How Editors Are Using Ai To Streamline Their Work

Gary Smailes
Gary Smailes | 3 December 2025
How Editors Are Using AI to Streamline Their Work

Where AI Fits in the Editorial Workflow

Treat AI like a sharp junior in the office. Great at sorting, fast at pattern spotting, always in need of your eye. Judgment, taste, and ethics stay with you.

Map tasks to stages

Think in stages, then slot tools where they help.

A simple rule saves time: tools propose, editors dispose.

Anchor to style and audience

Unanchored tools drift. Give them context.

Then ask for outputs in that frame. “Apply Chicago, US spelling, house London terms list, middle-grade tone.” If the response wanders, stop and restate the frame. Consistency follows clarity.

Pick the right tool for the job

Choose categories with intent. One tool rarely does everything well.

Test tools against a known sample from your archive. Score speed, accuracy, and false positives. Pick what earns trust, then standardize.

Build prompt libraries that work every time

Reusable prompts save hours and improve consistency. Write them like checklists, not wishes.

Store your best prompts in a shared document. Add examples and expected output formats. Update after every project. Future you will thank you.

Quick exercise: pick one scene. Run your line-edit assist prompt on a 300-word excerpt. Accept nothing. Use the suggestions to spot patterns, then revise by hand. Read aloud. If the voice slipped, roll back.

Track results with simple numbers

Good editors measure. Not everything, only what guides decisions.

Build a small dashboard in your project tracker. When a tool slows you down or introduces new errors, drop it or change scope.

Guardrails that keep standards high

Use AI to clear the path, not to choose the destination. The work still belongs to you.

Manuscript Intake and Assessment

Start fast, then slow down. Use AI to map the terrain, then bring your eye to the hard parts. No shortcuts on judgment.

Rapid triage

Give a model the opening chunk, around 25 to 50 pages, plus any pitch materials. Ask for three outputs, short and usable.

Example prompt:

“Read the first 30 pages. Write a one-page synopsis, three themes, and three comp titles from the last five years. Keep to 250 words. No new facts. Plain style.”

Now verify. Compare the synopsis to the manuscript, not to your hopes. Pull lines that support each theme. Cross-check comps with Bookshop or Nielsen. Remove mismatches before sharing with the author.

Quick exercise: give the same pages to two tools. Put both synopses side by side. Merge the best parts into a tight brief. Spend five minutes max.

Character, location, and timeline matrix

Continuity problems hide in small details. Names shift. Ages drift. A model can sift for patterns across a chunk, then you confirm.

Example prompt:

“From this excerpt, build a table with columns: character, role, age, key traits, first appearance, last appearance, recurring locations. Add a second table for locations with description, first appearance, notable events. Flag name variants or age conflicts.”

Run this on the opening and a mid-book section. Look for mismatches. Eleanore vs. Eleanor. A June scene listed as winter. Mark each issue in your notes with page numbers. Resolve with the author during the first call, not three rounds later.

Scene-by-scene outline with beats

Editors diagnose pacing with structure in hand. A scene map reveals gaps faster than a reread.

Example prompt:

“Produce a scene list: number, location, on-page characters, POV, purpose, beats, approximate word count. Highlight abrupt POV shifts or time jumps. Present as a table. Do not invent events.”

If the manuscript lacks clear breaks, ask for sections by double line space or **. Accept a rough map, then refine. Check approximate counts against chapter totals to spot bloated scenes or thin bridges. Note repeated scene purposes, such as three consecutive arguments resolving nothing. Plan queries from those notes.

Mini-test: take one chapter. Read the scene map, then read the chapter aloud. Does the map match what you hear. If not, revise the map before diagnosing anything.

Developmental report skeleton

Do not wait until a full read to build scaffolding. Start a skinny report while the structure sits fresh.

Use a template like this:

Example prompt:

“From the outline and synopsis, draft bullets for strengths, risks, opportunities, and questions for the author. Prioritize structural issues over line-level comments. Keep to 300 words.”

Paste this skeleton into your report doc. After a full read, rewrite every point in your voice. Add page numbers, quotes, and suggestions framed as choices.

First-pass style sheet

Anchoring early prevents whiplash later. Ask a tool to gather choices, then lock decisions after review.

Example prompt:

“Create a first-pass style sheet per Chicago, US spelling. Include names, titles, capitalization, hyphenation, numerals, abbreviations, recurring terms, place names, and foreign words. Provide entries in two columns: term, decision.”

Check names against the manuscript. Confirm whether Mr., Mrs., and Doctor appear with periods. Pick twenty-one vs. 21 style based on genre and house rules. Set hyphenation for well known compounds in advance. Keep a notes column for open questions, such as dialect spellings or headline case. Share the style sheet with the author after round one, not before burdening them with decisions made in haste.

Data minimization and validation

Protect the manuscript and your reputation. Follow a narrow-input rule.

A simple workflow keeps standards high:

  1. Extract structured notes with a model.
  2. Confirm against pages in front of you.
  3. Log decisions in the style sheet.
  4. Use findings to plan the human read.

What good intake feels like

You finish with a one-page brief, a living scene map, a continuity grid, and a style sheet draft. Enough to guide a conversation with the author, set a scope, and build a schedule. No guesswork, no bloat. The machine handled sorting and listing. You handled judgment, tone, and priorities. That balance wins projects and keeps revisions tight.

Line Editing and Copyediting Assistance

Treat the model like a sharp intern. Fast with patterns. Never in charge of the sentence you sign off on.

Targeted rewrites without losing voice

Work at the line level, not across the whole book. Paste one paragraph. Give guardrails.

Example prompt:

“Offer 3 tighter options for this paragraph. Keep tone, subtext, and voice. Preserve all on-page facts. Max 10 percent shorter. No new imagery.”

Sample original:

“Jonah was starting to feel as though the room was getting smaller around him, and he began to think that he might not have made the right choice.”

Possible options:

  1. “The room seemed to shrink. Jonah wondered if he chose wrong.”
  2. “The room pressed in. Jonah doubted his choice.”
  3. “Space tightened. Jonah questioned the decision.”

Now do your job. Pick the option that fits the character, or stitch two options into one line. Keep a copy of the original in the margin for traceability.

Mini exercise: run the same prompt on three spots with different moods. A joke. A moment of fear. A quiet beat. See where the model matches tone, and where it goes flat. Note patterns.

Clarity and concision passes

Signal exactly what to reduce. Ask for a light touch. Then review like a hawk.

Example prompt:

“Edit for clarity and concision. Reduce filler, nominalizations, and unnecessary passive voice. Preserve cadence and character voice. Track changes.”

Before:

“There was a realization on her part regarding the necessity of making a decision in relation to the plan.”

After:

“She realized she needed to decide on the plan.”

Scan for losses. If the edit trims nuance, restore it. If rhythm breaks, rebuild it. Keep a short list of banned tics for this book. Things like “seemed to” or “started to.” Ask the model to flag those for a focused pass.

Consistency sweeps

Set the rules first. Then ask the tool to mark deviations, not to decide.

Essentials to align:

Example prompt:

“Using US spelling and Chicago style, list inconsistencies across capitalization, numerals, acronym handling, and serial comma use in this chapter. Return as issue, location, suggested fix.”

Sample output items to expect:

Approve or override each, then push decisions into the style sheet. Repeat at the end of each chapter.

Surface style issues at scale

Patterns sink prose. Surface them fast, then decide what to fix and what to keep as voice.

Ask for a report like this:

“Provide counts and examples for repeated words, cliché phrases, adverbs ending in -ly, echoing sentence starts, and mixed metaphors. Limit to top 20 items, with page numbers.”

Look for:

Do not scrub the life out of the prose. Protect deliberate repeats. Flag the rest for a second pass.

Courteous author queries in a house tone

Use the model to draft neutral comments. Then adjust for your relationship with the author.

House tone examples:

Batch similar queries. Keep them short. Avoid moralizing. Ask for intent, not guilt.

Prompt to try:

“Draft margin comments in a neutral, professional tone. One sentence each. No prescriptive language unless necessary for safety or legality.”

Locking decisions into the style sheet

The style sheet is the spine. Update it while you work, not at the end.

Core sections to maintain:

Example entry:

“health care. open as noun, hyphenate as modifier only when needed for clarity.”

“OK not okay.”

Share the style sheet before copyedit starts. Invite the author to confirm high-risk areas such as dialect, capitalization of terms of respect, and invented spellings.

Compare versions without losing voice

After each round, run a diff. Then read the changed lines aloud. Listen for voice drift.

Checklist for a compare pass:

Prompt to assist:

“Review the redlined changes. Flag any edits that alter meaning, subtext, or tone. List page and line with a brief note.”

Accept, reject, or adjust. Note each decision in the change log.

A practical workflow that saves hours

You decide what lives in the book. The model speeds the grunt work, surfaces risks, and keeps you honest. That leaves you free for the high-value edit, the one the author hired you to do.

Research, Fact-Checking, and Continuity

Your name rides on the facts. AI helps you gather, sort, and test them fast. You still make the call.

Build a fact-check checklist

Pull checkable claims into one place before you chase sources. Dates. Measurements. Historical statements. Brand names. Titles. Legal terms. Medical claims. Anything a sharp reader might trip over.

Prompt to try:

“From this chapter, list checkable claims with location. Include dates, places, measurements, historical statements, quotations, brand names, and stats. Return as claim, location, suggested source type, risk level from 1 to 3.”

Then verify against authoritative sources. Primary first. Laws and statutes for legal points. Peer‑reviewed work for science. National archives for history. Manufacturer specs for tech.

Example triage:

Keep a citation list as you go. Page, source, retrieval date, and a short note on relevance.

Mini exercise: run the checklist prompt on one chapter with heavy exposition. Then on a quiet scene. Compare volume and risk levels. Notice where your instincts match the model, and where they diverge.

References and citations without chaos

Messy references slow everyone down. Use the model as a formatter, not a decider of facts.

Prompt to try:

“Standardize these references to Chicago Notes and Bibliography. Preserve author names, titles, publication year, publisher, and DOI or URL. Flag any missing elements. Return as formatted entries plus a list of gaps.”

Common fixes to expect:

For APA, swap the prompt. The model handles commas and periods at speed. You verify authors, years, and titles match sources. Reconcile in-text citations with the reference list. Ask for a crosswalk.

Prompt:

“Cross-check in-text citations against the reference list. Report missing entries, mismatched years, name variants, and duplicates. Include location and a suggested fix.”

Timelines, ages, and travel logic

Continuity errors break trust. Build a grid to hold dates, ages, and movement through space.

Prompt to try:

“Extract a timeline from this manuscript. Include chapter, scene date, on-page time cues, character ages, and travel segments with start and end points. Return as a list with page markers.”

What to scan:

Ask the model to compute distance and duration with real-world constraints.

Prompt:

“For each travel segment, estimate plausible duration by car, train, or foot based on typical conditions. Note any implausible legs.”

Approve, adjust, or bend for story reasons. If you bend, leave a breadcrumb for the reader, a line that signals awareness.

Quotations, epigraphs, and permissions

Quotes attract errors. Epigraphs even more so.

Prompt to try:

“For each quotation or epigraph in this chapter, list exact text, stated source, original source if different, publication year, and public domain status. Flag discrepancies and likely permission needs.”

Then verify. Use reliable editions. Cross-check punctuation and capitalization. Watch for ellipses that change meaning. Confirm translations and translators.

Example catch:

Escalate anything with legal exposure to the publisher or rights team. Note your findings in the memo and style sheet.

Sensitive language and inclusivity sweeps

Run a scan, then hand work to sensitivity readers where lived experience matters.

Prompt to try:

“Scan this chapter for terms tied to race, gender, disability, religion, sexuality, age, nationality, and class. Flag outdated or harmful terms, stereotypes, or careless metaphors. Provide neutral alternatives and context notes. Do not rewrite.”

Use judgment. Voice, period setting, and character intent matter. Your goal is to surface risk and open a conversation, not to scrub voice into paste.

Sample query language:

Log decisions in the style sheet so your copyedit stays consistent.

Plain-language summaries of technical sources

Authors often bring dense research. Help them integrate it with clarity.

Prompt to try:

“Summarize the key findings from this technical source in plain language for a general audience. Limit to five bullet points. Preserve nuance. Note any uncertainties or contested claims. Include page references.”

Use these summaries to shape margin notes:

Example:

Original: “Incidence increased by 12 percent year-over-year, adjusted for demographic shifts.”

Summary: “Cases rose 12 percent from last year, even after accounting for changes in age and population size.”

Tie each point back to the manuscript with a clear suggestion. “Introduce population size before citing the rate.” Brief. Useful.

A practical workflow that saves hours

AI accelerates the grunt work. You protect meaning, voice, and trust. That partnership keeps the book honest, and keeps you focused on the edit only you bring.

Project Management and Client Communication

Your edit lives or dies on logistics and tone. AI helps you move faster, stay consistent, and keep authors calm. You still steer.

Draft letters and roadmaps, then tune the voice

Start with a rough build. Ask for structure, not prose.

Prompt to try:

“Outline an editorial letter based on these notes. Sections needed: greeting, summary of strengths, top three priorities, three to five concrete next steps, risks to watch, suggested timeline, closing that invites questions.”

Paste your notes. Get a scaffold in seconds. Then rewrite the opening and the calls to action in your voice.

Sample opening you can adapt:

“Thank you for trusting me with this draft. The voice is confident and the stakes feel clear by chapter three. To focus revisions, I recommend three priorities. Pacing in the middle third. Clarifying the antagonist’s goal. Tightening exposition in scenes with medical detail.”

For fiction, attach a revision roadmap:

For nonfiction, attach a query sheet that gathers open questions by chapter. Ask the model to draft queries in a neutral house tone, then check for specificity and kindness.

Prompt to try:

“From these margin notes, produce a query list by chapter. Each entry should include the issue, a direct question, and a suggested path to resolve. Keep the tone courteous and clear.”

Schedules, milestones, and status without fuss

Map the work before you start. Ask for task lists with dependencies.

Prompt to try:

“Create a schedule for a 92,000-word novel with a two-round edit. Round 1 developmental, Round 2 line edit. Include tasks, durations in days, dependencies, and simple milestone names. Format as bullets I can paste into a calendar.”

Then drop the dates into your calendar or PM tool. Color-code stages. Set alerts for handoffs and author check-ins.

Useful milestones:

For weekly updates, keep it short. Three lines do the job.

Ask the model to compress notes into those three lines. Edit for accuracy.

Estimating scope, timelines, and budgets

Start with the manuscript length and complexity. Factor in health of the draft, number of sources, number of figures, and special formatting. Build a simple model, then test best and worst cases.

Prompt to try:

“Estimate hours and delivery dates for a 60,000-word prescriptive nonfiction book. Inputs: first-time author, 120 in-text citations, heavy tables, one round of dev edit and one round of copyedit. Assume 1,500 words per hour for dev read and note-taking, 1,000 words per hour for dev edit, 1,800 words per hour for copyedit. Include admin overhead at 15 percent. Present three scenarios: smooth, average, rocky, with dates for a start on [DATE].”

You will still price based on your rates and risk. The model gives you a baseline and a way to explain tradeoffs to the author.

Templates that save your future self

Standardize the routine parts. Store them in one place.

Keep templates for:

Example intake email:

“Thanks for sending the manuscript. I have the files and will hold them in a private folder. I will start with a close read and send a developmental letter by [DATE]. If you have questions or new material before then, reply to this thread so we keep a single record.”

Prompt to try:

“Revise this template email to match a warm, professional voice. Keep to 120 words. Avoid jargon. Add one sentence that sets expectations for response times.”

Version control that prevents heartburn

Name files so no one wonders which draft is current. Keep a change log. Store prompts used for major decisions.

Adopt a pattern:

ProjectName_Author_Stage_V01_2025-03-12_AB.docx

Stages to use:

Add a plain text change log in the project folder. Date, file, summary of changes, who touched it. Ask the model to turn a messy list of edits into a tidy log.

Prompt to try:

“Summarize these tracked changes into a change log with date, file name, and two-line summaries. Group by theme where possible.”

Store a “Prompts” document with the key instructions you used for this project. Include notes on settings, glossaries, and any house rules applied. Future you will thank you during proof.

Marketing support on request

Sometimes an author needs copy for agents or sales. Treat it like a separate mini project. Ask genre-specific questions before you draft.

Prompt to try:

“Based on this synopsis and audience note, write three versions of back-cover copy. 120 words each. Tone: tense and propulsive for a thriller. Include a one-line hook, the protagonist, the central conflict, and a sense of stakes. No spoilers.”

For a query letter, focus on the hook, comp titles, word count, and credentials. Keep it short.

Prompt to try:

“Draft a one-page query letter to a literary agent for a 90,000-word contemporary romance. Include a 2–3 sentence hook, two comps published in the last five years, author bio in two lines, and closing with thank you.”

Always adjust to house voice and market norms. Swap out comps that do not fit. Tighten nouns and verbs.

A lightweight weekly rhythm

This rhythm keeps you ahead of surprises. AI moves the boxes faster. You keep the relationships steady and the work readable.

Ethics, Privacy, and Professional Standards

Your reputation rides on trust. AI helps with speed and scale, but your name covers every decision. Set the rules before the work starts.

Get permission in writing

Spell out AI use in your agreement or welcome packet. Keep it plain. List the tasks covered. Name the tasks excluded. Give the client a way to opt out of any item.

Clause you can adapt:

“I use privacy-first AI tools for admin and analysis. Covered tasks include summarizing notes, flagging consistency issues, formatting references, and preparing schedules. I do not upload full manuscripts to public models. I do not ask AI to rewrite narrative voice or make final edits. I review all outputs and remain responsible for decisions. If you prefer to limit or stop AI assistance at any time, tell me in writing.”

Add a line to your intake email:

“For transparency, I use privacy-first AI for checklists and schedules. No full manuscript uploads. All decisions stay human.”

Privacy by default

Treat the manuscript like a medical file. Share on a need-to-know basis. Lock down the tools.

Quick redaction pass:

Disclosure and credit

Some agents, publishers, and journals expect a statement. Give it clean and factual. Never list AI as an author or co-editor.

Disclosure text to adapt:

“This project used AI tools for administrative support and editorial analysis. Tasks included schedule drafting, reference formatting, and consistency checks. All developmental, line, copyediting, and final proofreading decisions were performed by the editor.”

If an entity asks for tool names or versions, provide them. If they ask for prompts, provide representative samples without revealing private client details.

Copyright and licensing

Protect the author and protect yourself.

When in doubt, say so. Better a cautious note than a rights complaint.

Keep humans in the loop

Draw a bright line between suggestion and decision. AI proposes. You decide.

Reserve these for human judgment:

Use AI for support tasks:

Mark AI suggestions in comments. Explain your reasoning in the letter. Own the edit.

Audit for bias and fairness

Bias slips in through prompts and outputs. Look for skew, and keep a record of fixes.

Mini test to try:

Give the model two author bios. One male, one female, with identical achievements. Ask for pitch lines. If the male bio gets “visionary” and the female bio gets “supportive,” your prompt needs work.

A simple policy pack

Keep these documents ready and up to date:

Store them in your house style folder. Review quarterly.

Prompts that help you write the policy

Use a model to draft guards, not to set them.

Edit those drafts yourself. Strip out fluff. Align with your jurisdiction and your contracts.

A preflight checklist for every project

Run this before you touch the manuscript:

Treat ethics like style. Document the rule. Follow the rule. When the rule fails, fix the rule and tell the client what changed. That is how trust survives new tools.

Frequently Asked Questions

What should I upload during manuscript intake and assessment to protect privacy and get useful AI output?

Follow a data minimisation rule: upload short excerpts (opening 25–50 pages, a mid-book section, and the ending) rather than full drafts, and replace personal or sensitive names with placeholders like [AUTHOR] or [COMPANY]. That gives the model enough context for a useful synopsis, scene map, or character matrix while reducing exposure of confidential material.

Use privacy-first settings or enterprise plans where available, save screenshots of terms and retention settings, and keep a simple data map that records tool, purpose, date, and which section you shared. These steps make manuscript intake and assessment both safe and auditable.

How do I preserve the author's voice during AI-assisted line editing?

Treat the model as a suggestion engine: run AI-assisted line editing on single paragraphs with tight prompts such as “Offer three tighter options, preserve tone and regional idiom, no new facts.” Ask for options, not rewrites, then choose or rework the suggestions by ear to keep rhythm and idiosyncratic diction.

Work with a reference paragraph nearby, accept only mechanical fixes automatically, and perform a voice-check by reading earlier favourite pages alongside revised text. If the voice slips, restore or rewrite the line so the author’s signature moves remain intact.

What belongs in a prompt library and how do I write prompts that work every time?

Store reusable prompts as checklist-style templates: triage prompts for synopses, a style sheet starter to extract names and hyphenation, line-edit assist prompts that preserve voice, and query-generator prompts for neutral margin comments. Each prompt should state format, scope (word-count or paragraph), and hard guardrails such as “No new facts.”

Test prompts on known archive samples and score them for speed, accuracy and false positives; only standardise the ones that earn trust. Keep examples, expected output formats, and a change history so prompts evolve with each project.

How should I track AI suggestions, decisions and versions so the process is transparent?

Maintain a concise change log and clear version-control filenames (for example Project_Author_LineEdit_V02_2025-06-01.docx). For each AI session record date, tool and version, purpose (e.g. “flag passive voice in Chapter 3”), key prompts, scope of text submitted and a short summary of what was accepted, rejected or rewritten by hand.

Store the log and prompts with the manuscript files and include a data map (tool, purpose, date, excerpt) so agents, publishers or legal teams can trace human decisions after the fact. That single audit trail both protects you and speeds review.

What quick metrics should I track to evaluate whether a tool is saving time or introducing errors?

Track a few simple numbers: time saved per stage (minutes logged for intake, diagnostics, line prep, QC), error rates caught by the tool in a small sample (style violations, repeated words, citation mismatches), author satisfaction (one question score out of five) and percentage of suggested changes the author accepted. These measures give a practical sense of alignment and value.

Use a small dashboard to spot when a tool starts to slow you or increase false positives; if acceptance rates fall or time savings disappear, narrow the tool’s scope or replace it. Measure what guides decisions, not everything.

When and how should I disclose AI use to clients, agents or publishers?

Disclose when a venue asks, when AI shaped text materially, or when contracts require it. Use plain factual language in acknowledgements or production notes (for example: “I used [Tool, version] for line-level suggestions on grammar and consistency; all revisions were reviewed and approved by me”). Never list AI as an author—credit the help, not authorship.

Include disclosure and AI-use clauses in your agreement or welcome packet so clients know permitted tasks and opt-out options up front. Keep representative prompts and the change log available if a publisher requests further detail.

How do I combine AI workflows with sensitivity readers and fact-checking to avoid bias and factual errors?

Use AI for technical tasks—claim extraction, timeline grids, plain‑language summaries—and then put humans in charge of cultural and factual integrity. Do not treat prompts like “check for cultural sensitivity” as a substitute for lived-experience review; sensitivity readers catch nuance that models miss.

Implement a fact-check protocol after every AI pass: verify dates, names and statistics against primary sources, flag high-risk claims, and run an inclusivity sweep before sending text to sensitivity readers. Human-in-the-loop workflows preserve voice and reduce the risk of bias and hallucinated facts.

Writing Manual Cover

Download FREE ebook

Claim your free eBook today and join over 25,000 writers who have read and benefited from this ebook.

'It is probably one of the best books on writing I've read so far.' Miz Bent
Get free book