This paper examines the transformative impact of artificial intelligence on tax compliance and reporting functions across organizations. As tax departments face mounting challenges from regulatory complexity, frequent legislative changes, and increasing data volumes, AI technologies have emerged as powerful solutions to enhance efficiency, accuracy, and strategic value. The research analyzes the evolution of AI adoption in tax functions, from basic automation to advanced cognitive computing, exploring how machine learning, natural language processing, and robotic process automation address specific tax compliance challenges. Through examination of implementation case studies across industries, the study identifies significant benefits including 30-60% reductions in compliance time, 35-45% decreases in errors, and substantial improvements in audit outcomes. Despite these advantages, organizations face implementation challenges related to data quality, system integration, skill gaps, and governance concerns. The analysis demonstrates how successful implementations follow a strategic, phased approach that balances technology selection with organizational change management. Looking forward, AI adoption in tax functions is becoming a strategic imperative as tax authorities themselves increasingly employ advanced technologies for enforcement and as regulatory requirements trend toward real-time compliance and digital reporting. The research concludes that organizations implementing AI effectively can transform tax operations from cost centers focused on compliance into strategic functions that provide valuable insights for business decision-making while simultaneously reducing risks and operational costs.