Challenges in Democratizing Generative AI in EPS are: Customization Change Management Education and Training A and B

The challenges in democratizing Generative AI in Enterprise Product Systems (EPS) can indeed encompass several factors, including: 1. **Customization**: Tailoring generative AI models to meet the specific needs and contexts of different organizations or departments can be complex. Customization requires understanding the unique requirements of users and the data they work with. 2. **Change Management**: Implementing new technologies like generative AI often leads to changes in workflows, processes, and job roles. Effectively managing this change to ensure smooth adoption and addressing resistance is a significant challenge. 3. **Education and Training**: As generative AI can be complex and technical, providing adequate education and training to employees is vital. Ensuring that team members understand how to effectively use these tools is essential for successful integration. Given these points, the answer to your question seems to suggest that the challenges are indeed a combination of customization, change management, and education and training. Therefore, "A and B" (referring to customization and change management) would only partially cover the challenges, as education and training are also crucial. In summary, the complete answer should note that all three factors play significant roles in the challenges of democratizing generative AI in EPS.