Purpose: This paper analyzes key factors influencing AI project management, drawing on case studies, industry reports, and scholarly literature. It investigates the motivations behind AI adoption, the challenges encountered during implementation, and the outcomes of AIdriven initiatives. By reviewing existing literature on AI project management, analyzing case studies of successful and unsuccessful AI implementations, and identifying emerging trends and best practices, the paper aims to provide a comprehensive understanding of AI project management. This will empower organizations to make informed decisions and maximize the potential of AI technology. The insights gained will offer guidance to project managers, business leaders, and policymakers on harnessing AI's power while mitigating risks, AI isn’t neutral, it reflects the biases inherent in its training data. How do project managers navigate ethical dilemmas related to AI decision-making? We’ll address fairness, transparency, and accountability. Methodology/approach: The case studies were prepared from the documents stored in the companies' databases, and an attempt was made to collect the information comprehensively and analyze it. Data are analyzed utilizing inductive and deductive qualitative content analysis. The resulting categories are considered communicational core messages and are included in the developed change story. Findings: The analysis of the provided texts highlights the critical intersection of artificial intelligence (AI) and project management, emphasizing the unique challenges and strategies necessary for successful AI implementation within organizations. Both case studies, focusing on Spotify and Hansab, illustrate how AI can transform traditional processes and enhance operational efficiency.