2026 PMI CPMAI: First-grade Cognitive Project Management in AI (PMI-CPMAI) Test Questions

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PMI CPMAI Exam Syllabus Topics:

SectionWeightObjectives
AI System Testing and Evaluation- Model evaluation and monitoring
  • 1. Explainability and reliability assessment
    • 2. Performance evaluation and drift detection
      Data for AI- Data identification and governance
      • 1. Data compliance and ethics
        • 2. Data sourcing and selection
          AI Operationalization and Governance- Deployment and lifecycle management
          • 1. AI governance and responsible AI
            • 2. Continuous improvement and monitoring
              Data Preparation for AI- Data cleaning and transformation
              • 1. Data quality assurance
                • 2. Feature engineering and preparation
                  Identify Business Needs and Solutions26%- 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

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                          PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q183-Q188):

                          NEW QUESTION # 183
                          A fintech AI project uses third-party data sources for credit risk modeling. The project manager is concerned about compliance and accountability if the external data quality changes. Which control best supports responsible and trustworthy AI delivery?

                          Answer: D

                          Explanation:
                          PMI's trustworthy AI framing highlights governance, transparency, and accountability as essential ingredients for systems people can interpret and monitor. When third-party data feeds can change, the PMI-aligned approach is to establish governance and supplier controls that define data quality expectations, lineage, permitted uses, privacy constraints, and monitoring/audit mechanisms. This supports accountability by making data dependencies explicit and enabling early detection when upstream changes degrade model behavior.


                          NEW QUESTION # 184
                          A project manager is leading a complex project for a global financial institution. The project is developing an AI-driven system for real-time fraud detection and risk management. The system needs to adhere to all financial regulations. The project manager has identified skills gaps with the existing available resources. What should the project manager do?

                          Answer: A

                          Explanation:
                          Engaging consultants helps fill immediate expertise gaps in a complex, regulated AI project where specialized knowledge in fraud detection, risk management, AI implementation, and financial compliance is required to proceed effectively.


                          NEW QUESTION # 185
                          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?

                          Answer: B

                          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 # 186
                          In a complex healthcare project, a provider plans to implement AI for patient data analysis to improve diagnostic accuracy. The project involves the need for interoperability between the AI systems and existing healthcare databases. These databases contain sensitive patient information. The requirements involve strict ethical and legal regulations in various countries.
                          Which critical step must be performed?

                          Answer: D

                          Explanation:
                          Implementing privacy impact assessments is critical because the project involves sensitive patient data, interoperability with healthcare databases, and legal and ethical obligations across multiple countries. This helps identify privacy risks, compliance requirements, and safeguards before the AI system is implemented.


                          NEW QUESTION # 187
                          In what way would you be using Generative AI if you used the results of the Generative AI solution to improve and accelerate your job?

                          Answer: C


                          NEW QUESTION # 188
                          ......

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