With the surge of AI applications in the fitness industry, AI-powered fitness apps that provide personalized features are emerging as popular tools for exercisers. One such feature is the personalized workout plan, which uses specially designed algorithms to automatically create workout plans that are pertinent to exercisers’ demographics, fitness goals, fitness preferences, and skill levels. Despite its growing use in AI-powered fitness applications, there are still few studies examining exerciser experience with it. To fill this gap, this research conducted content analysis on exercisers’ online reviews of AI-powered fitness apps that are relevant to the feature. The analyses reveal 4 themes: exerciser information and feedback collection, workout plan generation and adaptation, workout data tracking and analysis, and workout data presentation. Furthermore, this research extracted 8 sub-themes within the 4 themes and enumerated the key points of view for each of these themes and sub-themes. This research contributes to the literature on fitness apps by illuminating exerciser experience with the emergent feature. It also contributes to the literature on human-AI interaction by delving into the unique context of digital fitness and generating fresh insights on the interaction between exercisers and AI-powered fitness apps. The findings of this research provide valuable insights into the factors that drive and hinder exercisers from adopting and continuously using this novel feature.