**John Furrier's Perspective on Agents as an Application for Generative AI** 1. **Market Transformation:** John Furrier believes that agents, particularly in the context of generative AI, are set to transform various markets. He emphasizes that AI will create renaissances in every single market due to advancements in hardware and distributed computing [Clip Link](https://video.cube365.net/c/942429). 2. **Enterprise Use Cases:** Furrier highlights the potential of agentic AI to drive tangible business value for enterprises. In his view, agentic AI offers a more structured and goal-oriented approach compared to consumer applications, which tend to be more open-ended and complex [Source Link](https://siliconangle.com/gen-ai-passe-enter-age-agentic-ai). 3. **Integration with Existing Systems:** The ability of agentic AI to integrate with legacy systems is another significant point raised by Furrier. He notes that connecting to legacy apps and harmonizing data across different platforms is crucial for the successful deployment of agentic AI [Clip Link](https://video.cube365.net/c/946074). 4. **Enhanced Decision-Making:** Furrier also discusses how agents can make intelligent decisions by analyzing vast amounts of data in real-time. This capability is essential for applications such as supply chain management, where agents can optimize multiple tasks and account for interdependencies within the system [Clip Link](https://video.cube365.net/c/956107). 5. **Future Trends:** Looking ahead, Furrier sees a shift towards lighter weight, cost-effective AI solutions like agentic AI. He believes businesses will be more attracted to this model compared to generative AI, which is heavier and more procedural-based [Clip Link](https://video.cube365.net/c/956620). In conclusion, John Furrier views agents as a transformative application for generative AI that can drive significant value across various markets and enterprise use cases by enhancing decision-making, integrating with existing systems, and offering a cost-effective solution.