Download Cognitive project management in AI.CPMAI.ExamTopics.2026-09-25.212q.vcex
| Vendor: | PMI |
| Exam Code: | CPMAI |
| Exam Name: | Cognitive project management in AI |
| Date: | Sep 25, 2026 |
| File Size: | 1 MB |
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Demo Questions
Question 1
A healthcare organization is developing an Al model to predict patient outcomes. The project manager needs to address issues of missing or incorrect data before training the model.
What is an effective method to help ensure data quality?
- Performing systematic data validation
- Enhancing with data augmentation techniques
- Implementing an AI data needs assessment
- Applying predictive data algorithms
Correct answer: A
Question 2
In an aerospace manufacturing project, engineers are preparing data to train an AI system for predictive maintenance. They need to transform the data from multiple sensors and ensure it is consistent and accurate before building the model.
What should the project manager do to handle the inconsistencies?
- Use data augmentation techniques to fill the gaps.
- Enhance the current data with additional sources.
- Identify and reconcile conflicting data points.
- Implement a validation protocol for sensor data.
Correct answer: C
Question 3
A financial services firm is building an AI model to detect fraudulent transactions. Identifying and validating data sources is critical to the model’s success.
What is an effective method that helps to ensure data accuracy?
- Utilizing data lineage tools to track data origin and transformations
- Employing a federated database system for decentralized data access
- Setting up a batch processing system for data cleansing
- Implementing a blockchain-based ledger for transaction data
Correct answer: A
Question 4
A telecommunications company is preparing data for an AI tool. The project team needs to ensure the data is in the right shape and format for model training. In addition, they are working with a mix of structured and unstructured data.
Which method will address the project team’s objectives?
- Separating structured and unstructured data into different databases
- Converting unstructured data into structured formats
- Using a hybrid storage system for both data types
- Employing a data transformation tool to standardize formats
Correct answer: D
Question 5
A project involves integrating AI systems across multiple departments, each with different access levels. This complex Al project has presented the project manager with significant issues related to data misuse. The project team has been focused on their ethics guidelines but continues to experience data misuse. The project involves different regional data protection regulations which further increases the complexity.
What issue will cause these challenges to occur?
- Lack of a detailed plan addressing a governance strategy
- Limited awareness of explainability requirements
- Overlooking algorithmic bias and fairness concerns
- Failure to implement robust encryption for data security
Correct answer: A
Question 6
A transportation company is preparing data for an AI model to optimize fleet management. The project team is working with large amounts of structured and unstructured data.
If the project manager avoids addressing the variety of data during preparation, what will be the result?
- Decreased data processing speed
- Increased data consistency
- Reduced model performance
- Improved model accuracy
Correct answer: C
Question 7
An organization is planning their digital transformation initiatives by building an AI solution to focus on data-collection needs. The goal is to reduce the manual handling of data.
Which approach should be prioritized to achieve the objective?
- Upgrading cloud storage solutions for better data management
- Enhancing the current database infrastructure to handle larger volumes of data
- Outsourcing data-processing tasks to third-party vendors
- Implementing intelligent systems that can autonomously process and analyze data
Correct answer: D
Question 8
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?
- Engage consultants to fill the expertise gap.
- Allocate additional budget for consultant AI training.
- Proceed with the project until external expertise is needed.
- Delay the project until internal expertise is developed.
Correct answer: A
Question 9
A company needs to launch an AI application quickly to be the first to the market. The project team has decided to use pretrained models for their current AI project iteration.
What is a key result of leveraging pretrained models?
- The project can face unexpected scalability challenges.
- The custom project development time can increase due to adjustments.
- The team can see a reduction in the overall project timeline.
- The team can encounter compatibility issues with existing systems.
Correct answer: C
Question 10
A healthcare provider is operationalizing an AI tool to assist in diagnostic processes. To ensure robust model governance, they need to address data privacy and ethical considerations.
What should the project manager do?
- Set up a continuous CUE review process.
- Develop a detailed privacy impact assessment (PIA).
- Implement a multi-tiered DCA framework.
- Establish a comprehensive DPMS protocol.
Correct answer: B
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