CAI-2 AI Practitioner (Sales): assessment blueprint

Review and limits. The course content has completed cross-model editorial review. 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 Sales shows

A CAI-2 AI Practitioner (Sales) credential shows that the holder produced a B2B seller's AI-assisted work to the exam's published rubric in a time-boxed exam. The tasks ask them to research accounts and contacts with AI without letting invented events, outdated figures or the wrong person into their plans; write outreach that is relevant without being intrusive and follows the stated outreach rules; turn calls into accurate CRM records and honest follow-ups; keep proposals within what the business has approved; forecast with honest numbers; 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 sales work with AI in a time-boxed exam, not by recalling facts. 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). CAI-1 is recommended but not required.

Competency domains and weights

| Domain | Weight | A competent candidate can… | | -------------------------------------------------- | ------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | D1. Account research and planning | 18% | use AI to research accounts from public material while separating sourced, current facts from invented events, outdated figures and wrong-company or departed contacts; build an account plan with a sourced trigger, a value hypothesis tied to generally available capabilities, a realistic stakeholder map and a research-verification appendix. | | D2. Sales communication | 34% | brief AI for outreach sequences whose touches have distinct purposes and honest framing; personalize from professional, sourced information only; write accurate, field-based CRM summaries and follow-ups that correct over-promises; report forecasts clearly. | | D3. Pipeline analysis and forecasting | 0% | use AI to plan pipeline analysis while calculations run in a spreadsheet; distinguish naive, stage-weighted and judged forecasts; pool win rates correctly and treat small samples as such; find stale, slipped and inflated deals; make an honest Commit and Best case call, neither inflated nor sandbagged, and check AI-generated forecast figures. | | D4. Commitments, claims, consent and data risk | 33% | keep capabilities, prices, discounts, roadmap statements and contract terms within what is approved, escalating to the right owner with a specific question; make fair, checkable competitor comparisons; apply stated outreach rules (corporate and individual contacts, opt-outs, suppression, call screening); keep customer, recording and third-party confidential information in the right tools and records. | | D5. AI collaboration and workflow | 15% | give an assistant the materials, rules and constraints it needs; work in checkable steps; challenge, verify and correct its output; keep decisions human; design repeatable sales workflows with human gates and records. |

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; Pipeline review and forecast 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 | Account plan and outreach | Call to CRM summary and proposal | Mean (exam weight) | | ------ | ------------------------- | -------------------------------- | ------------------ | | D1 | 36 | 0 | 18% | | D2 | 34 | 34 | 34% | | D3 | 0 | 0 | 0% | | D4 | 15 | 51 | 33% | | D5 | 15 | 15 | 15% | | Total | 100 | 100 | 100% |

Traceability: tasks → criteria → domains

| Task | Criterion (weight within task) | Domain | | ------------------------------------- | --------------------------------------------------------------------------------------------------------------- | ------ | | 1. Account plan and outreach sequence | Research reliability (20), Account plan (16) | D1 | | | Outreach sequence (22), Personalization is relevant and appropriate (12) | D2 | | | Outreach rules and suppression (15) | D4 | | | AI-collaboration quality (15) | D5 | | 2. Call to CRM summary and proposal | CRM summary is accurate (20), Follow-up corrects and confirms (14) | D2 | | | Detects the proposal misstatements (20), Corrected proposal section (16), Escalation to deal desk or legal (15) | 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 sales work with an AI assistant: research, outreach, CRM summaries, follow-ups. | Rubric, including the transcript | D1, D2, D5 | | Critique | Find the planted errors, unsupported claims 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–D4 | | Scenario | Make a sequence of decisions in a realistic sales workflow. | Deterministic, from the quality of each choice (course only) | D1–D5 | | Work product | Produce a corrected proposal section, a forecast memo or a workflow design. | Rubric with 4–7 analytic criteria | D3–D5 |

How you earn CAI-2 Sales

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

The exam

Format: two performance tasks in the browser-based exam workspace, in configured order:
1. Account plan and four-touch outreach sequence from a target-account dossier, with a research-verification appendix and a compliance note. About 55 minutes.
2. From a call transcript: a CRM summary, a follow-up email, and a corrected proposal section that misstates capabilities, pricing or terms, with an escalation note. About 50 minutes.
Pipeline review and forecast 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.
Rules in the materials: outreach policies, approval matrices and forecasting rules are stated in each task. The exam does not test recall of any country's law.
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. On this exam 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.
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. 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. Not every task in this exam has passed these checks, 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, rules and constraints, 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 customer, prospect, CRM or personal 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 (Sales).
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 note-takers and call recording (part of D4) is flagged as short half-life, reviewed regularly, and changes are published in the course changelog. Rules on electronic marketing, calls, call recording, data protection and comparative claims differ between markets and change over time (UK guidance on business-to-business marketing is under review at the time of writing); the course teaches widely shared principles with named UK and US examples, and the exam materials state every rule a task needs.