Based on a presentation delivered during a recent Prophy webinar on the future of scholarly publishing.
One of the questions I hear most often these days is some variation of the following: Do journals still matter? Will books survive? Where is scholarly publishing headed over the next two to five years?
These are understandable questions, but they may not be the most important ones.
Before asking whether journals will survive, it is worth stepping back and asking a more fundamental question: What is the purpose of scholarly communication in the first place?
At its core, scholarly communication has always served four essential functions:
- Registration – Research must be formally recorded to enter the scholarly record.
- Verification – Knowledge must be reviewed, scrutinized, and validated before it can be trusted.
- Accessibility and Discoverability – Research must be findable and able to reach the right audiences.
- Preservation – The scholarly record must be maintained for future generations.
Historically, journals have fulfilled all four functions, often within a single artifact. That consolidation is now beginning to unravel.
The Interface Is Changing, Not the Foundation
The most important distinction to understand is this: journals are unlikely to disappear because they remain central to maintaining the verified scholarly record. What is changing is their role as the primary interface through which people discover and consume knowledge.
AI systems are rapidly becoming the dominant interface for research discovery, summarization, synthesis, contextual interpretation, and personalized navigation. Researchers, clinicians, students, policymakers, and professionals are increasingly turning to AI tools rather than browsing databases or journal websites directly.
As this shift accelerates, journal content increasingly operates behind the scenes while AI becomes the visible interaction layer.
This does not mean journals are becoming less important. Rather, their role is evolving.
On one side, journals continue to provide trust, validation, certification, and long-term stewardship of the scholarly record. On the other, the functions of discovery, navigation, and synthesis are increasingly moving toward AI-powered systems.
The latter may change dramatically. The former remains indispensable and may become even more valuable in a world flooded with AI-generated content.
Why Long-Form Scholarship Still Matters
The rise of AI has also revived a familiar assumption: that faster, shorter, and more convenient forms of information consumption are inherently better.
I am not convinced.
Books and long-form scholarship continue to serve a critical purpose that summaries and AI-generated responses cannot fully replicate. They help build expertise, judgment, and intellectual depth.
Deep understanding does not emerge from consuming information alone. It develops through sustained engagement with complex ideas, reflection, synthesis, and, at times, intellectual struggle.
Reading a summary can improve efficiency. It rarely develops mastery.
For that reason, books, monographs, and other forms of long-form scholarship will remain essential, not despite advances in AI, but because of them. As AI makes information more accessible, the ability to think critically and deeply may become even more valuable.
AI Will Change How Scholarly Content Is Created
AI will undoubtedly accelerate the production of scholarly content. Many aspects of scientific writing, editing, and communication are already becoming more automated.
But acceleration is not the same as replacement.
Researchers will continue to play a central role in generating original ideas, conducting experiments, interpreting findings, exercising judgment, and defining research questions. Likewise, peer reviewers, editors, and research integrity professionals will remain critical to validating and certifying knowledge.
The more interesting shift may be in how scholarly influence is established.
As AI increasingly assists with writing and expression, a researcher’s ability to communicate ideas effectively across disciplines and to broader audiences may become a more important differentiator. Public communication, interdisciplinary explanation, and the ability to translate complex findings into meaningful narratives could become increasingly important measures of impact.
Communication may no longer be viewed as a peripheral skill. It may become a core component of scholarly contribution.
The Publisher’s Strategic Opportunity
Publishers face an important strategic choice.
For decades, the dominant model has been relatively straightforward: validate content and license access to it. That model is now under pressure from multiple directions.
The more important question is what comes next.
A significant opportunity may lie in becoming providers of trusted context and interpretation for AI systems.
In practical terms, this could include:
- Author-approved plain-language summaries
- Rich metadata and semantic tagging
- Knowledge graphs and structured research relationships
- Research integrity and provenance frameworks
- Machine-readable context that helps AI systems interpret findings accurately
- Governance mechanisms that reduce the risk of misrepresentation or hallucination
In this emerging environment, publishers function less as gatekeepers of content and more as providers of trusted knowledge infrastructure.
The organizations that help AI systems understand, contextualize, and accurately represent scholarly knowledge may hold significant influence in the future research ecosystem.
Publishers are well positioned to play this role, but doing so will require deliberate investment rather than passive observation.
The Scholarly Ecosystem Is Reorganizing, Not Collapsing
The traditional scholarly communication model was relatively linear:
Researcher → Journal → Reader
The emerging model is more layered:
Researcher → Journal and Publisher → AI Systems → User
Researchers continue to create knowledge.
Journals continue to validate and certify it.
Publishers increasingly provide context, structure, and integrity safeguards.
AI systems facilitate discovery, interpretation, and synthesis.
Users increasingly consume interpreted knowledge rather than raw content.
In this environment, journals become the trust layer. Publishers become providers of knowledge infrastructure. AI becomes the interaction layer.
Journals and books do not disappear from this picture. If anything, their importance in supporting trust, expertise development, validation, and long-term preservation may grow.
What changes is where value is created, how knowledge is accessed, who controls interpretation, and where influence resides within the ecosystem.
That is a significant enough shift to demand serious strategic thinking from publishers, editors, librarians, and researchers alike.
But it is important to recognize what this moment is—and what it is not.
This is not the collapse of scholarly communication.
It is a reorganization.
The foundational functions of registration, verification, accessibility, and preservation remain as essential as ever. What is changing is where those functions sit within the scholarly communication stack and how users interact with them.
The challenge for our industry is not whether to adapt to this shift. It is how to shape it—and how to ensure that the systems being built on top of the scholarly record are worthy of the research they are designed to serve.
About the Author
Ashutosh Ghildiyal is Vice President, Strategy and Growth at Integra and has spent nearly 20 years working in scholarly and research publishing. He is passionate about the future of scholarly communication and frequently writes and speaks on topics including AI, research integrity, peer review, publishing innovation, and the evolving role of publishers in the global research ecosystem. He has worked extensively across Asia and international markets, helping organizations build partnerships, expand capabilities, and navigate industry change.
