Predictive data analytics powered by artificial intelligence (AI) has become a game-changer for improving strategic decision-making in contemporary businesses. Organizations are using cutting-edge AI technologies like machine learning, deep learning, and natural language processing to glean useful insights from massive and intricate datasets in an increasingly data-intensive business environment. Organizations may increase overall operational efficiency, identify possible dangers, forecast future trends, and allocate resources optimally with the use of predictive analytics. In order to enhance strategic decision-making in important organizational domains like finance, marketing, human resources, supply chain management, and risk management, this study investigates the use of AI-driven predictive analytics. The study looks at how predictive models help managers make evidence-based decisions, increase forecasting accuracy, and improve scenario planning. Organizations can move from reactive to proactive and prescriptive decision-making by combining AI algorithms with big data infrastructures. The study also emphasizes how crucial cloud computing, automated decision-support systems, and real-time analytics are to enhancing competitive advantage. The report also covers the theoretical underpinnings of dynamic capacities and data-driven decision-making, highlighting the ways in which AI adoption promotes organizational agility and creativity. AI-driven predictive analytics has many benefits, but it also has drawbacks, such as algorithmic bias, data privacy issues, a shortage of qualified experts, integration difficulties, and ethical considerations. The study assesses these issues and recommends governance structures and ethical AI procedures to guarantee accountability, equity, and openness in strategic choices. According to the research, companies that successfully apply AI-based predictive analytics show better performance outcomes, decreased uncertainty, increased risk reduction, and better strategy alignment. According to the study's findings, AI-driven predictive analytics is a strategic enabler that transforms corporate decision architectures rather than just being a technical advancement. The investigation of hybrid AI-human decision models and the creation of moral AI guidelines specific to strategic management settings are two areas of future research.