Outlet Title

Issues in Information Systems

Document Type

Article

Publication Date

2026

Abstract

AI-enabled tools are increasingly embedded in project environments, introducing privacy risks that remain conceptually underdeveloped as a structured risk domain. Although research examines AI applications in project management, the treatment of privacy risk within AI-enabled projects remains fragmented. This study conducts a systematic literature review of seventeen studies to critically map the conceptual gaps in privacy risk management across AI-enabled project contexts. Following established SLR guidelines, the review analyzes the literature through the lens of PMBOK® Guide’s Risk Performance Domain and Contingency Theory to examine how AI-related privacy risks are conceptualized and integrated across predictive, adaptive, and hybrid project lifecycles. The findings reveal that current AI implementation research is structurally blind to project lifecycle governance, with fifteen of seventeen studies failing to link privacy risk to any lifecycle structure. The study introduces the APRIL framework (AI Privacy Risk Integration Across Project Lifecycles) as a proposed governance architecture to address this gap and outlines directions for future empirical research.

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