Artificial Intelligence-empowered software systems are continually evolving, with fuzzy logic frequently serving as a fundamental enabling technology [1, 2]. This tutorial aims to provide a comprehensive understanding of how fuzzy logic can enhance the capabilities of intelligent systems, enabling them to handle uncertainty, imprecision, and approximate reasoning more effectively [3–5, 69–72]. We will explore the foundational concepts of fuzzy logic, including fuzzy sets, membership functions, linguistic variables and fuzzy inference systems. Also, we will discuss other Artificial Intelligence techniques, which are often combined with fuzzy logic [6–8, 15–23, 33, 34, 41, 73–82]. Emphasis will be placed on the advantages of fuzzy logic in improving system adaptability, robustness, human-like reasoning [9, 10] and ethical requirements [28, 32, 35, 66–68] in comparison with other intelligent methods [11–13, 24, 30, 31, 40, 47–56] and machine learning [14, 25–27, 29, 36–39, 42–46]. Furthermore, through practical applications and case studies, attendees will have the opportunity to delve into the implementation of fuzzy logic into various software systems, enhancing their intelligence and performance in the context of AI-empowered software engineering [57–66, 83–85].