How does the Embedded Model differ from other AI models?

The Embedded Model is distinctive because it enhances the current infrastructure by integrating AI capabilities within it rather than needing a separate or entirely new system. This approach allows organizations to leverage their existing resources and systems while still benefiting from advanced AI functionalities. By augmenting rather than replacing, the Embedded Model facilitates a smoother transition to AI-enhanced operations and minimizes disruption to ongoing processes.

The emphasis on augmenting existing infrastructure means that organizations can tap into their current investments and technologies while evolving to include intelligent capabilities. This model fosters greater efficiency and can lead to a more immediate return on investment, as it builds on what is already in place.

In contrast, the other options suggest scenarios that do not align with the Embedded Model's practical application. While some models might require a complete overhaul of an infrastructure or depend solely on external services, the Embedded Model operates on a principle of integration and enhancement, making it a particularly effective and practical choice for incorporating AI into business processes.