Artificial intelligence has become an inescapable reality in scholarly publishing, prompting many organizations to implement AI solutions without clear strategy or structure. As a result, we now face a fragmented landscape of AI initiatives that often create more problems than they solve, from inconsistent decision-making to unpredictable outcomes and mounting technical debt. Process orchestration, combined with Graph-based Retrieval Augmented Generation (GraphRAG), offers a sophisticated path forward. Process orchestration provides the essential structure and control that AI implementations desperately need, while GraphRAG empowers AI systems with crucial context by leveraging the intricate network of relationships within publishing data. This powerful combination enables publishers to move beyond simple automation to truly intelligent workflows that enhance rather than complicate existing processes. Through real-world publishing examples, we'll demonstrate how process modeling creates the framework for effective AI deployment. You'll learn practical ways to identify AI touchpoints in your workflows, enhance them with GraphRAG capabilities, and implement the controls needed for quality and transparency. We'll explore specific applications in peer review, content classification, and author services, showing how these technologies work together to create reliable, scalable solutions. Join us to discover how leading publishers are bringing structure and purpose to their AI initiatives through systematic, process-first approaches. Whether you're beginning your AI journey or refining existing projects, you'll gain actionable strategies for orchestrating intelligent publishing processes that deliver measurable results.