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PMI CPMAI Exam Syllabus Topics:

Section	Weight	Objectives
Data for AI		- Data identification and governance 1. Data sourcing and selection 2. Data compliance and ethics
Data Preparation for AI		- Data cleaning and transformation 1. Data quality assurance 2. Feature engineering and preparation
Identify Business Needs and Solutions	26%	- Problem framing and business alignment 1. Define AI business objectives 2. Feasibility and ROI analysis
AI Model Development and Iteration		- Model building and validation 1. Iterative delivery approach 2. Machine learning / generative AI model development
AI Operationalization and Governance		- Deployment and lifecycle management 1. AI governance and responsible AI 2. Continuous improvement and monitoring
AI System Testing and Evaluation		- Model evaluation and monitoring 1. Performance evaluation and drift detection 2. Explainability and reliability assessment

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PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q163-Q168):

NEW QUESTION # 163
You just joined a new company and they want to start their first AI project. Senior management thinks the best approach is to just buy AI from a vendor. You know that AI is something you do, not something you buy. What is your next best course of action to address this?

A. Share prior experiences with how your last team addressed this problem and their data quality issues
B. Say nothing and let the team figure it out for themselves
C. Help senior management do research on AI vendors
D. Share prior experiences with how your last team addressed this problem and how you solved it

Answer: D

Explanation:
Sharing your prior experiences with how your previous team approached AI projects helps educate senior management on the complexities of AI implementation and the importance of doing AI rather than just buying it.

NEW QUESTION # 164
An organization needs a document classification capability. A commercial service already provides this function at acceptable accuracy, while an internal build would take an estimated nine months.
What should the project manager evaluate first?

A. Whether the commercial service can be customized
B. Whether the internal team has the necessary skills
C. Whether the capability represents a competitive differentiator for the organization
D. Whether the commercial service costs less over five years

Answer: C

Explanation:
Build decisions are justified when the capability provides differentiation that a commodity service cannot deliver. If the function is not a differentiator, buying conserves resources for work that creates distinct organizational value.

NEW QUESTION # 165
A project manager is preparing a final report on an AI project. The report must highlight lessons learned, focusing on ethical concerns and compliance with data regulations. In addition, the team has identified multiple ethical issues related to data privacy during the project. What is an effective approach to address the situation for future AI projects?

A. Increase the frequency of compliance audits.
B. Implement a robust ethical data governance framework.
C. Develop a transparent data compliance usage policy.
D. Provide additional training on ethical AI practices.

Answer: B

Explanation:
Implementing a robust ethical data governance framework provides a structured way to manage privacy, compliance, accountability, consent, data usage, and ethical risks across future AI projects. This directly addresses lessons learned from multiple data privacy issues and helps prevent recurrence.

NEW QUESTION # 166
An AI initiative has demonstrated a technically successful model, but the business unit cannot quantify what the improvement is worth.
What was most likely omitted during Business Understanding?

A. A data acquisition plan
B. A stakeholder register
C. Baseline performance measurement of the current process
D. A model selection rationale

Answer: C

Explanation:
Business value is calculated as the difference between the AI-enabled outcome and the existing baseline. Without measuring current process performance before the project, improvements cannot be quantified or attributed to the AI solution.

NEW QUESTION # 167
For AI projects the code and systems don't matter as much as the dat

A. In fact, big data is what's powering much of this latest wave of AI. What's most important for your company to consider around data?
B. Because of almost-infinite storage and compute power, collect as much data as possible and deal with organizing it later.
C. Understanding which algorithms are best for your data needs.
D. Have team members that have experience, understanding of tools, and the ability to deal with massive volumes of data.
E. Collect enormous amounts of data - the more data the better.

Answer: E

NEW QUESTION # 168
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