Enterprise AI

The contributions by experts in multiple socio-technical disciplines have been accordingly structured in three parts: First, Scalable and Sustainable Practices for Enterprise AI explores emerging strategies that enable organizations to scale AI systems sustainably by maximizing performance while minimizing resource consumption. It offers a deep dive into three complementary approaches that address this challenge from different angles: data distillation, federated learning, and resource-efficient deployment. Next, Safe and Responsible Enterprise AI addresses the critical aspects of AI safety in the enterprise context. The four chapters provide a comprehensive set of resources for individuals and enterprises seeking to implement AI systems that are not only powerful but also principled. By addressing data quality, privacy, explainability, and human-AI collaboration, this part lays the groundwork for building AI systems that are safe, transparent, and aligned with human and organizational values. Eventually, Value Creation with Enterprise AI offers four chapters providing a multidimensional view of value creation with AI, that balances innovation with responsibility, and efficiency with trust. They provide a roadmap for enterprises seeking to harness AI not just as a tool for automation, but as a catalyst for meaningful, sustainable transformation.