Master of Public Administration for Senior Leadership

Date

5-2026

Document Type

Capstone

Degree Name

Master’s in Project Management

Department

School of Professional Studies

Chief Instructor

Mary M. Piecewicz, MBA, MSPC, PMP

Keywords

risk, non profit, community based, emerging risks, AI, continous risk monitoring

Abstract

Nonprofit and community-based organizations operate in complex and resource-limited environments where effective project performance is critical to achieving social impact, optimizing limited budgets, and offering value to the communities they serve. Despite the significance of proactive risk management, many nonprofits continue to rely on manual, periodic, and reactive risk management practices that limit their ability to identify emerging risks quickly and react effectively during project implementation. These limitations frequently contribute to schedule delays, cost overruns, inefficiencies, and reduced project outcomes.

Advances in artificial intelligence (AI) present a chance to improve traditional risk management practices by permitting continuous risk monitoring, early risk detection, and data-informed decision-making. While AI-enabled risk monitoring has demonstrated potential in other sectors, its adoption and effectiveness within nonprofit and community-based projects remain limited and under-explored. This project is designed to examine how the use of AI for continuous risk monitoring may influence project performance in nonprofit and community-based organizations.

The primary business driver for this project is the need to improve project performance and reduce avoidable project failures in nonprofit settings by strengthening risk visibility and decision-making procedures. By investigating AI-based continuous risk monitoring, this study intends to identify opportunities to improve project governance, reduce risks proactively, and support more effective and effective project delivery in nonprofit and community-based environments.

Worcester

No

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