PMI-ACP Practice Questions #63
Your project management team leverages generative AI to archive lessons learned in a centralized knowledge repository. The AI categorizes insights based on their relevance to project stages.
Which feature of generative AI ensures the repository remains practical and beneficial for future projects?
A. Automatic deletion of older lessons to save storage.
B. Categorization and tagging for easy retrieval of relevant lessons.
C. Generating project plans for upcoming projects.
D. Securing historical lessons to prevent modifications.
Analysis
The question focuses on how generative AI enhances a lessons-learned repository by ensuring that archived insights remain practical and beneficial for future projects. The key capability of AI in this context is to improve knowledge organization, retrieval, and application while maintaining accessibility for future teams. The best answer should emphasize how AI structures lessons learned effectively, rather than deleting, restricting, or misapplying the information.
Analysis of Options
A: Automatic deletion of older lessons to save storage.
This option suggests that AI will automatically remove older lessons, which is incorrect. Lessons learned provide historical insights that can be valuable across multiple projects. While optimizing storage is important, deleting past knowledge limits future teams from accessing critical insights that may still be relevant. AI should facilitate better organization and retrieval, not erase past data.
B: Categorization and tagging for easy retrieval of relevant lessons.
This is the correct option. AI can categorize lessons based on project stages, themes, or topics, making them easier to retrieve when needed. Tagging enables teams to access relevant insights quickly, ensuring that past learnings inform future decisions. This aligns well with AI’s role in knowledge management, where structuring and contextualizing information helps teams learn from past experiences effectively.
C: Generating project plans for upcoming projects.
This option is incorrect because AI should not replace human decision-making in project planning. While AI can suggest relevant insights based on historical data, project planning requires human judgment, stakeholder input, and alignment with business objectives. Lessons learned serve as a reference, but they cannot dictate exact project plans for future work.
D: Securing historical lessons to prevent modifications.
This option is also incorrect. While maintaining data integrity is essential, lessons learned should be adaptable as new insights emerge. AI should support continuous learning and refinement, rather than locking historical data, as some insights may need to be updated or reinterpreted in future contexts.
Conclusion
The correct answer is Option B, as categorization and tagging improve knowledge accessibility, making lessons learned relevant and actionable for future projects. The incorrect options include Option A, which focuses on deleting valuable insights instead of retaining them, Option C, which assumes AI can replace human-driven project planning, and Option D, which prevents adaptability instead of enabling continuous learning.
PMI – ACP Exam Content Outline Mapping
| Domain | Task |
| Leadership | Promote Knowledge Sharing |
Topics Covered:
- Categorization and Tagging: Ensures that lessons learned are organized by relevance to specific project stages, facilitating easy retrieval for future projects.
- Knowledge Organization: AI structures insights effectively, enabling quick access to relevant information when needed.
- Continuous Learning: By organizing and tagging lessons learned, AI supports ongoing knowledge sharing and helps future projects benefit from historical experiences.
- Promoting Knowledge Sharing: Encourages the dissemination of valuable insights across teams, fostering a culture of shared learning.
- Adaptability: AI enables the evolution of insights, making sure lessons learned remain practical and applicable in future project contexts.
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