The increasing prominence of Artificial Intelligence (AI) in diverse fields has led to a growing interest in the concept of agentic AI, which refers to the autonomous, proactive, and decision-making capabilities of AI systems. This paper presents a systematic literature review of 42 peer-reviewed studies extracted from reputable academic databases, including Scopus, ProQuest, and ScienceDirect, to explore the state of research on agentic AI through the lenses of technologies, applications, and development domains. The review aims to explore technological advancements driving AI agency, examine its practical applications across industries, and analyze how Agentic AI enhances various business domains. Key findings highlight the rapid development of agentic AI technology components, such as architectural, learning, training and evaluation, and computational, alongside their different applications in healthcare, finance, education, and other business domains. Furthermore, the analysis reveals critical management strategies for integrating agentic AI, including governance, ethical guidelines, and organizational adaptation. By synthesizing current knowledge, this study provides a comprehensive understanding of agentic AI and identifies gaps and future research directions to advance its role in technology and management.