Can you use AI to write your website content? What Google and Australian law expect

The short answer: Google judges the page, not the tool

Plenty of business owners now ask an AI tool to draft a service page, a blog post or a batch of meta descriptions, then wonder whether Google will hold it against them. Google's answer is direct. In its FAQ on AI content it says "Appropriate use of AI or automation is not against our guidelines", as long as it isn't used to generate content primarily to manipulate search rankings.

It doesn't work the other way either. The same FAQ says "Using AI doesn't give content any special gains. It's just content." A page drafted with AI is judged like any other page: if it's useful, original and trustworthy it might do well, and if it isn't, it might not.

So the real question isn't whether you used AI. It's whether the published page helps a customer decide, says things that are true about your business, and adds something they couldn't get from a hundred similar pages. The rest of this guide covers where AI helps, where it causes problems, and how to review a draft before it goes live.

Where AI genuinely helps with website content

Google's own guidance says generative AI "can be particularly useful when researching a topic, and to add structure to original content." That matches where it saves a small business the most time: turning your notes into a first draft, suggesting headings, tightening a long paragraph, or listing questions a customer might ask about a service.

The starting material matters more than the tool. If you give AI your actual process, the jobs you take on and don't, your service area, the questions your team answers every week and a real example from a recent job, the draft has something original to work with. If you give it only a keyword, you'll get the same generic page anyone else could generate.

A useful split is to let AI help with structure and wording while a person who knows the business supplies the substance and makes the final call.

Keep readingGive AI search clear facts about your business

Where AI-written content goes wrong

The biggest search risk is volume. Google's spam policies define scaled content abuse as "when many pages are generated for the primary purpose of manipulating search rankings and not helping users", and the first example listed is "Using generative AI tools or other similar tools to generate many pages without adding value for users". A set of near-identical suburb pages or fifty thin blog posts produced in an afternoon is exactly what that policy describes, however they were made.

The second risk is sameness. Google's guide to generative AI search describes commodity content as "often based on common knowledge", content that "typically adds little unique insight for readers", and tells site owners not to "just recycle what others on the internet have already said, or could easily be produced by a generative AI model." An AI draft with no input from you tends to land right there.

The third risk is plain error. Google warns that "generative models don't retrieve facts" and that outputs "may contain inaccuracies", and it says it's "critical to manually factcheck and review all AI-generated content for accuracy and trustworthiness before publishing." That review also applies to title elements, meta descriptions, structured data and image alt text, which AI tools are often asked to write in bulk and which can appear in search results.

AI-written claims are still your claims

Search rankings aren't the only thing at stake. Consumer Affairs Victoria says "It is unlawful to make false or misleading representations about products and services when supplying, offering to supply or promoting those products or services." That covers claims about the standard or quality of your services, testimonials, and any guarantee or warranty. A sentence an AI tool wrote becomes your representation the moment you publish it.

AI drafts are prone to exactly the claims that cause trouble: years in business, licences or memberships you don't hold, guarantees you don't offer, response times you can't meet, or a quote presented as coming from a customer. Consumer Affairs Victoria also notes that "A representation can be misleading even if it is partly true", so a confident sentence that's half right still needs fixing.

Testimonials need particular care. Never let a tool invent a review or a customer quote, and don't have it rewrite real ones beyond light, agreed trimming. Use customers' own words, with permission, and keep the originals.

Keep readingUse real testimonials without misleading anyone

Keep customer details out of public AI tools

It's tempting to paste a customer's email, a job summary or a set of reviews into a chatbot and ask it to turn them into a case study or testimonial. Be careful. The Office of the Australian Information Commissioner says "As a matter of best practice, the OAIC recommends that organisations do not enter personal information, and particularly sensitive information, into publicly available generative AI tools".

For website content, that's rarely a real limitation. Remove names, addresses, phone numbers and anything identifying before using a draft tool, and write the specific details back in yourself once the customer has agreed to be featured. A short written rule for your team about what can and can't go into AI tools saves a lot of guesswork.

Keep readingWrite a simple AI use policy for your team

Bylines, authorship and whether to say you used AI

Google encourages accurate authorship information, such as bylines, where readers would expect it, and it's firm about faking it. Its helpful content guidance says "Fabricating creator profiles (such as by using AI-generated headshots, made-up names, or false credentials to make content appear as if it was written by human experts) is a form of deception." Don't invent a staff writer or an expert reviewer. Put real names on content only when those people actually wrote or checked it.

On disclosure, Google's position is practical rather than a blanket rule. It says AI or automation disclosures are useful for content where someone might think "How was this created?" and suggests adding them when that would be reasonably expected. Its FAQ adds that giving AI an author byline is probably not the best way to make that clear.

For a typical service page that a person in the business has rewritten and approved, the page is yours and a disclosure usually isn't expected. If you publish something substantially generated by automation, such as an auto-written summary or product descriptions at scale, a short note on how it was produced helps readers judge it.

Worked example: an electrician's AI content plan, before and after

This is a hypothetical example, not a client story. A Ballarat electrician uses an AI tool to produce 30 suburb pages that each say the business offers "fast, reliable, fully licensed electrical services" in that suburb, plus 20 blog posts on topics like "10 electrical safety tips". The pages are near-identical, and two of them mention a 24/7 emergency service the business stopped offering last year.

The owner pulls the suburb pages and the blog posts, and starts again from the business. They record a 15-minute voice note on how switchboard upgrades actually work for them: when one's needed, what the inspection involves, what affects the cost, how long the job takes and what customers usually ask. They use AI to turn that transcript into a structured draft for a single switchboard upgrades page, then check every claim against what the business really does, add their licence details as they appear on the licence, and add a real photo of a recent job with the customer's permission.

AI also suggests a page title and meta description, which the owner edits so they match the page. The service areas go into one accurate section on the page instead of 30 copies. The result is one page that answers real questions in the business's own terms, rather than 50 that say nothing a competitor couldn't.

Keep readingCheck a service page against real customer questions

A review checklist before AI-assisted content goes live

Give one person who knows the business responsibility for approving every AI-assisted page, and run through this list before it's published. Google's helpful content guidance suggests asking whether content provides "original information, reporting, research, or analysis" and whether it has "any easily-verified factual errors"; the list below turns that into practical checks.

Demandify's ongoing SEO service combines content planning with technical and on-page maintenance, and that work starts from your real services and customer questions rather than a page count. This guide is general information, not legal advice; get advice for your specific situation.

Before you publish, check:

• Does the page answer a real customer question with detail from your own business?
• Has every fact, price, licence, guarantee and time frame been checked against what you actually offer?
• Are all testimonials, quotes and examples real, or clearly labelled as hypothetical?
• Were customer names and personal details kept out of public AI tools?
• Are the title, meta description, alt text and any structured data accurate for this page?
• Is this page meaningfully different from your other pages, rather than a reworded copy?
• Is any author name real, and would a reader reasonably expect a note on how the page was made?