CAI-2 AI Practitioner (HR & People Ops): assessment blueprint

Review and limits. The course content has completed cross-model editorial review. That review is not employment-law advice or a completed legal sign-off. The task descriptions and operational pass rule below describe the configured exam. Domain weights, timings and the pass standard remain provisional: no completed job-task analysis or empirical standard-setting study is claimed.

What CAI-2 HR & People Ops shows

A CAI-2 AI Practitioner (HR & People Ops) credential shows that the holder produced an HR and people-operations professional's AI-assisted work to the exam's published rubric in a time-boxed exam. The tasks ask them to update policies with AI so that the result matches what was approved and meets every stated legal minimum, and explain the change consistently to employees and managers; prepare recruiting materials and screening that are job-related and free of proxies, unlawful questions and AI-made decisions; read people data honestly while protecting anonymity; handle employee-relations drafting and sensitive data with care; and brief, check and refine an AI assistant's work in a recorded conversation.

CAI-2 is performance-based and open-AI-by-design: you earn it by doing realistic HR work with AI in a time-boxed exam, not by recalling facts. It does not test memorized employment law: every legal rule a task needs is stated in its materials, as simplified exercise rules for a fictional US multi-state employer. It is genuinely failable: completing the course does not earn it, and a pasted answer or a single prompt doesn't meet the minimum for your recorded conversation.

CAI-2 builds on the CAI-1 skills (briefing, verification, data handling, decisions about people). CAI-1 is recommended but not required. The credential is not a legal qualification and does not certify knowledge of any jurisdiction's employment law.

Competency domains and weights

| Domain | Weight | A competent candidate can… | | ----------------------------------------------------- | ------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | D1. Policy drafting and change communication | 30% | use AI to draft a policy change from the old policy, the approved brief and stated legal minimums; keep the policy to what was approved; write an employee announcement and manager FAQ that match the policy and cover hard cases; keep a change log with reasons and sources; route open questions to counsel or leadership as specific questions. | | D2. Recruiting and selection | 22.5% | build job ads from a job analysis; remove coded language and unnecessary requirements; meet stated posting rules; build structured interview kits with anchored scoring; screen against published, job-related criteria with evidence; restore human decisions where AI has made them. | | D3. People analytics | 0% | use AI to plan survey and turnover analysis while calculations run in a spreadsheet; compute pooled rates and percentage-point changes correctly; recognize changed-question trends, correlation presented as cause and non-response; re-issue analysis whose claims stay within the evidence, with next steps framed as tests. | | D4. Fairness, employment-law and people-data risk | 32.5% | detect policy clauses below stated minimums and eligibility rules that exclude groups; recognize protected characteristics and proxies; apply the four-fifths rule as a screening heuristic; remove recommendations that treat people differently by a protected characteristic; protect anonymity thresholds and sensitive data; keep confidentiality in employee-relations work; cite the rule behind each finding. | | D5. AI collaboration and workflow | 15% | give an assistant the materials and rules it needs; work in checkable steps; challenge, verify and correct its output; keep personal data out of unapproved tools; keep decisions about people with people; design repeatable workflows with human gates, data rules, records and fairness monitoring. |

The launch exam uses the two configured tasks below, weighted equally. Each domain weight is the mean of its share in those two task rubrics. The broader course includes additional practice; Survey analysis is outside this launch exam.

D3 has 0% direct exam weight under this selection; course coverage is not evidence that this domain is directly tested by these two tasks.

| Domain | Recruiting review | Policy-update package | Mean (exam weight) | | ------ | ----------------- | --------------------- | ------------------ | | D1 | 0 | 60 | 30% | | D2 | 45 | 0 | 22.5% | | D3 | 0 | 0 | 0% | | D4 | 40 | 25 | 32.5% | | D5 | 15 | 15 | 15% | | Total | 100 | 100 | 100% |

Traceability: tasks → criteria → domains

| Task | Criterion (weight within task) | Domain | | ------------------------------ | ---------------------------------------------------------------------------------------------------------------------------- | ------ | | 1. Recruiting materials review | Re-issued job ad (15), Re-issued rubric and questions (20), Shortlist handling keeps decisions human (10) | D2 | | | Detects the planted problems (25), Each finding cites the rule and who it affects (15) | D4 | | | AI-collaboration quality (15) | D5 | | 2. Policy-update package | Corrected policy section (20), Announcement and manager FAQ (20), Change log (10), Open questions go to the right owner (10) | D1 | | | Catches the planted conflicts (25) | D4 | | | AI-collaboration quality (15) | D5 |

Task types

The course and the exam use the same task families (assessment-as-learning).

| Task type | What you do | How it's scored | Main domains | | ------------------------- | ----------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------- | ------------ | | AI practice (sandbox) | Do real HR work with an AI assistant: brief, review, refine, deliver. | Rubric, including the transcript | D1, D2, D5 | | Critique | Find the planted errors, unlawful or biased items and risks in AI output, and justify each against the materials. | Rubric: one checklist item per planted issue, plus corrections and false-alarm avoidance | D1, D3, D4 | | Scenario | Make a sequence of decisions in a realistic HR workflow. | Deterministic, from the quality of each choice (course only) | D1–D5 | | Work product | Produce an attrition memo, an adverse-impact review or a workflow design. | Rubric with 4–7 analytic criteria | D3–D5 |

How you earn CAI-2 HR & People Ops

Pass the CAI-2 HR & People Ops exam. Course completion is recommended, and the module checkpoints (80% mastery threshold, unlimited retakes) are the best rehearsal, but they are not required. Experienced HR professionals can take the exam directly (the challenge path).

The exam

Format: two performance tasks in the browser-based exam workspace, in configured order:
1. Review and re-issue AI-drafted recruiting materials (job ad, screening rubric, interview questions, shortlist note) against a job analysis and stated hiring rules. About 50 minutes.
2. Policy-update package: from an old policy, an approved change brief and counsel's summary of legal minimums, check an AI-drafted policy section and produce the corrected section, an employee announcement, a manager FAQ and a change log. About 55 minutes.
Survey analysis remains additional course practice and a possible later exam family.
Time: a single 3-hour time-boxed window for both tasks. (Provisional; to be confirmed in the beta.)
Task contexts: this exam uses fixed, reviewed task materials and data. Candidates may receive the same company, figures and constraints. Sharing task content is prohibited.
Legal content: all exam materials use a fictional US employer operating in three states called State A, State B and State C. State rules are simplified exercise rules stated in the materials; federal points are simplified exercise rules stated at a general level. The materials have completed cross-model editorial review. That review is not employment-law advice, and no completed employment-law or SME sign-off is claimed.
What's graded: your work products for each task, plus your AI-collaboration transcript for that task.
Integrity: honor-code attestation on submission.

Scoring

Each task is scored against a published-format rubric of 4–7 analytic criteria, including an AI-collaboration quality criterion worth 15% of the task. Each criterion is scored 0–4 against behavioral level descriptions, derived from a checklist of observable features.
Every checklist decision must cite verbatim evidence from your submission or your transcript. Claims your work doesn't support earn no credit.
Rubric scoring. Your answers are scored against the rubric's behavioral level descriptions. Before a task variant is used, the workspace assistant's own answer to it is measured and stored for reference. That stored answer does not decide whether a variant is used.
Criterion scores combine into a weighted composite per task (0–4), and the two task composites are averaged with equal weight.

Pass standard (provisional)

An overall composite of at least 2.5 of 4, with no task below 2.0.
Your recorded conversation with the workspace assistant must also meet a minimum on every task: at least 2.0 of 4 on AI-collaboration quality.
This remains a provisional operational standard. No completed job-task analysis or empirical standard-setting study is claimed. Until both tasks pass their scoring checks, a person reviews every result, so no score releases a result on its own. The award rule above is computed from final authorized scores.

How decisions are made

AI grading uses three separate scoring passes on a fixed, versioned grading configuration. The passes may share a model.
Until both tasks pass their scoring checks, a person reviews every result, pass or fail, before it is released. No credential is issued without that person's decision. The AI grades are an advisory starting score for the reviewer. Any change to this review will be published in this blueprint before it applies. Every credential decision is logged.
Feedback generated by AI is labeled as AI-generated.
Appeals: you can appeal any result. The first appeal on each attempt is free. While Certavant has one human reviewer, an independent AI Model re-grades your work blind and a person countersigns the outcome. The outcome letter says if that person also confirmed the original decision. Appeals are decided within 5 business days.

What has been checked

Editorial review checks the course and task content for accuracy, alignment, accessibility and bias. It does not establish a validated pass standard.
Scoring checks compare the grading configuration with panel-adjudicated scores on fictional responses to the selected task contexts. They measure agreement with those AI-scored references, not agreement with human experts. The scoring checks for this exam are not yet complete, which is why a person decides every result.
Job-task analysis and standard setting remain provisional. The operational pass rule is not an empirical finding about workplace performance; it is reviewed against real submissions after launch.

AI-use policy for the exam

CAI-2 is open-AI-by-design: using AI well is part of the skill being assessed.

You may:

use the AI assistant provided in the exam workspace, as much as the turn limit allows. The limit is shown at the start of the exam;
use a spreadsheet or calculator, your own notes, the course materials and any reference sources.

How your AI use is assessed:

The workspace assistant is the sanctioned AI channel. Every message you send and every reply is recorded server-side, per task, and attached to your submission as a transcript appendix.
The transcript is graded under AI-collaboration quality: whether you supplied the materials and rules, worked in steps, checked and challenged the output, corrected its errors, and made the decisions yourself. It is 15% of each task's score, and it has its own minimum on every task, so each task needs a recorded conversation with the assistant that meets it.
Answers are scored against the rubric, and your recorded conversation must meet the minimum on every task. A pasted answer or a single prompt doesn't meet it.

You may not:

use any AI tool other than the workspace assistant during the exam. You confirm this in the attestation when you submit;
have another person do any part of the work, or share task content with anyone;
paste real employee, candidate or other personal or confidential data into the assistant. The tasks provide all the information you need;
include text intended to influence the grader, such as instructions to the AI grader or hidden text, in your submission or your conversation with the assistant. This is an integrity violation. It results in a fail and can lead to a ban and revocation of any credential.

The course tutor is not available during the exam.

The credential

Verifiable and shareable (Open Badges 3.0), with an "Add to LinkedIn profile" option. Displayed as CAI-2 AI Practitioner (HR & People Ops).
Evidence-embedded: the credential can link to the work you submitted, with privacy settings you control (public, employer-link-only, or hidden).
Stamped with an expiry date at issue (12–18 months; the final term is to be confirmed) and renewable by assessment.

Content freshness

Most of the course and exam measure durable skills (D1–D3, D5) that change slowly. Material on AI screening tools, automated-employment-decision rules and tool features (part of D4) is flagged as short half-life, reviewed regularly, and changes are published in the course changelog. Employment law differs by country, state and city and changes often; the course teaches widely shared principles, names the jurisdiction whenever it states a rule, tells learners to confirm legal points with employment counsel, and the exam materials state every rule a task needs.