Review AI-written blog posts before they go live

Before an AI-written post goes live, review AI-written blog posts the way you would review a new employee's first draft to a customer. Check the local facts, the prices, the names, and any sentence that sounds like proof, then ask whether it sounds like your business. A writing tool can hand you a clean paragraph that is still wrong. NIST's July 2024 Generative AI Profile calls that confabulation: the system generates and confidently presents erroneous or false content in response to a prompt. [1] Google's guidance is the practical counterpart. Focus on accuracy, quality, and relevance, especially when the page was produced automatically, including the title and description that can show up in search results. [2]

The check is about the draft, not a ban on the tool

Two habits both miss the mark. One is publishing because the draft sounds professional. The other is treating any sentence a tool touched as unfit to run.

Google's current spam policies define scaled content abuse as many pages generated for the primary purpose of manipulating search rankings and not helping users. The policy describes large amounts of unoriginal content that provides little to no value, no matter how it is created. [3] One example Google lists is using generative AI tools to generate many pages without adding value for users. [3] That example is about the abuse, not a rule that a machine may not help you write.

In a March 2024 explanation of the same policy, Google said its long-standing position is that automation, including generative AI, is spam if the primary purpose is manipulating ranking. The update, Google wrote, was meant to make clear that producing content at scale is abusive when it is done to manipulate rankings, whether automation, people, or a mix produced the pages. [4] A single post that a customer can use, checked by someone who knows the business, is not the pattern that definition describes. A stack of near-duplicate town pages, never compared to the towns you actually serve, is closer to it.

We use that line with clients. The review pass keeps a normal publishing habit on the useful side of it. The person who knows the price sheet still has to read the draft.

Local facts, names, and the record you already have

You will not catch this by tone. NIST describes confabulation as a result of how generative models are built. They approximate patterns in training data, so a sentence can be right, wrong, or inconsistent with an earlier line in the same draft. [1] The harm starts when someone trusts the confident version and publishes it. The same profile notes that generated citations and step-by-step logic can be false even when they seem to explain the answer. [1]

For a local business, the risky lines are the specific ones:

• Street address, suite number, phone, hours, and holiday closures
• Cities, counties, and ZIP codes you actually serve
• Staff names, job titles, and license numbers
• "Family owned since," years in business, and awards
• Services you still sell, and services you dropped
• Product brands you install, and certifications you currently hold

Read every proper noun against a record you control. That record is your website's contact page, a current license, a recent invoice, or the person who answers the phone. If the draft names a technician who left last year, or a suburb you stopped driving to, that is not a style nit. It is a false statement in your voice.

A sentence that stacks a certification, three town names, a founding year, and a savings figure is four claims. Unless each one is true today, delete it or replace it with a fact you can point to. Do not invent a title for a staff member the draft made up. If you publish for a client, the person who clicks publish needs that client's current service list. Grammar edits will not catch a retired partner.

Also check for contradictions. NIST includes output that diverges from the prompt or disagrees with something the draft already said. [1] If the intro says you are appointment-only and the FAQ welcomes walk-ins, keep the version that matches this week's operations.

Prices, offers, and claims that need proof

Price is not decoration. The FTC's small-business advertising FAQ lists price among material claims, the kind that matter to a buyer's decision, along with performance, features, safety, and effectiveness. [5] Advertisers must have evidence before the ad runs, and that evidence has to be a reasonable basis: objective support matched to the claim. [5] At a minimum, you need the level of proof the sentence itself promises. If the draft says something like "two out of three doctors recommend" a product, the FAQ says you need a reliable survey to that effect. [5]

The same standards apply to ad claims on the internet, including price comparisons and "on sale" language. [5] A post that says the inspection is free this month, or that packages start at a specific dollar amount, is making an offer. If that offer expired, applies to only one service, or was never your price, do not publish it and hope a footer will rescue you. When a disclosure is needed so the claim is not misleading, the FTC says it has to be clear, close to the claim, and easy to notice. Fine print does not undo a headline that says the opposite. [5]

A few patterns we strike before anything goes up:

• A dollar amount the draft guessed because other companies publish one. Use your price sheet, and date the figure or link to the page you update. An old number presented as today's price is how a helpful post becomes a complaint.
• "Limited time" with no end date you actually use.
• "Free" tied to another purchase, without the conditions. When a free offer depends on buying something else, the FTC says the price of that other item should not be increased above its regular price, and the important terms should sit near the offer. [5]
• A guarantee your contract does not offer. If you mention a guarantee or warranty, tell people how to get the details, and disclose limits such as a time window. [5] A money-back promise is not a substitute for proof. [5]
• Health, safety, or hard savings claims ("cuts energy use in half," "prevents mold") without matching support. In most cases, the FTC says those claims need competent and reliable scientific evidence. [5]
• Happy-customer lines used as if they prove an objective result. The FAQ says satisfied-customer statements usually are not enough for a health or safety claim, or for any other claim that needs objective evaluation. [5]

This is not a legal opinion. Every state has its own consumer protection laws for ads, many pricing questions are local, and the FTC usually refers local matters to state or city agencies. [5] The publishing test is simpler. If you would not say the number on a sales call, it does not go on the blog.

Customer quotes and borrowed authority

Drafts invent testimonials because testimonials make a page feel lived-in. That is one of the faster ways to create a problem you did not have an hour ago.

The FTC's Rule on the Use of Consumer Reviews and Testimonials took effect on October 21, 2024. [6] Staff guidance defines a testimonial as an advertising message people are likely to believe reflects someone's real experience, including copy on a company website. [6] Putting testimonials on your own site is disseminating them, and staff guidance says a business could be liable if they are fake or false. [6] The Commission's August 2024 announcement of the rule calls out reviews and testimonials that pretend to come from someone who does not exist, including AI-generated fake reviews, or from someone who did not have the experience described. [7]

Do not publish a quotation, a star story, or a before-and-after unless you can match it to a real customer and the words reflect what happened. Do not ask a tool to write a batch of glowing reviews. If you want a customer story, ask the customer, keep a record of permission, and use what they said. If the result was unusual, do not present it as normal. The FTC's small-business FAQ says consumer endorsements must reflect the typical experience, and that a line like "results may vary" is not enough when the story is not typical. [5]

Borrowed authority belongs in the same pass. "As featured in," "A+ rated," "licensed and insured," "factory certified," "the only shop in town." Each of those is a claim. If it is true, say it plainly and link to a source a skeptical customer could check. If you are not sure this week, cut it. A tool will often add the badge because other pages in the trade have one. That is a guess wearing your logo.

Does the draft sound like the business?

Facts can be correct and the post can still be the wrong page. Google's people-first guidance is a self-check, not a ranking recipe. Ask whether you have an audience that would find the page useful if they came to you directly, and whether it shows first-hand knowledge from doing the work. [8] One expertise question is plain: does the content have any easily verified factual errors? [8] Warning signs include using extensive automation to produce content on many topics, and covering many topics in the hope that some of them rank. [8]

That is where you review AI-written blog posts for fit, after the records check, not instead of it. Read the draft on your phone, the way a customer will.

1. Mark sentences that could describe any company in your trade. Replace them with a constraint you actually face, a question the front desk hears, or a step you actually perform. If you cannot add that detail, the section may not be worth publishing. Google flags pages that mainly summarize what others already say, without much of your own, as a search-first warning sign. [8]
2. Mark promises your staff would walk back. "We are always there the same day" and "every job includes a ten-year warranty" are operations statements. If dispatch cannot keep them, they do not belong in a post.
3. Mark a tone that is not yours. If your company is plainspoken and the draft is breathless, customers notice. So does the person who has to stand behind the page later.

If a tool did a substantial share of the writing, say so. Google asks you to consider explaining how automation was used, and why, when a reader would reasonably wonder how the piece was made. [8] [2] A short note is enough: a writing tool produced the first draft, and a named person checked services, prices, and service area against current records. Google strongly encourages a real byline where readers would expect one. [8] "The team" is not a name.

A pre-publish pass you can finish in one sitting

One person who knows the business can do this in a sitting. Ask a second person to skim when the topic is money, health, safety, or a legal promise. Google says trust is the most important of the qualities it groups as experience, expertise, authoritativeness, and trust, and that its systems give more weight to content with those qualities on topics that can affect health, financial stability, or safety. [8] Google also says E-E-A-T itself is not a specific ranking factor. [8] It is still a reason to slow down on those topics.

Use this order:

1. Read for the business before you read for grammar. Highlight every name, place, price, date, license, superlative ("best," "only," "guaranteed," "most"), and offer.
2. Confirm each highlight against a current source. If the source is a price sheet, either date the figure in the post or link to the page you update when prices change.
3. Open every link and every cited study. Because generated citations can be false even when they look formal, do not trust a footnote you have not opened. [1] If the page does not say what the draft claims, drop the claim. Do not swap in a different study you did not read.
4. Check scope. Does the post offer a service, a city, or a turnaround time you do not sell? Narrow it or cut it.
5. Check quotes and results against real customers and against what is typical, not against what would make a nicer ending. [5] [6]
6. Read the title, the meta description, and any text on images. Accuracy includes those fields, because they can appear in search results even when the reader never reaches your careful third paragraph. [2]
7. Read it once more for voice, then publish only if you would sign it.

If you ship many posts a week, run the pass on each URL. Google asks whether content is mass-produced, or spread across a large network of sites, so individual pages do not get as much care. [8] Scaled content abuse is many pages whose main purpose is manipulating rankings and that give users little value, including pages spun up with generative tools that way. [3] Publishing often is not the violation. Publishing mainly to manipulate rankings, with little value for the reader, is what that March 2024 explanation described, whether a person or a tool did the typing. [4]

Practical takeaways

• When you review AI-written blog posts, start with records you control: names, places, hours, licenses, and services. Style comes after the facts survive.
• Treat prices, discounts, "free" offers, guarantees, and result claims as advertising. Have objective proof before the post goes up, at the level of proof the sentence promises. [5]
• Delete invented staff, invented customers, and invented citations. Confident wording is not evidence, and a formal-looking source line can itself be false. [1]
• A machine-assisted draft is not automatically spam. Google's scaled content abuse policy targets many low-value pages produced mainly to manipulate rankings, no matter how they were made. [3] [4]
• Put a named person on the byline. When a tool did substantial drafting, say so in plain language where a reader would wonder how the page was made. [8] [2]
• If you would not say it on a sales call, do not publish it. If two sentences disagree, operations wins.

How we can help

Have more questions or want to get in touch? Our team helps small and mid-sized businesses put a human review step in front of anything that goes on the site, including posts drafted with writing tools, so the page that ships matches the services, prices, and service area you actually run. If you want to walk a live draft through this checklist, contact us. You can also see how we approach content and other day-to-day operations on our AI solutions page.

Citations

1. National Institute of Standards and Technology, "Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (NIST AI 600-1)" (2024-07-26)
2. Google Search Central, "Google Search's guidance on using generative AI content on your website" (2025-12-10)
3. Google Search Central, "Spam policies for Google web search" (2026-08-28)
4. Google Search Central, "What web creators should know about our March 2024 core update and new spam policies" (2024-03-05)
5. Federal Trade Commission, "Advertising FAQ's: A Guide for Small Business" (page current as fetched 2026-09-25; longstanding FTC small-business guidance)
6. Federal Trade Commission, "The Consumer Reviews and Testimonials Rule: Questions and Answers" (rule effective 2024-10-21; staff Q&A fetched 2026-09-25)
7. Federal Trade Commission, "Federal Trade Commission Announces Final Rule Banning Fake Reviews and Testimonials" (2024-08-14)
8. Google Search Central, "Creating helpful, reliable, people-first content" (2025-12-10)