Build the foundations
Understand AI capabilities and limitations, then identify a specific business workflow.
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Connect AI adoption to a measurable business problem.
Understand AI capabilities and limitations, then identify a specific business workflow.
Assess data readiness, costs, risks and alternatives; define measurable pilot criteria.
Design governance, human review and adoption support with named owners.
Present a pilot decision with evidence, limitations and a plan for monitoring business outcomes.
Your checklist stays in this page session only. It is a self-check, not a skills assessment.
Pick one credential that matches the technology in your target vacancies. Check prerequisites and prove the skills with a project before booking.
For decision-makers leading AI adoption and organisational change in the Microsoft ecosystem.
Before booking: Best with experience making business decisions and guiding organisational change; coding is not required.
For leading AI projects from a business need through delivery.
Before booking: A useful route for project leaders moving into AI initiatives.
A cross-platform specialisation for people governing AI systems and connecting technical decisions with organisational responsibilities.
Before booking: Useful after exposure to AI, privacy, compliance, risk or governance work.
Review the official source for fees, assessment format, prerequisites and award/renewal requirements. Guidance reviewed 13 September 2026.
Write an AI pilot proposal with baseline measures, data checks, risk controls, adoption plan and go/no-go criteria.
Use these original practice scenarios to structure your answers. They are not leaked exam questions or an employer’s interview script.
A strong answer covers: Compare business value, feasibility, data readiness, risk and a simpler non-AI alternative.
A strong answer covers: Investigate workflow fit, trust, training and incentives, then measure adoption and task outcomes.