Introduction
Scientific and scholarly publishers face a convergence of rising submission volumes, tightening compliance mandates, and growing demands for faster, more accessible content delivery. Legacy workflows—built for slower, lower-volume eras—are now operational bottlenecks, impacting speed, scalability, and compliance.
This whitepaper explores how domain-trained AI can transform publishing operations—enhancing throughput, embedding compliance, and building long-term operational resilience without compromising editorial integrity.
About the Whitepaper
The paper takes a domain-centric approach to AI in publishing—mapping workflow vulnerabilities, outlining a practical AI maturity model, and sharing real-world use cases that move beyond point solutions toward strategic, end-to-end transformation.
It offers a phased roadmap—Discovery, Pilot, Scale—to help publishers deploy AI responsibly and effectively, ensuring integration with existing systems and minimal disruption to editorial workflows.