1. Fuelling Adaptive AI Models<p>Real-time data allows AI systems to respond instantly to dynamic changes, improving accuracy in areas like fraud detection, predictive maintenance, and personalised recommendations.<p>2. Breaking Data Silos<p>Data activation integrates fragmented data across platforms enabling AI to access rich, unified inputs for better insights and cross functional decision making.<p>3. Turning Insights into Action<p>Reverse ETL moves AI-generated insights from data warehouses back into operational tools (like CRMs) ensuring predictions drive real-world actions.<p>What other ways does data activation empowers AI Models?