PMI Certified Professional in Managing AI (PMI-CPMAI日本語版): PMI-CPMAI Exam

"PMI Certified Professional in Managing AI (PMI-CPMAI日本語版)", also known as PMI-CPMAI exam, is a PMI Certification. With the complete collection of questions and answers, iPassleader has assembled to take you through 141 Q&As to your PMI-CPMAI Exam preparation. In the PMI-CPMAI exam resources, you will cover every field and category in PMI Certification Certification helping to ready you for your successful PMI Certification.

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  • Updated on: Jun 18, 2026
  • No. of Questions: 141 Questions & Answers

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  • Updated on: Jun 18, 2026
  • No. of Questions: 141 Questions & Answers

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PMI PMI-CPMAI日本語 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Matching AI with Business Needs (Phase I): This section of the exam measures the skills of a Business Analyst and covers how to evaluate whether AI is the right fit for a specific organizational problem. It focuses on identifying real business needs, checking feasibility, estimating return on investment, and defining a scope that avoids unrealistic expectations. The section ensures that learners can translate business objectives into AI project goals that are clear, achievable, and supported by measurable outcomes.
Topic 2
  • Testing and Evaluating AI Systems (Phase V): This section of the exam measures the skills of an AI Quality Assurance Specialist and covers how to evaluate AI models before deployment. It explains how to test performance, monitor for drift, and confirm that outputs are consistent, explainable, and aligned with project goals. Candidates learn how to validate models responsibly while maintaining transparency and reliability.}
Topic 3
  • Managing Data Preparation Needs for AI Projects (Phase III): This section of the exam measures the skills of a Data Engineer and covers the steps involved in preparing raw data for use in AI models. It outlines the need for quality validation, enrichment techniques, and compliance safeguards to ensure trustworthy inputs. The section reinforces how prepared data contributes to better model performance and stronger project outcomes.
Topic 4
  • Identifying Data Needs for AI Projects (Phase II): This section of the exam measures the skills of a Data Analyst and covers how to determine what data an AI project requires before development begins. It explains the importance of selecting suitable data sources, ensuring compliance with policy requirements, and building the technical foundations needed to store and manage data responsibly. The section prepares candidates to support early data planning so that later AI development is consistent and reliable.
Topic 5
  • The Need for AI Project Management: This section of the exam measures the skills of an AI Project Manager and covers why many AI initiatives fail without the right structure, oversight, and delivery approach. It explains the role of iterative project cycles in reducing risk, managing uncertainty, and ensuring that AI solutions stay aligned with business expectations. It highlights how the CPMAI methodology supports responsible and effective project execution, helping candidates understand how to guide AI projects ethically and successfully from planning to delivery.

Reference: https://www.pmi.org/certifications/ai-project-management-cpmai

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