Artificial Intelligence (AI) has emerged as a transformative force in the 21st century, enabling computational systems to simulate human cognition, automate complex processes, and provide predictive insights. This study critically examines AI theories, techniques, and applications across various sectors, highlighting interdisciplinary and societal implications. The historical evolution from symbolic reasoning to contemporary machine learning (ML), deep learning (DL), and hybrid intelligence frameworks is explored. Key AI techniques such as neural networks, reinforcement learning, natural language processing (NLP), robotics, and hybrid systems are analyzed. Sectoral applications in education, healthcare, agriculture, finance, governance, and defense are discussed with examples from India and internationally. Particular emphasis is placed on AI integration in education, including Intelligent Tutoring Systems (ITS), adaptive learning platforms, AI-driven assessments, teacher training, and skill development aligned with NEP 2020 objectives. Ethical considerations, including bias, transparency, accountability, privacy, and equity, are addressed. “This study highlights AI’s transformative role in personalized learning, student engagement, teacher training, and curriculum integration.”