PMI

PMI Certified Professional in Managing AI (PMI-CPMAI)

PMI-CPMAI

The PMI Certified Professional in Managing AI (PMI-CPMAI) certification validates your ability to lead AI-driven projects and initiatives with confidence. Designed for project professionals, it equips you to navigate the unique challenges of AI, from defining use cases to managing data, models, and ethical considerations. Earning it demonstrates you can bridge the gap between technical AI teams and business goals, ensuring responsible and successful AI adoption.

Practice Free Questions

5Domains

37Objectives

222Practice pages

1035Free questions

PMI-CPMAI free practice questions

Choose any objective and open any question page — no sign-in required.

Oversee privacy and security plan

29 questions · 6 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–29

Manage AI/ML transparency (e.g., data selection, algorithm selection)

34 questions · 7 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–34

Conduct bias checks (e.g., model, data, algorithm)

22 questions · 5 pages

Questions 1–5 6–10 11–15 16–20 21–22

Monitor regulatory and policy compliance

31 questions · 7 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–31

Manage accountability documentation and audit trail

29 questions · 6 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–29

Identify problem to be solved (e.g., needs, persona)

31 questions · 7 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–31

Evaluate initial AI feasibility

24 questions · 5 pages

Questions 1–5 6–10 11–15 16–20 21–24

Conduct risk assessment(s) (e.g., security, safety, ethics)

30 questions · 6 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30

Develop AI project scope statement

27 questions · 6 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–27

Determine ROI

20 questions · 4 pages

Questions 1–5 6–10 11–15 16–20

Manage adoption/integration risks

24 questions · 5 pages

Questions 1–5 6–10 11–15 16–20 21–24

Draft AI solution

21 questions · 5 pages

Questions 1–5 6–10 11–15 16–20 21–21

Define success criteria (e.g., KPIs, metrics)

25 questions · 5 pages

Questions 1–5 6–10 11–15 16–20 21–25

Support business case creation

31 questions · 7 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–31

Identify project resources (e.g., people, hardware, contractors)

34 questions · 7 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–34

Define required data

33 questions · 7 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–33

Identify data SMEs

26 questions · 6 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–26

Identify data sources and locations

27 questions · 6 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–27

Coordinate AI workspace and infrastructure

29 questions · 6 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–29

Gather required data

24 questions · 5 pages

Questions 1–5 6–10 11–15 16–20 21–24

Check data privacy, compliance, and access

29 questions · 6 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–29

Oversee data evaluation

25 questions · 5 pages

Questions 1–5 6–10 11–15 16–20 21–25

Determine if data meets solution needs

24 questions · 5 pages

Questions 1–5 6–10 11–15 16–20 21–24

Convey data understanding to leadership

32 questions · 7 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–32

Oversee AI/ML model technique(s) (e.g., algorithm, selection)

29 questions · 6 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–29

Oversee AI/ML model QA/QC (e.g., configuration management, model performance)

33 questions · 7 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–33

Manage AI/ML model training

36 questions · 8 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–35 36–36

Manage data transformation to conduct data preparation

36 questions · 8 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–35 36–36

Verify data quality for go/no-go decision to conduct data preparation

25 questions · 5 pages

Questions 1–5 6–10 11–15 16–20 21–25

Verify model ready for operationalization go/no-go decision

21 questions · 5 pages

Questions 1–5 6–10 11–15 16–20 21–21

Manage creation of AI solution deployment plan

37 questions · 8 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–35 36–37

Manage AI solution deployment

27 questions · 6 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–27

Oversee model governance

34 questions · 7 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–34

Oversee AI solution metrics (e.g., KPI, model performance)

22 questions · 5 pages

Questions 1–5 6–10 11–15 16–20 21–22

Prepare final report/lessons learned

32 questions · 7 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–30 31–32

Manage AI solution transition plan

28 questions · 6 pages

Questions 1–5 6–10 11–15 16–20 21–25 26–28

Oversee AI solution contingency plan

14 questions · 3 pages

Questions 1–5 6–10 11–14

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Percentages reflect share of the current practice bank, not official exam weightings. Every page above is a live, crawlable practice page (37 objectives · 222 pages).

PMI Certified Professional in Managing AI (PMI-CPMAI)

PMI-CPMAI free practice questions

Domain 1 · Support Responsible and Trustworthy AI Efforts14% of practice bank · 5 objectives · 145 questions14%

Domain 2 · Identify Business Needs and Solutions26% of practice bank · 10 objectives · 267 questions26%

Domain 3 · Identify Data Needs24% of practice bank · 9 objectives · 249 questions24%

Domain 4 · Manage AI Model Development and Evaluation17% of practice bank · 6 objectives · 180 questions17%

Domain 5 · Operationalize AI Solution19% of practice bank · 7 objectives · 194 questions19%