PMI-CPMAI practice question 19 of 25

An AI project team is assessing the scalability of a healthcare solution. Which factor should the project manager consider to help ensure the solution is scalable?

Full set: 102 questions
Answer options
A: Compliance with data regulations
B: Ability to handle increased loads Correct answer
C: Human oversight requirements
D: Integration with the existing infrastructure
Correct Answer:
B. Ability to handle increased loads
Explanation

Scalability is a fundamental non-functional requirement in system design, particularly for AI solutions that often process large and growing datasets. It refers to the system's ability to handle an increasing amount of work—or its potential to be enlarged to accommodate that growth—without a corresponding degradation in performance. In the context of a healthcare AI solution, this means ensuring the system can effectively manage a rising number of patients, larger data volumes, and more concurrent user requests as the service expands. The project manager must prioritize this factor to ensure long-term viability and performance.

Why Incorrect

A. Compliance with data regulations is a critical legal and ethical requirement, but it is distinct from the system's technical ability to handle increased load.
C. Human oversight requirements are a governance and safety consideration, not a direct measure of the system's performance capacity or its ability to scale.
D. Integration with the existing infrastructure addresses interoperability and implementation feasibility, not the solution's inherent capacity to grow and manage a heavier workload.

References

1. Kleppmann, M. (2017). Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. O'Reilly Media. In Chapter 1, "Reliable, Scalable, and Maintainable Applications," scalability is explicitly defined as a system's ability to cope with increased load, which is described in terms of parameters like requests per second, data volume, or number of active users (pp. 4-6).

2. Zaharia, M., et al. (2016). CS229T/STAT231: Statistical Learning Theory. Stanford University Courseware. Lecture notes on "Scalable Machine Learning" consistently frame scalability around the challenge of handling large datasets ("large n") and high-dimensional data ("large p"), directly linking it to load and performance.

3. Project Management Institute. (2021). The Standard for Project Management and A Guide to the Project Management Body of Knowledge (PMBOK® Guide) – Seventh Edition. The Delivery Performance Domain emphasizes that "projects deliver outcomes that have nonfunctional requirements," including performance and scalability, which are essential for the solution's operational success (Section 2.4.4, p. 78).

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