Effective human-AI collaboration for physical task com-pletion has significant potential in both everyday activities and professional domains. AI agents equipped with in-formative guidance can enhance human performance, but evaluating such collaboration remains challenging due to the complexity of human-in-the-loop interactions. In this work, we introduce an evaluation framework and a multi-modal dataset of human-AI interactions designed to assess how AI guidance affects procedural task performance, error reduction and learning outcomes. Besides, we develop an augmented reality (AR)-equipped AI agent that provides interactive guidance in real-world tasks, from cooking to battlefield medicine. Through human studies11The Institutional Review Board (IRB) of our institution approved this human subjects research before the start of the study., we share empirical insights into AI-assisted human performance and demonstrate that AI-assisted collaboration improves task completion.