AI-Enabled Analytics for Product Management: Trends, Methods, and Research Gaps

Abstract

Artificial intelligence (AI) is revolutionizing product management because it supports product lifecycle data-driven, predictive, and prescriptive analytics. The current review critically looks at applications, processes, and new trends in product management through machine learning, deep learning, reinforcement learning, and natural language processing uses of AI. Applications Product discovery, feature prioritization, pricing optimization, user engagement analysis, and lifecycle monitoring are the key applications. Although AI can improve decision-making, there are still issues of data quality, model explain ability, ethics and preparedness of the organization. The research reveals gaps in the study as understudied methods of AI, longitudinal validation, human-AI cooperation, and standardization. The focus on these aspects can develop practice and scholarly work in AI-based product management.