Free PMI-CPMAI Practice Test Questions 2026

A company plans to operationalize an AI solution. The project manager needs to ensure model performance is meeting selected thresholds before release.

What is an effective way to confirm these thresholds before this release?

A. Testing against validation datasets

B. Implementing an impact evaluation

C. Running multiple end-user acceptance tests

D. Conducting a series of penetration tests

An AI project team has prepared the data and is ready to proceed with model development.

Which action should the project manager perform next?

A. Conduct a final assessment of the data quality

B. Document the performance metrics for the model

C. Ensure go/no-go questions have well-defined answers

D. Prepare a report on the model's scalability

A hospital system has been using a chatbot and has received complaints from end users. The end users believe they are speaking to a person but are frustrated when answers do not make sense.

To help ensure end users know that they are engaging with an AI chatbot, what should be considered to support transparency?

A. Inclusion of diverse data sets

B. Operationalize advanced algorithms

C. Disclosure notice with each use

D. Use of interpretable AI models

In an IT services firm, the AI project team is tasked with developing a virtual assistant to support customer service operations. The assistant must integrate seamlessly with existing customer relationship management (CRM) systems and handle a variety of customer queries.

Which necessary initial task should the project manager take?

A. Building a dedicated data lake

B. Conducting a comprehensive data audit

C. Designing a custom AI algorithm that enhances the chatbot's capacity

D. Procuring advanced natural language processing (NLP) libraries

A company is evaluating whether to implement AI for a project. They have defined their business objectives and determined the AI capability they want to use.

Which action will enable the project manager to move forward with the project?

A. Implementing a preliminary version of the AI solution

B. Identifying the contingency procedures

C. Conducting a go/no-go assessment

D. Conducting a data quality assessment

An AI team is defining success criteria for a customer support chatbot. Leadership wants to approve the project but needs objective measures that reflect both business value and risk. Which set of metrics is most appropriate?

A. Response time only

B. User satisfaction, containment rate, escalation accuracy, and privacy/compliance incidents

C. Number of features delivered

D. Lines of code written

A telecommunications company is considering an AI solution to improve customer service through automated chatbots. The project team is assessing the feasibility of the AI solution by examining its potential scalability and effectiveness.

What will present the highest risk to the company?

A. The team may lack experience implementing AI-based customer service solutions

B. The solution may not handle the volume of customer queries effectively

C. The chatbot may not integrate well with existing customer service platforms

D. The solution might breach customer data privacy regulations, leading to legal consequences

A manufacturing company is implementing an AI system to optimize production schedules. The project manager needs to gather the required data from machine sensors, production logs, and supply chain databases. During data collection, they notice discrepancies in machine sensor data.

What should the project manager do first?

A. Develop a data integration framework to harmonize formats.

B. Outsource data preprocessing to an external vendor.

C. Replace machine sensors for real-time data accuracy.

D. Implement a robust data validation and correction process.

An IT services company is verifying data quality for an AI project aimed at predicting server downtimes. The project manager needs to decide whether to proceed with data preparation.

Which technique should the project manager use?

A. Data augmentation strategies

B. Advanced data labeling methods

C. Detailed cost-benefit analysis

D. Exploratory data analysis (EDA)

An IT services company is developing an AI system to automate network security monitoring. The project manager needs to consider various factors to mitigate risks associated with false positives and false negatives.

Which action should the project manager implement?

A. Operationalizing the nearest neighbor detection algorithms

B. Conducting model combinations and trade-offs

C. Implementing a robust data security validation process

D. Establishing a continuous feedback loop with security

A project manager is tasked with explaining the AI model's decision-making process to the board of directors. The board members are nontechnical and require a comprehensible explanation to help ensure the model's decisions align with business objectives.

Which action should the project manager take?

A. Use confusion matrices to demonstrate true positives, false positives, and overall model accuracy.

B. Illustrate the decision pathway using LIME (local interpretable model-agnostic explanations) for localized interpretability.

C. Show how precision-recall trade-offs influence decision outcomes.

D. Present the model’s ROC (receiver operating characteristic) curve and discuss the optimal threshold for decision making.

A healthcare provider plans to deploy an AI system to predict patient readmissions. The project manager needs to conduct a risk assessment to ensure patient safety and data integrity. What is an effective method to help ensure the AI system adheres to ethical standards?

A. Implementing a data encryption protocol

B. Using an explainability framework

C. Performing continuous monitoring and auditing

D. Conducting a stakeholder impact analysis