From managing an ever-increasing volume of submissions, maintaining rigorous quality standards, navigating intricate ethical considerations, and ensuring the timely dissemination of groundbreaking research; the role of a journal editor has never been more crucial—or more complex.
Editors must contend with the breakneck pace of technology and its impact on research methodologies, data analysis, and even the very format in which academic work is presented and consumed. They must also be attuned to the changing expectations of authors, reviewers, and readers in an increasingly digital and open-access environment.
Providing support to editors and empowering them to excel in their roles is not just beneficial – it’s critical to the success and relevance of your journals.
The integration of cutting-edge technology, particularly artificial intelligence (AI), offers promising solutions to many of these challenges. In this post, we'll explore three innovative technology-backed strategies that forward-thinking scholarly publishers are exploring to better support their editors.
1. Equip your team with editorial content intelligence
How effectively are your editors able to react to market trends and reader preferences?
Emerging data and AI tools, such as Hum, are revolutionizing the way publishers understand their audiences and their content ecosystem. Sophisticated data and AI technology analyze every piece of content, mapping intricate relationships between different articles, topics, and authors while tracking historical performance metrics.
Oxford University Press journal publishers are leveraging this type of deep content intelligence and sharing it with journal editors and society partners to inform journal development and content strategy. Using Hum's Content Discovery reports, OUP staff can identify top-performing content and opportunities across its entire library, as well as pinpoint oversaturated topics and underperforming pieces.
These insights allow OUP to explore trends, reader engagement patterns, and understand how specific pieces or types of content are resonating with key audience segments. As a result, editors can identify promising research areas and emerging topics that align with the scope and readership interests for each journal.
Ashley Petrylak, Interim Publishing Director at OUP, shares: "Hum has given us a crucial, more broad view of what our readers are engaging with at a journal and portfolio level. And having access to content intelligence feeds our ability to support editors and present society partners with robust, data-backed recommendations on content strategy.”
2. Provide tools to support author and reviewer recruitment
Building and maintaining positive relationships with authors and reviewers is a crucial element of maintaining journal quality and relevance, and it’s a responsibility that requires a distinctly human touch. But it can also be time-consuming, and editors are often left to their own devices in determining who to focus on and how to reach them.
AI tools can support editors’ ability to hone in on and reach the right potential authors and peer reviewers; for example, Rockefeller University Press is using data and AI to target and customize campaigns for researchers at specific institutions with read and publish deals.
AI can also be used to support editors in managing the author experience. Some publishers are automating outreach and nurturing efforts for potential authors based on specific behavioral triggers. Others are using advanced intelligence to tailor calls for papers to audience members with proven interest in specific topics.
Introducing AI to identify author and reviewer candidates and help editors deploy targeted outreach can significantly reduce the administrative burden on editors, allowing them to focus more on strategy and personal relationship-building.
3. Help editors protect research integrity
Along these same lines, many publishers are investigating AI solutions for editorial workflows to enhance efficiency and quality control throughout the publishing process.
Wide adoption of AI by researchers has introduced new challenges for editors, and AI technology has proliferated paper mills and other significant threats to research integrity. As pressures remain on editors to uphold a strict standard for incoming manuscripts, the introduction of new AI tools can share the burden of responsibility editors face to catch bias, mistakes, and misinformation.
There are a wide number of specialized AI tools being developed and tested to combat these new challenges and bolster research integrity by:
- Pre-screening manuscripts for potential ethical concerns, data privacy concerns, or conflicts of interest
- Comparing submissions against vast databases of published work to identify plagiarism or text recycling
- Detecting data fabrication and inaccurate statistics with high accuracy
- Analyzing images in manuscripts to detect potential manipulation or duplication
Though editors and peer reviewers will still need to diligently review papers for quality standards, these tools can identify and flag issues far faster and more effectively than a human could.
Building systems to support editors works best with editor buy-in
By embracing new tools and AI-driven strategies, publishers can enable their editors to focus on the core aspects of their role: curating high-quality research, fostering academic discourse, and driving their fields forward.
Embedding new technology in existing editorial workflows can be intimidating, and it’s best done with editor buy-in. Publishers must approach AI implementation with sensitivity and clear communication.
- Focus on how AI can augment, rather than replace editorial judgment. Involving editors from the start helps alleviate fears and ensure that AI adoption truly meets their needs.
- Establish AI working groups that include and prioritize editors, allowing them to voice concerns and contribute to the decision-making process.
- Develop internal stakeholders to champion adoption. These key users are essential for building out comprehensive training and offering ongoing support to help editors effectively leverage new AI tools.
- Build internal resources. Workshops, one-on-one sessions, and playbooks can be useful onboarding tools to ensure that your editors feel supported.
The key to success lies in thoughtfully building and installing these AI solutions while preserving the critical human elements of editorial judgment and academic integrity.
As we move forward, the synergy between AI-powered tools and editorial expertise will not only enhance the quality and relevance of published research but also free up editors to focus on the strategic and creative aspects of their roles. This collaborative approach between technology and human insight promises to elevate the standards of scholarly publishing, benefiting researchers, readers, and the broader scientific community.