Project Risk Management in AI-Enabled Systems: Managing Ethical, Privacy, and Governance Risks

Author

Onome Cynthia Anakanire, Harrisburg University of Science and TechnologyFollow

Completion Date

2-7-2026

Document Type

Thesis

Degree Name

Master of Science (MS)

Program or Discipline Name

Project Management

First Advisor

Dr. Tedd Wheeler, Ph.D.

Abstract

This research examined how Artificial intelligence (AI) has been embedded in project-based work, particularly in finance and software industries, where it enables efficiency and assists in complex decision-making. However, these innovations introduce significant ethical, privacy, and governance risks that traditional project risk management frameworks fail to adequately address. This study investigated how project managers can systematically integrate the management of these emerging risks into AI-enabled projects. Using a qualitative research design, the study drew on semi-structured interviews with project managers, compliance officers, and AI developers in finance, software and related sectors. Supplementary data included internal project documentation and risk registers. Data were coded and analysed using grounded theory techniques to surface themes related to risk perception, mitigation strategies, and governance structures. The research found that while project teams are aware of ethical and privacy risks, formal methods to manage them are inconsistent or underdeveloped. Participants noted the absence of clear AI-specific risk categories in existing project tools. The study identified ten major themes, amongst which are lack of bias auditing, uncertainty in regulatory compliance, underutilization of AI-specific standards, and the need for clearer accountability structures. The study concluded by proposing a conceptual framework that extends traditional project risk management by integrating ethical, privacy, and governance components across the project lifecycle. The framework has practical relevance for project managers seeking to ensure AI adoption aligns with stakeholder expectations and evolving legal standards. It also contributes to bridging the gap between AI governance and everyday project practice.

Recommended Citation

Anakanire, O. C. (2026). Project Risk Management in AI-Enabled Systems: Managing Ethical, Privacy, and Governance Risks. Retrieved from https://digitalcommons.harrisburgu.edu/dandt/90