Final test & Certificate

Choose the best answer for each question.

To pass: at least 8 of 10 correct.

1. Question 1. What's the core difference between 'AI tool adoption' and 'transformation'?

   AAdoption speeds up the old process; transformation redesigns the process and the rolesBTransformation costs more moneyCAdoption is for small firms, transformation for large groups

2. Question 2. Which three areas need particular caution when using AI in HR?

   ARecruitment screening, performance appraisal and disciplinary decisionsBWriting JDs, drafting emails and summarising meetingsCTraining, internal comms and event organisation

3. Question 3. What are the four HR AI maturity levels, in order?

   AAd hoc → Standardised → Integrated → RedesignedBIntegrated → Ad hoc → Standardised → RedesignedCStandardised → Redesigned → Ad hoc → Integrated

4. Question 4. An organisation at Level 1 (ad hoc) should target what next?

   ALevel 2 — publish guidance, a prompt library and basic trainingBLevel 4 — redesign every processCStop using AI until a new system arrives

5. Question 5. What are the two axes of the AI use-case prioritisation matrix?

   AValue delivered × FeasibilityBCost × Implementation timeCNumber of users × Tool popularity

6. Question 6. Which use case should you start with?

   AHigh value, easy to do, and where many people see the resultBThe most complex project, to prove capabilityCThe highest-risk use case, because it matters most

7. Question 7. What's the right question when redesigning an HR process?

   A'If we redesigned this from scratch WITH today's AI capability, what would it look like?'B'Which step is easiest to bolt an AI tool onto?'C'Which tool is most popular in the market right now?'

8. Question 8. What's the right human–AI division of labour?

   AAI handles volume, summarising and drafting; humans keep judgement, relationships and accountabilityBAI handles all repetitive work and hiring decisions, to remove biasCHumans should double-check AI output only when they have time

9. Question 9. What's the right advice about data?

   ADon't wait for perfect data — many high-value use cases don't need clean internal dataBClean all your data before doing anything at allCData doesn't matter because AI handles it

10. Question 10. When presenting an AI roadmap to leadership, where should you start?

    AFrom a specific business problem, with AI as the means of solving itBFrom a list of the newest AI toolsCFrom global AI trends