“Can we publish content that AI drafted, and who has to look at it first?”
Yes. A medical practice can publish content drafted with artificial intelligence if two people review it first. A licensed provider checks every clinical statement, and a staff member checks every fact about the practice. Google evaluates the quality of the published page, not whether AI helped write it. What matters is whether the page is accurate, whether it offers information patients cannot find on other practices’ websites, and whether someone at the practice is willing to put their name on it.
This article covers the review step in our series on AI for medical practice marketing. It assumes your staff already follow the rules for using AI chatbots under the Health Insurance Portability and Accountability Act (HIPAA), so no patient information was entered when the draft was created.
Where AI helps in content production
An AI model can produce an outline from the patient’s question and your brief. You will likely rewrite about half of it, but editing an outline takes a few minutes, which is faster than starting from a blank page.
The model saves the most time when it writes a first draft from your knowledgebase, which is the collection of verified documents about your practice described in the first article of this series. When the model works from your service descriptions, provider biographies, locations, and brand voice rules, the draft reflects your practice. Without that material, the draft reads like generic content that could appear on any practice’s website.
An AI model can also rewrite technical language for patients. A provider may write a paragraph the way they would explain the topic to a colleague, and the model can rewrite it in plain language for the provider to check. The model can also turn an approved article into other formats, such as a frequently asked questions section for a service page, social media captions, or a patient email, which is how a single reviewed article feeds an entire content marketing program. Shortening content can remove an important qualifier, so a staff member should compare each new version with the approved article before it is published.
Where AI fails with medical content
AI models also make errors that the review step is designed to catch. A model is trained on data collected up to a fixed date, so a draft may describe a screening interval, medication, or society guideline as it was before a recent change, and the model will not flag the difference.
AI models can also cite studies that do not exist, and the fact-checking section below shows how often this happens. When asked to write about a service, a model fills in information it does not have, such as a procedure the practice does not perform, a location that does not offer the service, or an insurance plan the practice no longer accepts.
Drafts written without practice-specific material also tend to be generic. Google’s guide to its AI search features describes commodity content as content that is “based on common knowledge, which could originate from anyone” and that “typically adds little unique insight for readers.” A draft written from a one-line prompt usually fits that description.
Do I need someone to review AI content?
Yes. Each AI-assisted page needs two reviewers, because checking clinical accuracy and checking practice details require different knowledge.
A licensed provider reviews every clinical statement, including how the condition is described, how the procedure works, the risks, the recovery, and whether any outcome is promised. The provider’s name and license are associated with the page, and this review usually takes about fifteen to twenty minutes for a standard blog post.
A staff member, usually the office manager, reviews practice facts and compliance. This review covers provider names and credentials, services by location, insurance plans, hours, phone numbers, links, and any rules your attorney or specialty board has set about marketing claims. The office manager knows the practice’s details better than the physician and is more likely to catch an error such as a wrong suite number.
After both reviews, publish the page with a line that names the reviewer, lists their credentials, and gives the review date. The line shows patients, and anyone else evaluating the page, that a qualified person checked the information. Provider review is a fixed step in our medical content engine for the same reason.
Will AI fact-check my content?
No. An AI model should not be the reviewer of record, and it should not be the only check between a draft and your website. A 2026 study published in The Annals of the Royal College of Surgeons of England reviewed 1,249 references from 108 chatbot answers to common surgical questions. In the worst-performing models, 34 percent of the references were fabricated or could not be verified. Several other models produced no fabricated references, and the advanced reasoning versions produced better references than the standard versions. Because accuracy varies this much between models and versions, a reviewer still needs to check every citation.
An AI model with web search can help with fact-checking. It can list the claims in a draft that need checking and suggest where to find sources, which makes it a useful first pass. The reviewer still needs to open each source, read the relevant section, and confirm that the source supports the claim as written. If the reviewer cannot find a source for a claim, the claim should be removed.
Does Google penalize AI content?
No. Google evaluates content by its quality, not by how it was produced. Google’s 2023 guidance on AI-generated content says its systems reward high-quality content however it is produced. The same guidance says that using automation, including AI, mainly to manipulate search rankings violates Google’s spam policies.
The spam policy that applies most directly to AI-drafted content is scaled content abuse. Google’s guidance states that using generative AI tools to produce many pages without adding value for users may violate this policy. Publishing twenty pages about the same condition, each targeting a slightly different search phrase and drafted from the same prompt, is the kind of pattern the policy describes. A single reviewed page that answers a question patients actually ask does not fit that pattern.
Google’s AI optimization guide, updated July 10, 2026, also recommends non-commodity content, which it describes as content that “provides unique expert or experienced takes that go beyond common knowledge.” A page based on a provider’s actual experience with a service fits that description. A page generated from a prompt alone is unlikely to fit it, even after careful editing.
How to make AI-assisted content worth ranking and citing
To give an AI-assisted page a better chance of ranking in search results and being cited in AI-generated answers, add information that only your practice can provide. This is the part of SEO and local search visibility that no tool can automate. A short interview with the provider before drafting begins is the most direct source. Ask the provider about the topic, including what patients often misunderstand, what the provider explains at the first visit, and what tends to surprise patients. Record the answers and add them to the brief, so the draft includes statements that no other practice’s page contains. The interview should take twenty minutes or less.
The page should also describe how your practice performs the service. Most websites explain how a procedure works in general, while your page should explain what a patient can expect at your practice, including the consultation, the preparation, who they will see, how long the visit takes, and what happens afterward. The questions patients ask your front desk about the topic belong on the page as well, answered in the order patients usually ask them.
Pre-publish review checklist
Print this checklist. Both reviewers should initial it, and the initialed copy should be kept in the approval log.
- Every claim and statistic is traced to a source the reviewer opened, and the date of the data is noted.
- The reviewing provider has confirmed procedure details, including risks and recovery.
- Provider names and credentials are spelled and formatted as they appear on the provider’s license.
- Services are listed only at the locations that offer them.
- The page contains no outcome guarantees, no before-and-after claims, and no comparisons with other practices.
- The page contains no patient information of any kind.
- The page includes a reviewed-by line with the reviewer’s name, credentials, and the review date.
If an error is published, it appears under your practice’s name, and patients will hold the practice responsible for it. The two reviews exist to prevent that. Choose your clinical reviewer and your practice reviewer today, and give them this checklist before the next draft is ready. If you would rather have a team that already runs this process, our strategy and foundation work sets up the reviewers, the knowledgebase, and the approval log for you.
Net One Click works exclusively with medical practices. If you’d like to talk about how we can help build and grow your practice, book a free consultation.
