Abstract

Project Portfolio Management (PPM) occupies a strategic position in organizations, which must select, prioritize, and manage initiatives aligned with their objectives. However, increasing business complexity, uncertainty, resource pressure, and project proliferation make the portfolio manager’s role particularly demanding. Portfolio managers must analyze large volumes of data, anticipate risks, optimize resource allocation, and support strategic decision-making. Faced with these growing responsibilities and information volumes, organizations are increasingly turning to technological solutions capable of supporting, automating, or improving some of these functions, particularly artificial intelligence (AI). The integration of AI into PPM, however, raises challenges that extend beyond technology and may influence its ability to reduce managerial workload. This study explores the contribution of AI to decision-making in project portfolio management and examines how it can support portfolio managers. Following a PRISMA selection process, fifteen publications were retained for a critical literature review examining contributions, limitations, and conditions for successful AI integration into PPM. The analysis examines recurring themes, methodological approaches, proposed solutions, developed tools, points of convergence and divergence, and common limitations. Based on this synthesis, the study proposes an integrated conceptual model linking organizational preconditions, AI capabilities, PPM functions, managerial effects, and human oversight and governance. Practical recommendations are also formulated to help organizations strengthen decision-making capabilities, improve portfolio management processes, and responsibly use AI to support portfolio managers.

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