Reimagining the Future of Data Analytics through Generative AI: A Mixed-Methods Comparative Study of Julius AI and Power BI Copilot

This study investigates how generative artificial intelligence (AI) is reshaping data analytics by focusing on two advanced platforms: Julius AI and Power BI Copilot. Employing a mixed-methods approach that integrates literature review, comparative analysis, and case-based observation, the research explores how these tools influence user roles, enhance data accessibility, and introduce new ethical and governance concerns. A conceptual framework is presented to analyze the relationship between technology, analytics processes, and human interpretation. Findings show that Julius AI enables agile, conversation-based analytics, while Power BI Copilot excels in enterprise integration and structured reporting. The study concludes with policy and educational recommendations for responsible AI adoption. Keywords: Generative AI, Data Analytics, Julius AI, Power BI Copilot, Mixed Methods, Human-AI Collaboration, AI Governance, Conceptual Framework.