Navigating the AI Frontier – Balancing Human Brilliance and Machine Efficiency in Peer Review

Posted on: September 19th 2025

Each year, Peer Review Week offers the global scholarly community an opportunity to pause, reflect, and recalibrate one of the most fundamental pillars of scholarly publishing: the peer review process. This year’s focus on the AI era is particularly timely. Artificial intelligence (AI) has moved rapidly from being a peripheral support tool to becoming an influential force shaping the future of scholarly publishing. And let’s be candid: while AI brings tremendous opportunities, it also compels us to ask tough questions about what should evolve, and what must remain unequivocally human.

Unlocking Potential: How AI Can Revolutionize Peer Review Efficiency

At its best, AI has the potential to address long-standing inefficiencies in scholarly publishing. Reviewers are often overwhelmed by workload, editors face growing backlogs, and authors experience long delays in seeing their work published. AI-driven tools can step in to reduce this friction.

For instance, AI can assist in initial manuscript triage—screening for basic compliance with journal scope and policies, checking for integrity and ethical concerns. These are time-consuming but essential tasks where automation can free editors to focus on substantive intellectual critique.

Moreover, AI-powered linguistic tools can improve clarity and readability of submissions, particularly for researchers writing in non-native languages. By reducing barriers in communication, AI enhances inclusivity in publishing.

AI can also help scan through the experiment data and supplementary files to help identify specific insights that will help reviewers in their analysis and judgement. This is where the real opportunity lies: using AI to elevate the reviewer’s role, not dilute it.

Straive, with its deep expertise in content enrichment and technology-driven workflows, is already helping publishers integrate AI responsibly into manuscript preparation and review support.

The Integrity Imperative: Safeguarding Trust and Transparency in an AI-Powered Landscape

While the benefits are clear, so are the risks. If left unchecked, AI could undermine the very integrity it is meant to support. Consider the possibility of reviewers relying on AI-generated summaries without deeply engaging with the manuscript, or the risk of “black box” decisions made by opaque algorithms influencing acceptance outcomes.

The core question, then, is how can AI enhance, rather than erode, trust in peer review? Transparency is key. Reviewers, editors, and authors must know when and how AI tools are being used. Just as journals have adopted disclosure norms around competing interests, they may need to require statements on AI usage during the review process.

In addition, peer review platforms must ensure that the data used to train AI tools is ethically sourced, diverse, and representative. Without such diligence, there is a risk of perpetuating biases—whether in gender, geography, or institutional affiliation—that already challenge the fairness of peer review.

Building the Guardrails: Establishing Ethical AI Guidelines for Peer Review

The scholarly community cannot afford a “wait and see” approach. It needs a shared ethical framework to govern the responsible use of AI. Such guidelines should address at least three areas:

Transparency of Use: Reviewers and editors must disclose whether and to what extent AI was used in evaluating a manuscript. This ensures accountability and prevents over-reliance on machine-generated assessments.
Data Privacy and Security: Manuscripts are confidential intellectual property. AI systems used in peer review must guarantee data security and should not use sensitive content to train future models without explicit consent.
Bias Mitigation: Developers of AI systems must actively test and refine algorithms to minimize bias. For publishers, adopting tools from partners who are committed to ethical AI practices is essential.

Straive has embedded ethical AI principles at the core of its scholarly publishing services—aligning innovation with the enduring values of transparency and fairness.

Empowering the Human Element: Training and Supporting Editors and Reviewers in the AI Era

Even with clear guidelines, the human element of peer review cannot be overlooked. Many editors and reviewers are still skeptical with AI tools, or hesitant to adopt them. The solution? Publishers, universities, and professional associations must invest in training and empowerment.

Workshops and webinars can equip reviewers with practical skills: how to use AI responsibly, how to critically evaluate AI-assisted outputs, and how to recognize when a human judgment must override algorithmic recommendations. Peer review is, after all, both a technical and ethical practice; nurturing this dual awareness is vital.

Equally important is ensuring that reviewers feel supported rather than replaced. AI should be positioned as a partner—a tool to sharpen their insights, not supplant them. By framing AI as augmentation rather than automation, the community can foster confidence and reduce fears of dehumanization.

The Indispensable Core: What AI Can’t Replace in Peer Review

Despite AI’s growing capabilities, certain dimensions of peer review must remain uniquely human. At its heart, peer review is a dialogue among scholars—a process of intellectual stewardship rooted in curiosity, critical reasoning, and mentorship.

No algorithm can replicate the nuanced expertise of a researcher who has spent decades immersed in a field. Contextual judgment, the ability to weigh novelty against incremental contribution, or to recognize the transformative potential of an unconventional idea—these are profoundly human skills.

Yes, AI may be able to mimic polite feedback or suggest “empathetic” phrasing. But let’s be honest: true empathy in peer review goes beyond tone. It comes from lived experience, from understanding how feedback shapes careers, and from the mentoring spirit that constructive criticism can carry. It is this blend of expertise, discernment, and collegial exchange that machines cannot authentically replicate—and must remain the domain of humans.

Forging the Future: A Balanced Vision for AI-Enhanced Peer Review

The debate around AI in peer review is not a binary choice between rejection and adoption. Rather, it is a call for balance. AI can be a powerful ally in enhancing efficiency, inclusivity, and quality—but only if its use is transparent, ethical, and grounded in human oversight.

As the scholarly community reflects on the future of peer review, the conversation is ultimately about reaffirming trust—in science, in technology, and in each other. Straive, working at the intersection of content, data, and technology, is actively helping publishers navigate this transformation responsibly.

The future of peer review will not be defined by AI alone, but by how we, as a community, choose to integrate it. By safeguarding integrity, setting ethical standards, training editors and reviewers, and preserving the irreplaceable human spirit of scholarly dialogue, we can ensure that AI strengthens rather than diminishes the foundations of academic publishing.

Straive invites publishers, editors, and reviewers to collaborate in shaping a responsible AI-powered peer review ecosystem—one where technology enhances human judgment, rather than replaces it.

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