At the 2023 Platform Strategies event, we posed the question to our attendees: "What do you anticipate to be the biggest shift in scholarly publishing in the coming year?"

Unsurprisingly, artificial intelligence emerged as a prevalent topic during the conference and in the responses provided by our participants. Our graphic recording artist visually captured their answers in real-time. Below, explore the transformations that industry leaders anticipate in the coming year, both in visual and written formats.

  1. Opening new revenue streams with AI
Opening new revenue streams with AI could revolutionize scholarly publishing in the coming year through such applications as automating the process of manuscript screening and peer reviews, thus speeding up the publication process. AI tools could also be used to detect plagiarism or fraudulent data, ensuring the integrity of published work. Additionally, AI could personalize content delivery, tailoring recommendations based on user behavior or preferences, leading to increased user engagement and subsequently, higher subscription rates.

  1. Open new engagement streams with Generative AI
Introducing engagement streams with generative AI could have a transformative impact on scholarly publishing in the coming year. AI could facilitate personalized learning experiences, tailoring content to individual readers' needs and learning styles, thereby enhancing their engagement and fostering a deeper relationship with the platform.

  1. Education and research moving closer together
As education and research move closer together, scholarly publishing could see a shift towards more practical and application-focused content in the coming year. This convergence could also lead to the democratization of research, making it more accessible to students and educators and fostering a culture of continuous learning and improvement. Additionally, it could encourage more interdisciplinary studies, breaking down traditional silos in academia, resulting in more holistic and comprehensive research publications.

  1. Discoverability of scholarly content
Enhanced search capabilities through the use of AI could allow users to find more relevant and targeted content, improving user experience and increasing engagement. This increased discoverability could also facilitate cross-disciplinary research and collaboration, leading to more innovative and comprehensive scholarly publications.

  1. AI in production
AI technologies could automate tasks like formatting, proofreading, and even initial rounds of peer review, reducing time and cost, and allowing for quicker publication. AI could also help in predictive analytics, enabling publishers to identify trending research topics and strategically plan their content, thus staying relevant and competitive.

  1. AI in ethics
AI tools can be utilized to detect plagiarism, data manipulation, or other unethical practices, ensuring the integrity of the published work and enhancing the credibility of the platform. AI could also be employed in ethical decision-making processes, for instance, in managing conflicts of interest or ensuring fair and unbiased peer reviews, thereby promoting transparency and fairness in scholarly publishing.

  1. AI in peer review
AI could automate initial stages of review, checking for basic standards and flagging potential issues, thereby reducing the burden on human reviewers and speeding up the process. AI could also help in matching manuscripts with the most suitable reviewers based on their expertise, enhancing the quality of reviews and ensuring a more efficient and effective peer review process.

  1. Increased momentum with learning technology interoperability
The seamless integration of various educational resources, tools, and platforms facilitates access to a wider range of scholarly content and fosters cross-disciplinary learning and research. Interoperability could also lead to the development of more comprehensive and inclusive learning environments, catering to diverse learning needs and preferences, and thereby increasing the reach and impact of scholarly publications.

  1. Reconciling existing publishing models around open access content
Breaking down paywalls and making scholarly content accessible to a wider audience ultimately needs to align with publishing models for the long-term sustainability of OA within scholarly publishing. These efforts could encourage more collaboration and interdisciplinary research, and accelerate the pace of scientific discovery, while also pushing publishers to explore alternative, sustainable revenue models.

  1. Growing AI accessibility of scholarly content
AI can enhance search capabilities, making it easier for users to find, access, and engage with relevant content, thereby increasing the reach and impact of scholarly publications. AI can also easily transform images, text, audio, video, and more into new formats, thereby supporting accessibility efforts.

  1. Using AI to work smarter not harder
AI can automate repetitive tasks such as formatting and initial screening of manuscripts, thereby freeing up human resources for more strategic and creative tasks. AI can also provide valuable insights through data analysis, helping publishers make informed decisions about content selection, marketing strategies, and user engagement, leading to more efficient operations and potentially higher revenues.

  1. Managing stakeholder expectations related to AI transformation
Clear communication about the benefits and limitations of AI can help mitigate fears about job loss or over-reliance on technology, fostering acceptance and adoption of AI tools. Additionally, involving stakeholders in the AI transformation process can ensure that the technology is used in a way that meets their needs and preferences, leading to improved user satisfaction and potentially higher engagement with scholarly content.

  1. Incorporating AI meaningfully in everything
AI can streamline the publishing process, enhancing efficiency and cost-effectiveness. However, in the midst of an over-abundance of AI-related marketing plugs, the key drivers in the coming year will be those who incorporate in truly meaningful ways that do more than just offer lip service to the technology.

  1. Changing editorial workflows to include AI research integrity checks
Incorporating AI research integrity checks into editorial workflows could help to quickly detect issues such as plagiarism, data manipulation, or ethical violations, ensuring the integrity and credibility of published work. This can also streamline the review process, allowing editors to focus on the intellectual merit of submissions, thereby improving the quality and value of published research.


Read other recaps, watch the recordings, and peruse the photo gallery in the 2023 Platform Strategies Archive. 

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