Whitepaper
Transforming Scholarly Publishing: A Practical Framework for Responsible AI Adoption
As scholarly publishing grapples with rising submission volumes, operational bottlenecks, and increasing demands for transparency, the promise of AI is no longer hypothetical, it’s strategic. But successful integration requires more than automation. It demands editorial integrity, human oversight, and system-wide alignment. This whitepaper offers a clear, actionable roadmap for editorial and publishing leaders looking to harness the power of AI—without compromising academic standards or editorial independence.
What You’ll Learn
- Today’s Editorial Challenges, Redefined: Understand the pressures facing journal teams, from scale and speed demands to reviewer fatigue, and how AI can help address them meaningfully.
- A Strategic, Phased AI Implementation Framework: See how AI can be thoughtfully introduced across the editorial workflow, from submission triage and reviewer matching to decision letter support.
- Advanced Applications That Go Beyond Automation: Explore use cases like citation impact prediction, peer review quality scoring, and intelligent author guidance, all grounded in publishing workflows.
- Measuring What Matters: Learn which KPIs, like time-to-first-decision, editorial throughput, and cost-per-article, signal meaningful AI-driven improvement.
- The Irreplaceable Role of Human Judgment: Discover where human oversight remains essential, and how to design collaborative workflows that protect editorial autonomy and academic freedom.
- Addressing Bias, Fairness, and Transparency: Cut through the hype and hesitation with strategies to mitigate bias, protect data, and preserve integrity in AI-supported decisions.
And much more!