AI is transforming the role of data analysts by using machine learning, automation, and intelligent systems to uncover patterns, predict outcomes, and drive impact. By 2027, AI will initiate 95% of sales research and analytics workflows. Traditional data analysts are evolving into AI data quality analysts who proactively improve data fidelity and surface insights before they're needed. AI-powered analytics has flipped the paradigm for querying large-scale datasets, detecting fraud, analyzing sentiment, and more, delivering faster, more scalable, and context-aware insights. However, adopting AI for data analysis comes with real-world hurdles that organizations must proactively address, such as data silos, skill gaps, integration complexity, and ethical concerns. To realize their full potential, organizations need a strategic mix of technology modernization, talent development, and governance, and tools like Acceldata's Agentic Data Management platform can help unlock the promise of AI-driven insights.