather than trusting the first output.
This AI-drafted customer email quotes a refund window and a price. Our policy document is attached. Find and fix anything wrong before it is sent.
Everyday userLook for Checks every factual claim against the policy, corrects the errors, and adjusts tone; does not assume fluent text is accurate.
A colleague wants to paste a client contract into a free public chatbot to get a summary. What do you advise?
Power userLook for Raises confidentiality and data-handling risk, points to the approved tool or policy, and suggests a safe alternative rather than just saying no.
An AI tool's summary of a quarterly report says revenue grew 12%. How would you confirm this before it goes into a board pack?
Power userLook for Goes back to the source figures, recalculates the percentage, checks the period and definitions, and notes the source in the pack.
Your team wants to use AI to draft first responses to support tickets. Design the rollout, including how you will know whether quality has dropped.
AI leadLook for Starts with a narrow ticket type, keeps human review, defines quality measures (accuracy, customer satisfaction, escalations), samples outputs regularly, and plans a rollback.
Red flags
- Treats fluent AI output as correct without checking
- Pastes confidential or personal data into unapproved tools
- Cannot improve a weak output except by asking the same question again
- Uses AI for tasks where accuracy cannot be verified
- Hides AI use where disclosure is expected
- Cannot explain or defend the final work in their own words
Scoring rubric
| Criterion | Weight | What strong looks like |
|---|---|---|
| Output quality | 30% | The final work is accurate, useful and fits the brief. |
| Verification | 25% | Checks claims against sources and catches errors. |
| Prompting and iteration | 20% | Gives context and constraints; improves output deliberately. |
| Responsible use | 15% | Protects data and follows policy without prompting. |
| Explanation | 10% | Can explain what the AI did and what they changed. |
Why it is used
For employers
- See how candidates actually work with AI, not just whether they claim to
- Identify people who check AI output before it reaches customers
- Screen for data-handling judgement as AI use spreads
- Find candidates who can help the rest of the team adopt AI well
For candidates
- Show practical AI fluency that a CV line cannot prove
- Use the tools you would use on the job
- Credit for judgement and verification, not only speed
- A clear picture of how the employer expects AI to be used
Common questions
What is an artificial intelligence test?
The term has two meanings. Researchers use it for tests of AI systems, such as the Turing test or model benchmarks. In hiring, an artificial intelligence test or AI skills assessment measures how well a person uses AI tools at work: prompting, checking output, protecting data and building AI into a reliable workflow.
Can candidates use AI during an AI skills assessment?
They should. The point is to watch how they use it. Give them the same kind of tool they would use on the job and score the final work, how they checked it, and how they explain it.
How is AI fluency different from machine learning skills?
AI fluency is using AI tools well in everyday work. Machine learning skills are building and evaluating models, which needs statistics, programming and data engineering. Many roles need the first; only technical AI roles need the second.
How do I prepare for an AI skills test?
Practise giving a tool context, constraints and examples; always check facts and figures against a source; learn your employer's rules on confidential data; and be ready to explain what the tool did and what you changed.
How does Cohesyve evaluate applicants?
Cohesyve builds job simulations from your job description, so the tasks reflect the work of the role you are hiring for, and you receive a ranked shortlist of the applicants who performed best.
Test Artificial Intelligence before the first interview
Cohesyve takes your job description, finds candidates, reaches out to them and tests Artificial Intelligence in an AI job simulation of the real work, then returns a ranked shortlist.
1,500+
assessments completed
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5 min
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No credit card · 10 free candidates · Plans sized to your hiring volume
About to take an Artificial Intelligence test yourself? Practise on an AI job simulation that uses it. 3 free tests, no card.
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