The article explores the impact of Artificial Intelligence (AI) on Big Data Analytics, discussing its role in transforming raw information into valuable intelligence. AI acts as the engine driving big data analytics, enabling predictive and prescriptive analytics to identify patterns, forecast future trends, and recommend actions to optimize outcomes. The integration of AI with big data solutions enhances speed, accuracy, and personalization, providing faster decision-making, enhanced accuracy, and personalized experiences. Machine Learning (ML) and Deep Learning are key technologies driving AI in big data, while Cloud Computing and Edge Analytics enable real-time processing and analysis. However, implementing AI and big data solutions comes with challenges such as data quality and integration, resource-intensive requirements, and ethical concerns. Real-world examples of AI in big data include retail giants like Amazon, finance institutions like JPMorgan Chase, and transportation companies like Uber. The future of AI in big data analytics is marked by emerging trends like autonomous systems, democratization of AI, and AI-IoT integration, promising unprecedented levels of innovation and efficiency. To unlock the full potential of AI in big data, ensuring high-quality data is foundational to delivering actionable insights and confident decision-making.