THE ADOPTION OF ARTIFICIAL INTELLIGENCE IN STRATEGIC PROJECT MANAGEMENT: ENHANCING EFFICIENCY AND DECISION-MAKING

The integration of Artificial Intelligence (AI) into Project Management (PM) represents a paradigm shift from manual oversight to data-driven orchestration. As of 2026, traditional, static methodologies are being superseded by dynamic, AI-augmented frameworks. This research explores the transformative impact of Machine Learning (ML), Natural Language Processing (NLP), and Generative AI across the project lifecycle. Key findings indicate that predictive analytics significantly enhance risk mitigation and resource optimization by identifying bottlenecks before they manifest. Furthermore, AI-driven automation drastically reduces "administrative waste," allowing Project Managers to evolve from technical administrators into strategic leaders. This shift emphasizes high-value activities such as complex problem-solving and stakeholder influence. Moreover, the research highlights that AI serves as a powerful objective filter, neutralizing human cognitive biases like the "Planning Fallacy." By leveraging real-time data ingestion, organizations can pivot strategies instantly, ensuring long-term fiscal sustainability. These systems facilitate "Agentic Workflows," where autonomous scripts handle routine rescheduling and vendor communications, maximizing operational velocity. The study also delves into the necessity of data hygiene, asserting that the efficacy of these tools is strictly tethered to the quality of an organization’s historical data architecture. As AI matures, the development of "Explainable AI" (XAI) becomes a focal point for institutional trust, ensuring that algorithmic decisions are transparent and auditable by executive leadership. However, the study concludes that despite these technological advancements, the human element remains indispensable. Human intervention is critical for maintaining ethical governance, navigating complex organizational politics, and fostering emotional intelligence—nuanced areas where AI currently lacks depth.This evolution demands a new curriculum for MBA students, focusing on "Human-AI Collaboration" as a core competency.