You’ve seen a number of demonstrations of AI where the user outlines a series of steps the AI needs to take to produce an end goal. Multiple functionalities need to work together to accomplish the goal, including querying a corpus of knowledge, manipulating swarms, writing Python code to process the datasets, running the code, and applying the updated data to the swarm.
AI agents enable multi-step workflows triggered by simple, natural commands, often using compound requests—‘do this and then that’.
Agentic AI doesn’t just process commands—it empowers users. By translating multi-step tasks into AR visualizations, it transforms financial reporting into a collaborative, interactive experience that engages the visual cortex.