AI and ML for Software Product Management: A Framework for Emerging Challenges

Abstract

In the rapidly evolving landscape of software product management (SPM), the integration of artificial intelligence (AI) and machine learning (ML) presents both unprecedented opportunities and significant challenges. This thesis investigates the impact of AI and ML on SPM practices and develops a comprehensive framework tailored to address the emerging needs of this dynamic field. Utilizing a mixedmethod approach, the study first conducts a systematic literature review to identify the current utilization and challenges of AI and ML within SPM. This is followed by empirical data collection through interviews with professionals in the field, ensuring a robust foundation for framework development. The research findings reveal that while AI and ML can significantly enhance decision-making and efficiency in SPM, they also introduce complexities related to integration, ethics, and management. In response, this thesis proposes a novel SPM framework that incorporates how SPM should use AI and ML components and tools effectively, focusing on enhancing SPM and aligning with digital transformation and digitalization goals. The framework is validated through a workshop and an interview with experts in the field. This study aims to bridge a crucial gap in academic literature and to also offer practical insights for individuals and organizations aiming to leverage AI and ML for enhanced SPM strategies, ensuring both competitive advantage and alignment with evolving technological landscapes.