Scholarship on how artificial intelligence is reshaping professional practice — across healthcare, law, business, engineering, education, media, and public policy. Every submission gets an AI-assisted first-pass review, then a decision made by qualified human peer reviewers.
We publish as the world's first multilingual academic journal: every page can be translated instantly into dozens of languages and narrated aloud, alongside dyslexia-friendly, high-contrast, and focus-support reading tools — so the research is genuinely accessible to readers everywhere, not just fluent English speakers.
The Journal publishes original research examining the application, governance, and consequences of AI systems within professional domains. We are not a venue for opinion pieces, product announcements, or unreviewed commentary — that content belongs in Future Ahead Magazine, which is edited separately and is not part of the peer-reviewed record.
Diagnostic tools, clinical decision support, regulatory pathways, patient outcomes
Algorithmic accountability, AI in judicial and regulatory process, liability frameworks
Enterprise adoption, workforce impact, productivity measurement, organizational change
Applied methods, evaluation frameworks, deployment case studies, reliability
Pedagogy, academic integrity, learning-outcome studies, assessment design
Synthetic media, platform governance, disinformation research, journalism practice
Algorithmic trading, credit and risk modeling, labor-market and macro effects
Regulation design, procurement, public-sector deployment, international governance
Trust, explainability, usability of AI-assisted professional tools
Fairness, bias, labor displacement, environmental and social impact
AI-enabled threats and defenses, model security, adversarial robustness
Predictive maintenance, logistics optimization, industrial automation
Don't see your domain listed? The scope above is illustrative, not exhaustive — if your work examines AI's application or consequences within any professional field, it's in scope. Contact the editorial office if you're unsure before submitting.
Empirical studies with original data, analysis, and methodology. No length cap; typically 4,000–9,000 words.
Structured synthesis of existing literature with a stated search and inclusion methodology.
In-depth examination of a single deployment, organization, or incident, with clear generalizable takeaways.
Detailed method, system, or tool descriptions — reproducibility and implementation detail expected.
Focused findings or early results, up to ~2,500 words, reviewed on the same double-blind standard.
Study design and methodology peer-reviewed and provisionally accepted before data collection.
This is a young journal, and we're not going to inflate that fact: the article below is the first thing we've published. It went through the same desk check, AI-assisted first-pass review, and external double-blind human peer review described under Editorial Process that applies to every submission.
Shubh Sharma (University of Maryland, College Park)
Everything you need to prepare, format, and submit a manuscript — in one place, the way established journals lay it out.
Aims & scope, accepted article types, and word-count expectations for each. Read this before you start writing.
Pre-structured with all required sections and declaration prompts, so nothing gets missed. Delete the author block for blind review.
APA 7th edition throughout — author-date in-text citations, alphabetical reference list under its own "References" heading. Every in-text citation must have a matching entry, and vice versa.
We encourage depositing datasets and code in a repository with a persistent identifier — Zenodo, OSF, Figshare, or a public GitHub release — and citing it in a Data Availability Statement. If data can't be shared, say why.
Use the applicable EQUATOR Network standard for your study design: CONSORT for trials, PRISMA for systematic reviews, STROBE for observational studies, or TRIPOD-AI for prediction-model and AI-system evaluation studies.
Studies involving human participants or their data require IRB/institutional ethics approval and a documented consent process, cited by name and approval number in the manuscript.
Disclose any generative-AI tool used in drafting, editing, analysis, or code — name, version, and its specific role — consistent with ICMJE/COPE authorship norms. AI tools cannot be listed as authors.
Originality, ethics approval, blind-review formatting, funding, and conflict-of-interest declarations are collected as a required step inside the submission portal — worth previewing before you start.
Beyond scholarly quality, every accepted article is published to meet standard indexing requirements (including Google Scholar's technical guidelines), so your work is actually discoverable once it's live:
AI does the screening work — structure, completeness, internal consistency across 7 heuristic agents that cross-check each other — so human reviewers spend their time on judgment calls, not formatting. AI never makes the accept/reject decision; that's always a named human editor or reviewer. See full disclosure in our Peer Review Policy.