Fact-Checked AI Content Workflow: A Step-by-Step Editorial SOP That Meets Google’s ‘People-First’ Guidance

Mika Sandgrove | | 4 min read

Fact-Checked AI Content Workflow: A Step-by-Step Editorial SOP That Meets Google’s ‘People-First’ Guidance

Intro: Who this SOP is for (and the single promise)

This SOP is for teams publishing AI-assisted drafts, doing content updates/refreshes, or repurposing existing assets into new articles. It’s built for editors, content managers, and SEO leads who need accuracy work to be repeatable and auditable, not “be accurate” vibes.

Single promise: follow this workflow and every publishable piece ships with (1) a claim log, (2) risk-tiered verification, and (3) recorded evidence + sign-off, so you can explain what you published and why.

This SOP is not generic AI writing tips, deep technical SEO, or legal advice.

Working definition of “fact-checked”: material claims are verified against appropriate sources and the evidence is recorded (URL, excerpt, access date, decision).

Foundation: Define “material claims” + risk tiers

A material claim is anything a reasonable reader could act on, repeat, or use to decide. Log and verify:

  • Facts, numbers, dates, and “as of” statements
  • Comparisons/superlatives (best/only/fastest/guaranteed)
  • Quotes, attributions, “according to” references
  • Safety, pricing, eligibility, policy, compliance statements

Risk tiers (tier up if unsure):

  • Low: general statements; minimal harm if wrong.
  • Medium: specific product details, comparisons, pricing ranges, process steps.
  • High: YMYL (health/finance/legal), safety guidance, regulated/medical claims, warranties/guarantees, or anything that could cause harm.

Evidence rules: high-risk needs primary sources (regulators, laws, manufacturer docs, official datasets) and/or SME review; if you can’t support it, remove or escalate. Medium can use reputable secondary sources; corroborate if contentious. Low gets quick verification or a rewrite to a broader, supportable truth.

Avoid false precision: don’t keep exact numbers/dates you can’t verify (e.g., “in early May 2024” vs. “May 3, 2024”).

The step-by-step fact-check workflow (with gates + artifacts)

Run this on every AI-assisted draft. A spreadsheet or doc table is enough.

1) Intake: freeze the draft (save a version), capture prompt/context, open the claim log.

2) Extract claims: go section by section; log each material claim with location and risk tier, and assign an owner.

3) Verify sources: find evidence that directly supports the claim; prefer official/current sources. Record URL + excerpt + access date.

4) Fix or delete: keep only what the evidence supports. Rewrite unsupported specifics, drop false precision, and delete or escalate anything high-risk you can’t verify.

5) Quote/citation hygiene: confirm quotes exist, replace broken/irrelevant citations, and ban AI-invented references and fabricated attributions.

6) Final gate: set status (Approved / Needs SME / Needs legal-compliance / Rejected) and record sign-off.

Example: claim log row

Claim (verbatim) Location Risk Evidence URL Evidence excerpt Decision Owner Accessed
“Product X includes a 2-year warranty.” Pricing section, ¶2 Medium https://manufacturer.example/warranty “Product X warranty term: 24 months…” Verified Editor 2026-10-05

People-first & anti-deception controls (final gate)

Accuracy isn’t enough if presentation is misleading. Add a final integrity check before publish.

Byline/author profile verification:

  • Author is a real person (or clearly labeled editorial team).
  • Claimed credentials/experience are accurate and consistent across the site.
  • No invented affiliations (schools, employers, boards).

Disclosure policy (consistent and non-misleading): disclose AI assistance when it materially shaped drafting or research in a way readers would care about. Keep wording plain (e.g., “AI-assisted draft; reviewed and fact-checked by [name/role]”). Don’t imply hands-on testing you didn’t do.

Anti-deception rules:

  • No fabricated expertise (“as a doctor…”) without credentials.
  • No fake testimonials/case results.
  • No “we tested/used/measured” unless you actually did.

Example rewrite (remove manufactured experience):

  • Deceptive: “We tested five tools and Tool A was fastest.”
  • Truthful: “Based on vendor documentation and independent reviews, Tool A is often reported as fast; results vary by setup.”

Accountability: Roles, sign-offs, and audit trail (lean RACI)

Keep this lightweight but enforceable.

  • Writer: drafts, flags claims, fills first-pass claim log.
  • Editor (owner): assigns risk tiers, enforces rewrites/deletions, sets publish status.
  • Fact-checker (if separate): verifies evidence, records excerpts, challenges weak sources.
  • SME: required for high-risk/YMYL, safety guidance, policy interpretation, or disputed claims.
  • Legal/compliance: required for regulated claims, warranties/guarantees, medical/legal advice risk, or liability exposure.

Retain: claim log, evidence notes, version history, approvals/sign-offs. Keep them with the article until the next major update (or 12+ months, whichever comes first). Store in a shared folder (e.g., article-slug_fact-check_YYYY-MM-DD).

Conclusion: What “done” looks like + start using it today

Publish-ready means: every material claim is logged, high-risk claims are supported by the right level of evidence (or removed/escalated), quotes and attributions are verified, and approvals are recorded with a clear final status.

If you adopt one habit, make it the claim log: claim → evidence → decision → owner → date. Run this SOP on the next AI-assisted draft or refresh, then reuse the same artifacts on every update so accuracy work stays consistent and defensible.

Sources

  1. Google Search Central: Creating helpful, reliable, people-first content
Mika Sandgrove

Article author

Mika Sandgrove

Mika Sandgrove is an SEO writer and independent SEO consultant with more than three years of experience creating and optimizing content for search. He runs his own SEO practice, helping businesses improve their organic visibility through SEO strategy, content optimization, and technical and on-page SEO services. Much of his work comes through freelance marketplaces and online client platforms, where he works with businesses across different industries and markets. Mika primarily writes about SEO, search visibility, and practical optimization strategies, and is increasingly exploring Answer Engine Optimization (AEO) and how businesses can adapt their content for AI-powered search experiences.