Data topics

Business teams don't suffer from a lack of data. They suffer from a lack of time, clarity, and execution. Dashboards indicate what happened. Some tools even explain why. But few platforms help you decide what to do and then do it faster than your competition. That's the promise of augmented analytics. With agentic flows, natural language interfaces, and AI-driven automation integrated at every stage, that promise is now a reality.

AI analytics can help significantly improve inventory management analytics by introducing advanced capabilities to enhance accuracy, adaptability, and efficiency.

Here's how analytics and business leaders can gain a better picture of AI’s strengths and weaknesses when it comes to analytics uses.

This 2025 guide to AI analytics covers definition, architecture, and examples—plus how agentic AI with a semantic layer and orchestrated AI agents turns insights into approved action, reducing time-to-action and delivering measurable impact.