What’s starting to change in scholarly publishing

For much of the last decade, conversations in scholarly publishing revolved around identifying and dealing with crises such as research integrity, reviewer fatigue, reproducibility, or the use of AI. Peer review has carried a significant share of this burden. It remains one of the strongest trust signals in scholarly publishing and continues to play a central role in how research is validated and filtered.

But as we look toward 2026, something in the conversation is beginning to shift. There is growing recognition that peer review cannot, and should not, carry the full weight of safeguarding quality and integrity on its own. What feels different now is not a single reform or technology, but a change in how the system itself is being understood – less as a series of isolated checkpoints, and more as a connected ecosystem in which decisions made early quietly shape outcomes much later.

A few shifts stand out:

1) Integrity is moving upstream
Integrity failures rarely originate at the point of peer review. They are often the result of accumulated ambiguity: unclear expectations around study design, inconsistent data practices, blurred authorship norms, misaligned incentives, or uncertainty around acceptable uses of AI. By the time a manuscript reaches reviewers, many of these decisions have already been made. Peer review can surface concerns, but it is not designed to retroactively resolve systemic gaps.

As we look ahead, there seems to be an increasing focus on what happens before submission ever occurs. Today, the community is talking about clearer guidance at the research design stage, stronger support for data stewardship, explicit expectations around authorship, disclosure and AI use, and workflows that surface potential issues early, rather than forcing them to be inferred later.

This is not about shifting responsibility away from peer review. It is about recognizing that when expectations are clearer upstream, peer review becomes more focused, and less burdened by ambiguity. The result is more meaningful evaluation. It is encouraging to see community conversations headed in this direction.

2) AI is becoming quieter and more contextual

Early conversation around AI in scholarly publishing were loud, and understandably so. New capabilities arrived quickly, often without shared norms or guidance. Much of the focus, thus far, has been on detection, prohibition, or fear of misuse. What we are starting to see now is a more nuanced phase. Instead of asking whether AI is present, we are shifting our focus to the role it is playing. We are asking more pointed questions:

• Is it replacing human effort and/or judgment or supporting it?
• Is it being used as a shortcut or as a tool to eliminate redundant steps or processes?
• Is it obscuring responsibility or helping surface information more clearly?

There is a greater realization that the most thoughtful implementations of AI sit quietly within workflows rather than overriding them. They assist with consistency checks, language clarity, and pattern recognition, while leaving interpretation, critique, and decision-making in human hands. This shift matters because peer review and editorial decision-making require contextual understanding, disciplinary nuance, and professional judgment. As AI becomes more embedded in scholarly workflows, there is a greater acknowledgement of that fact that success in the use of AI will depend less on novelty and more on restraint.

3) There is a greater sense of shared accountability

For a long time, responsibility for research integrity has been implicitly concentrated at specific points: the author at submission, the reviewer during evaluation, or the editor at decision. What is changing is an acknowledgment that integrity is shaped collectively. Researchers operate within institutional cultures. Institutions respond to funding structures and incentives. Editors and publishers work within operational constraints. Service providers design tools that influence daily practices. Each layer introduces pressures, assumptions, and affordances that affect how decisions are made.

When accountability is fragmented, ambiguity grows. When it is shared, expectations become clearer. We are beginning to see integrity framed less as an individual moral obligation and more as a system-level responsibility that depends on alignment across roles rather than vigilance from a single group.

4) Designing for trust, not policing for failure

Taken together, these shifts point to a broader change in mindset. More and more people are talking about the need for better designs that reduce ambiguity, support human judgment rather than replacing it, and recognize integrity as something that can be built over time, not enforced at the end. Systems are changing to reflect this shift in mindset.

Peer review will remain central to scholarly publishing, but its impact will be amplified when it can operate as one layer within a well-aligned system, rather than as the final line of defense.

As we look toward 2026, the most meaningful progress may not come from doing more at the point of review, but from doing things better long before research ever gets there.

This perspective reflects how we think about the evolving scholarly ecosystem at ReviewerOne, where our focus remains on supporting peer reviewers through clearer workflows, responsible use of AI, and system-level approaches to integrity.