An academic publisher hears that AI can handle screening, correspondence, formatting and reference checks. The obvious question follows: how many staff hours—or how much money—could that save?
The answer depends on what the journal actually does today. Automation may remove repetitive steps, but running a credible journal also involves judgments, relationships and investigations that do not disappear when a model produces an answer quickly.
Start by mapping the real workflow
Follow a manuscript from submission to publication. Record the time spent checking files, confirming declarations, assigning an editor, inviting reviewers, tracking revisions, checking references, producing final formats and correcting metadata.
Distinguish repetitive work from tasks that require expert authority. Sending reminders may be straightforward to automate; deciding whether a clinical study has a fatal methodological flaw is not. A system that generates long reviews without reliable evidence checking could increase, rather than reduce, editorial work.
Where automation is promising
Manuscript completeness checks, consistent email drafts, reference matching, metadata validation and production quality assurance are good candidates for controlled trials. Tools may also help summarise reviewer reports for editors to verify.
Crossref's metadata guidance illustrates why seemingly modest improvements matter. Accurate titles, contributors, funding, licenses and references make outputs more discoverable and easier to connect to the wider scholarly record.
If a journal repeatedly repairs incorrect identifiers after publication, automating checks before release may save more time than automating article summaries.
The expenses are broader than the software subscription
A publisher may need model access, secure hosting, developer time, staff training, monitoring and a process for reviewing false positives. Confidential manuscript information can require specialised controls.
The ICMJE's AI guidance puts responsibility on human participants and warns against compromising manuscript confidentiality. A cheap public AI tool that creates privacy or integrity exposure is not a genuine cost-saving measure.
Test savings on one workflow
Consider a hypothetical journal handling 240 submissions a year. If a validated administrative tool saves 12 minutes per submission, that is 48 staff hours annually. At an illustrative fully loaded labour cost of $15 per hour, the gross labour value is $720 before software and oversight costs.
The arithmetic is deliberately modest. It shows why claims about eliminating entire editorial teams should be treated carefully. The saving may be worthwhile across a large journal portfolio, but negligible for one title if tooling is expensive.
Other benefits may matter more: fewer production mistakes, faster acknowledgments, better metadata and a clearer audit trail. Those outcomes should be measured alongside staff time.
Calculate the risk of a wrong answer
Not every publishing error has the same consequences. An incorrect draft reminder is inconvenient; an incorrect rejection explanation can seriously affect an author; a mistaken research-integrity flag can cause reputational harm. Automation priorities should reflect those differences.
A practical pilot can run an AI tool alongside the current human process without allowing it to decide anything. Editors then compare outputs, record false alerts and measure whether the system notices real problems that staff otherwise miss. Only after that evidence is collected should the publisher consider reducing manual steps. A successful trial is one that demonstrates reliability, not one that produces the largest number of automatic messages.
Keep decisions accountable
Build a human approval step at points where an error can harm an author, misstate research or change the publication record. Preserve logs of important changes. Make the journal's permitted AI use clear to editors and reviewers.
A strong automation plan asks, 'How will we know this process is better?' before asking, 'How much of the office can we replace?' That is the difference between technology-led cost cutting and a more reliable publishing operation.
