01 · The Question
Can AI Help Complete the Information Required by a Journal Submission System?
Your manuscript is ready, the figures have been prepared, and the cover letter is complete. You open the journal's submission portal expecting to upload the files and finish.
Instead, the system asks you to enter the manuscript title, abstract, keywords, author names, affiliations, email addresses, funding information, and several declarations. Some information already appears in the manuscript, but the portal requires it in separate fields.
Could generative AI extract this information, organize it, and help you complete the submission more efficiently?
Potentially. However, submission metadata is not merely administrative text. It helps identify the research, associate publications with their authors, support indexing and discovery, and communicate important information to editors and publishing systems. A small error can persist beyond submission if it is not detected.
03 · What You Need to Know
How AI Can Assist With Journal Submission Metadata
What Is Journal Submission Metadata?
Journal submission metadata is structured information describing a manuscript and its associated authors, institutions, funding, and publication-related characteristics.
Unlike the manuscript's main text, metadata is typically entered into designated fields within the submission system. Some information may subsequently be transferred into editorial, production, indexing, and scholarly metadata systems.
Crossref, for example, supports the registration and dissemination of scholarly metadata associated with persistent identifiers. ORCID provides persistent researcher identifiers that help distinguish individuals with similar names.
Not every submission field becomes part of the public publication record. Some information is collected for editorial administration, policy compliance, or confidential assessment.
Which Metadata Fields Can AI Help Prepare?
AI can be useful when the required information already exists in verified documents and needs to be extracted or organized.
| Metadata Field |
Possible AI Assistance |
What Must Be Verified |
| Manuscript title |
Extract the final title and identify inconsistencies |
Exact agreement with the approved manuscript |
| Abstract |
Extract or adapt the abstract to portal formatting |
Accuracy, word limits, and consistency with the manuscript |
| Keywords |
Organize existing keywords and suggest relevant alternatives |
Author approval, journal limits, and scientific relevance |
| Author names |
Organize names into required fields |
Spelling, name order, preferred publication names, and authorship approval |
| Affiliations |
Format institutional information |
Official institution names and correct author-affiliation relationships |
| ORCID iDs |
Match verified identifiers to author records |
Ownership and correct association with each author |
| Funding information |
Structure funder names and award details |
Actual funding records and correct grant identifiers |
| Author contributions |
Organize approved contribution descriptions |
Actual contributions and agreement among authors |
| Declarations |
Prepare text for required fields |
Truthfulness and compliance with journal requirements |
| Suggested reviewers |
Organize independently verified candidate information |
Expertise, identities, conflicts of interest, and journal rules |
AI should not fill missing information through plausible guesses. A blank grant number, uncertain affiliation, or missing ORCID iD is a verification task, not an invitation to generate a likely answer.
Why Accurate Metadata Matters Beyond the Submission Portal
Metadata supports several activities across the scholarly communication process.
Accurate author names and identifiers can help associate publications with the correct researchers. Institutional affiliations may support organizational reporting and research discovery. Funding metadata can help connect scholarly outputs with the organizations that supported them.
Incorrect information may cause administrative difficulties, inaccurate attribution, or problems during publication and indexing.
For example, a misspelled author name might be reproduced in production records if it is not corrected. A wrongly assigned ORCID iD could associate a publication with another researcher.
Not every error has the same consequence, and publishers may provide correction mechanisms. Nevertheless, checking metadata before submission is generally easier than resolving discrepancies after publication.
AI Extraction Is Different From AI Generation
The distinction between extracting existing information and generating new information is particularly important.
Metadata extraction
Identifying and transferring information that already exists in an authoritative source, such as an approved manuscript or verified author record.
Metadata generation
Producing new wording, suggestions, or values that may require substantive author judgment and independent verification.
Extracting the exact manuscript title is generally a lower-risk task than generating a new abstract. Similarly, formatting an approved affiliation is different from deciding which institution should receive attribution for the research.
Researchers should preserve this distinction when evaluating whether an AI-generated entry can be transferred directly into the submission system.
Can AI Enter Metadata Directly Into a Journal Submission Portal?
Some AI-enabled browser tools and automation systems may be technically capable of interacting with online forms. However, technical capability does not establish that automated submission is permitted or reliable.
Journal submission systems differ in their interfaces, access controls, validation rules, and permitted workflows. Certain fields may require direct confirmation by the corresponding author.
Automated entry can introduce errors through incorrect field mapping, accidental overwriting, or misunderstanding of dropdown options. It may also create privacy or security concerns when an external tool receives access to a submission account.
Authors should review the journal's applicable rules and avoid sharing account credentials with unauthorized services.
Where automation is permitted, the researcher should inspect the populated fields before any final submission action. A system should not independently make declarations or submit a manuscript without the author's informed authorization.
Why Author Names and Affiliations Require Particular Care
Names and affiliations are not always straightforward to extract.
Researchers may use different publication names, have multiple institutional appointments, or change affiliations during a research project. Some submission systems separate given names and family names in ways that do not accommodate every naming convention equally well.
AI may incorrectly infer which part of a name belongs in a particular field or associate an author with the wrong institution.
Rather than relying on inference, obtain approved information from each author. Where ORCID authentication is supported, authors should use the journal's authorized process to connect their identifiers.
AI should not create an ORCID iD or claim that an identifier belongs to a researcher without verification.
Funding and Disclosure Fields Must Reflect Actual Records
Funding information may include the name of the supporting organization, award identifier, and sometimes the recipient or associated project.
AI can format these details, but the underlying information must come from actual funding records.
The same principle applies to conflict-of-interest declarations, ethics statements, data availability information, and author contributions.
For example, AI should not infer that a study received no external funding simply because no funding statement appears in the manuscript. Absence of information is not evidence that a particular declaration is true.
Researchers should establish the facts before using AI to prepare the corresponding submission text.
Can AI Suggest Keywords and Manuscript Classifications?
Yes. AI can propose keywords based on the manuscript's research questions, methods, and subject matter.
It may also help identify relevant subject categories within a journal's submission system.
However, proposed terms should be evaluated for disciplinary accuracy and alignment with the journal's available classifications. An AI-generated keyword may sound appropriate while misrepresenting the actual study.
Where the journal uses a controlled vocabulary or predefined category list, authors should select from the official options rather than assuming that AI-generated terminology will be accepted.
The process of generating research manuscript keywords with AI can support discoverability, but final keyword selection remains an author decision.
Should Authors Compare Portal Metadata With the Final Manuscript?
Yes. Submission metadata and manuscript files can become inconsistent when authors revise one without updating the other.
A title may change during final editing. The abstract entered into the portal may be copied from an earlier draft. Author affiliations or contribution statements may be revised after the metadata was initially prepared.
These discrepancies can cause confusion during editorial processing and production.
A final comparison should therefore use the exact manuscript version intended for submission, not an earlier working draft.
04 · A Practical Example
Preparing Journal Submission Metadata With AI
Hypothetical Example
Submitting a Study on AI-Supported Feedback in Higher Education
A research team has completed a manuscript examining how university students respond to AI-supported formative feedback. The corresponding author must enter information into the target journal's submission system.
The team has already approved the final manuscript title, abstract, author order, affiliations, funding statement, and contribution descriptions.
The corresponding author uses an institutionally permitted AI tool to organize the approved information into a submission worksheet.
Step 1: Extract existing information
The AI extracts the manuscript title, abstract, and approved keywords without changing their meaning.
Step 2: Organize author metadata
The AI arranges the approved author names and affiliations according to the portal's requested fields. The corresponding author verifies every name and affiliation against the authors' confirmed information.
Step 3: Identify missing information
The AI notices that one author's ORCID iD is absent from the supplied records. Instead of inventing an identifier, it marks the field for confirmation.
Step 4: Prepare declarations
The AI organizes the team's approved funding and contribution statements. The authors check that the wording accurately represents the underlying records.
Step 5: Enter and verify the information
The corresponding author transfers the information into the journal's submission system, checks each field against the final manuscript, and reviews the portal's submission summary before proceeding.
During the final review, the researcher notices that the abstract in the submission worksheet came from an earlier manuscript version. The correct abstract is substituted before submission.
The example illustrates why AI-assisted preparation can improve organization while still requiring careful human verification. The principal benefit is reducing repetitive transcription work, not transferring responsibility for metadata accuracy.
06 · What This Means for You
Use AI to Prepare Metadata, Not to Make Unverified Submission Decisions
The safest approach is to create a verified metadata worksheet before entering the journal's submission portal.
Use the final approved manuscript and confirmed author information as the primary sources. Ask AI to extract and organize the relevant fields, preserving exact wording where necessary.
Separate information that can be copied directly from information requiring author judgment or confirmation.
A practical metadata verification framework
If the field contains an exact manuscript value
Extract it from the final approved version and verify that no wording or formatting has been changed incorrectly.
If the field identifies an author or institution
Use confirmed author information and verify names, affiliations, identifiers, and corresponding-author details.
If the field requires a declaration
Establish the underlying facts with the responsible authors before preparing or entering the statement.
If the field requests a classification or keyword
Evaluate the available options against the actual manuscript and select the most appropriate terms.
If an AI tool can populate the submission portal automatically
Confirm that the automation is permitted, protect account access, and review all populated fields before authorizing submission.
For declarations, AI can assist with organizing an approved author contribution statement or conflict-of-interest statement. It should not determine the underlying facts independently.
Before submission, perform a final comparison between the portal metadata, manuscript files, and verified author records.
That review should form part of the broader process of checking AI-assisted journal submission materials.
