Manage AI Solution Deployment PMI-CPMAI Practice Questions (Page 2)

Questions 6–10

1. 6expert · hard

   A retail company has deployed a new AI inventory management system. The system is expected to reduce stockouts. The project manager needs to verify that the system is stable and that it meets the business objectives. The company has a policy of continuous improvement. The project manager has limited resources. What is the most effective way to conduct post-deployment verification?

   • ACompare the system's inventory predictions with actual sales data for a week.
   • BMonitor key performance indicators such as stockout rate and system uptime, and collect user feedback.
   • CConduct a one-time user survey to gauge satisfaction.
   • DReview the system's code for potential bugs.
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2. 7application · medium

   An AI deployment team is in the middle of rolling out a new predictive maintenance system. The project manager is tracking progress against milestones. The team has completed the model integration but has not yet started performance testing. The go-live date is in three days. What should the project manager do?

   • AImmediately escalate the delay to the project sponsor.
   • BAsk the team to work overtime to complete performance testing.
   • CSkip performance testing to meet the go-live date.
   • DReview the deployment plan to identify any tasks that can be compressed or run in parallel.
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4. 8expert · hard

   A manufacturing company has deployed an AI system to predict equipment failures. The system is critical for maintenance planning. The project manager needs to verify that the system is stable and that maintenance engineers accept it. The engineers have reported that the system sometimes gives false alarms. The project manager has limited time and budget. What is the most effective way to conduct post-deployment verification?

   • AConduct a comprehensive user acceptance test with all engineers.
   • BMonitor the system's prediction accuracy against actual failures and collect engineer feedback.
   • CReview the system's uptime and error logs.
   • DCompare the system's predictions with historical maintenance records.
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5. 9application · medium

   A global company is deploying an AI model that will be used by teams in different time zones. The deployment involves multiple technical teams, including data engineering, security, and operations. The project manager needs to ensure that all teams are aligned and that security requirements are met. What is the most important thing to establish early in the deployment planning?

   • AA detailed technical specification of the AI model's architecture.
   • BA communication plan that defines how and when teams will share updates and escalate issues.
   • CA budget for the deployment project.
   • DA list of all security policies that must be enforced.
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6. 10expert · hard

   A multinational bank is deploying a new AI anti-money-laundering system. The deployment involves teams in three countries: data science (model development), IT operations (infrastructure), and compliance (regulatory approval). The compliance team requires a formal validation of the system's performance before go-live. The IT operations team wants to minimize downtime during the rollout. The data science team is concerned about model drift after deployment. The project manager has limited budget for additional tools. What is the most effective way to coordinate the deployment?

   • AEstablish a cross-functional deployment team with clear roles, a shared timeline, and regular status meetings.
   • BLet each team manage its own deployment tasks independently to avoid delays.
   • CUse a single communication channel for all updates to simplify coordination.
   • DPrioritize the IT operations team's schedule to minimize downtime, and defer compliance validation.
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