This thesis examines how Artificial Intelligence (AI) reshapes the foundations of competitive advantage in the digital era. Through a narrative literature review, it integrated classical strategic management theories, such as the Resource-Base View, the Knowledge-Based View and Dynamic Capabilities, with emerging technological developments including Data Science, Internet of Things (IoT), Cyber-Physical Systems (CPS), and Generative AI. The study shows that competitive advantage increasingly depends on a firm’s ability to combine data, technology, and human expertise into adaptive and continuously evolving capabilities. Across sectors such as manufacturing, finance, healthcare, retail and professional services, AI enables predictive maintenance, personalization, enhanced decision-making, and new data-driven business models. At the same time, the research highlights key challenges related to algorithmic bias, data quality, explainability, privacy, and the risk of organization dehumanization. These issues underline the need for strong governance structure and responsible AI deployment. The thesis also emphasized that human capital remains essential for sustained advantage, particularly as organizations transition toward the human-centric principles of Industry 5.0. Human-AI collaboration, continuous reskilling, and strategic HR practices are identified as critical for managing the emerging hybrid workforce. Overall, the study concluded that AI alone rarely creates lasting differentiation; sustainable competitive advantage arises when AI is combined with proprietary data, deep organization integration, ethical governance, and human-centred leadership.