Is it a good idea to generate informational content with AI?

Generating informational content with AI can be good for SEO, but not simply because it lets you publish faster. It is good when AI helps you research, structure, compare approaches and speed up drafts that are then reviewed with human judgement. It is bad when it is used to fill the blog with generic answers that add no experience, examples, data or clear connection to the business.

The important question is not whether Google allows or penalises content generated with artificial intelligence. The useful question is a different one: does this content deserve to exist even though an AI produced it? If the answer is no, the problem is not the tool, it is the editorial strategy.

At Queseo I already handle this as part of SEO content with AI: using automation to gain speed while keeping search intent, review, internal linking and a commercial reason behind every piece.

Short answer: yes, but with conditions

Yes, generating informational content with AI can be a good idea if three conditions are met: the topic has a role within the SEO architecture, the content offers something more than a rehash of the SERP, and there is a human review that improves accuracy, usefulness and focus.

Google has explained several times that its systems aim to reward helpful, high-quality content, regardless of how it was created. That does not automatically make AI a good strategy. It only means that the origin of the text is not the only criterion. A poor article written by a human may fail to rank; a well-crafted AI-assisted article can rank.

When it does make sense

• When the article answers a real question someone has before hiring a service.
• When it supports a commercial landing page or an important category.
• When it helps explain complex concepts more clearly.
• When it is used as a basis for creating guides, comparisons, checklists or processes.
• When it includes first-hand experience, examples, decisions and limits.

When it is usually a bad idea

• When it is published only to increase the number of indexable URLs.
• When it answers a question that Google already resolves in the SERP itself or in AI Overviews.
• When it does not link to or strengthen any important page on the site.
• When the content has no source, judgement or review.
• When every article follows the same pattern of introduction, generic lists and empty conclusion.

Informational content is not worth what it used to be

Informational content has lost some of its tactical value because many simple queries are now answered directly in Google, in featured snippets, in “People also ask” boxes or in AI-generated answers. This does not mean the blog is dead. It means that publishing basic information without a clear intent makes less and less sense.

In the past, a website could grow by creating lots of short answers to frequently asked questions. Today it pays to be more selective. If the query is too simple, the click may stay in the SERP. And if the article does not connect with a landing page, a solution or a commercial decision, the return will be low even if it earns impressions.

The problem with quick-answer searches

Questions such as “what is X”, “what is Y for” or “definition of Z” can attract traffic, but often they do not attract business. In sectors with AI Overviews, Google can put together a sufficient answer without the user visiting any website. For a small project or an SEO consultancy, basing the entire strategy on that type of query is usually a weak approach.

The value lies in the decision, not just the definition

An informational piece works better when it helps the user make a decision: whether to carry out an audit, when to create content, which mistakes to avoid, how much to invest, which tool to use or which alternative to choose. That kind of content is still informational, but it is more closely connected to the business.

That is why, before creating an article with AI, you should ask yourself which page it needs to strengthen. It could be a content marketing landing page, a page about artificial intelligence for SEO or a more specific service if the intent is already close to hiring.

How Google decides whether AI content deserves to rank

Google does not need to “hate” AI to filter out bad content. It only needs to detect signs of low usefulness: repetition, lack of originality, little depth, inaccurate information, no real experience, poor user satisfaction or patterns of mass publishing with no added value.

Quality and usefulness over method

Google’s official documentation consistently emphasises rewarding content that is helpful, reliable and created for people. AI can take part in that process, but it does not replace editorial judgement. A text can be well written and still add nothing new. That is one of the most common risks of automatically generated content.

E-E-A-T: experience, expertise, authoritativeness and trustworthiness

On topics where trust matters, AI tends to fall short if nobody adds real context. Explaining a theory is not enough. You have to show experience: project examples, prioritisation criteria, mistakes spotted, the limits of the recommendation and nuances that do not come from summarising the top positions on Google.

In SEO, for example, saying “use AI to create content” is not the same as explaining when I would use it, when I would not, how I would review a piece before publishing it and which signals I would look at afterwards in Search Console.

Scaled content abuse

The big risk is not creating an article with the help of AI. The risk is creating hundreds of similar URLs, with little oversight, to capture long tails without adding any real value. That is where AI becomes a form of low-quality spam, even if the text looks correct at first glance.

What informational AI content can work

AI works best when it is used to speed up parts of the process, not to hand over the whole strategy. It can help you open up avenues, organise information, spot questions, suggest structures and generate drafts. But the part that really ranks usually comes afterwards: editing, selection, examples, links, accuracy and commercial focus.

Decision guides

A guide that helps people decide is usually worth more than a definition. For example: when to use AI for SEO content, which types of content are worth automating, which reviews are mandatory or which topics should be written by hand.

Comparisons and alternatives

Comparisons let you bring in judgement. It is not just about saying “tool A vs tool B”, but about explaining when each option makes sense, what limitations it has and which mistakes keep coming up when choosing.

Checklists and processes

Checklists work well because they force you to get practical. If an article explains how to review a piece of content before publishing it, it can include steps covering search intent, structure, fact-checking, internal links, metadata and cannibalisation control.

Content that supports commercial landing pages

This is the most interesting use for many SEO projects. An informational article can strengthen a service landing page if it addresses an objection the user has beforehand. For example, a post on whether it is worth creating content with AI can support an SEO content page, an AI-for-SEO consultancy page or an SEO audit that identifies which content is surplus, missing or competing with other pages.

What informational AI content I would avoid

Not everything that can be generated should be published. The ease of production is precisely the danger: if publishing costs little, the filter drops. And when the filter drops, the blog fills up with pieces that help neither ranking nor conversion.

Definitions that offer nothing distinctive

If the article only defines a concept that is already explained on hundreds of sites, it will need a strong angle to justify publishing it. Without that angle, it will probably compete in a saturated SERP with few clicks available.

Posts made to chase volume without intent

A keyword with volume is not always an opportunity. If the user has no intention of hiring, comparing, deciding or going deeper, the traffic may be of little use. This is especially important on service websites, where the goal is not just to win sessions but to generate real opportunities.

YMYL content without expert review

On topics such as health, finance, legal matters or sensitive decisions, AI can make mistakes that look convincing. If there is no expert review, no sources and no clear editorial responsibility, it is not worth taking the risk.

Articles that cannibalise important pages

Another common mistake is creating informational posts that compete with service landing pages. Before publishing, you need to check whether the new URL strengthens the main page or steals its intent. If two URLs try to answer the same thing, AI will only have sped up an architecture problem.

My framework for using AI in informational content

When I use AI to create SEO content, I split the process into phases. AI can help in almost all of them, but it does not decide on its own what gets published.

1. Define the SEO role of the piece

Before the prompt, you need to know why the article exists. Is it going to capture a long tail? Address an objection? Support a landing page? Update a cluster? Tackle a question that appears in “People also ask”? If there is no role, there is no article.

2. Review the SERP and competitors’ structure

AI can summarise patterns, but it is worth looking at the actual SERP. You need to check which titles appear, which questions Google shows, whether there is an AI Overview, which formats repeat and how much depth competitors go into. For this type of query there are clear signals: Google’s official stance, helpful content, E-E-A-T, scaled abuse, human review, common mistakes and the relationship between SEO and GEO.

3. Create a structure with useful H2s and H3s

Good AI-assisted content should not stop at five generic H2s. If the topic has nuances, the structure should reflect them. H3s for decisions, mistakes, use cases, review criteria and examples. That depth helps the reader and avoids the typical pattern of shallow automated text.

4. Add first-hand experience

AI cannot make up this step. You need to bring in real judgement: what gets prioritised, what gets ruled out, what you have seen work, what usually goes wrong and how you would review it on a specific website. In an SEO for AI strategy, this part carries more and more weight because generative answers tend to reward clarity, authority and brand consistency.

5. Check data, links and metadata

Before publishing, I would review claims, examples, internal links, title, meta description, cannibalisation and CTA. I would also check whether the content needs a visible FAQ or whether it would just be filler. AI can suggest questions, but not all of them deserve to make the cut.

Checklist before publishing informational content made with AI

• The keyword has a clear intent and is not just a basic definition.
• The article strengthens a specific landing page, service, category or cluster.
• The structure responds to the SERP, not to a generic template.
• There are examples, your own criteria or editorial experience.
• Data, dates, tools and technical claims have been checked.
• Internal links are contextual and point to verified URLs.
• It does not cannibalise an existing commercial landing page.
• The title and meta description promise something the content delivers.
• The FAQ answers real questions and is not there out of habit.
• The content offers the user a sensible next step.

So, should you generate informational content with AI?

Yes, if you use it as part of an editorial system with a strategy behind it. No, if you use it as a machine for publishing URLs. AI can greatly reduce production costs, but the bar for publishing should go up, not down.

For a service website, my recommendation would be to prioritise informational content that sits close to a decision: costs, mistakes, comparisons, processes, checklists, objections and use cases. That kind of article can attract useful searches, link to commercial pages and help users understand when they need professional support.

If you want to use AI to create content without filling your website with generic pieces, it is best to start with a strategy: which landing pages need strengthening, which content is surplus, which queries have real intent and which review process guarantees quality before publishing. That is where an SEO in Valencia consultancy can separate useful automation from unfocused production.

Frequently asked questions

Does Google penalise AI-generated content?

Not simply because it was generated with AI. What can cause harm is publishing content that is low quality, unhelpful, inaccurate, repetitive or created at scale to manipulate results.

Does informational AI content rank?

It can rank if it responds well to search intent, offers distinctive value and has been reviewed. If it only summarises what other results already say, its chances will be lower.

How much AI content is acceptable in SEO?

I would not measure it as a percentage. What matters is editorial control: verified data, a useful structure, first-hand experience, correct links and a clear reason to publish the URL.

Is it better to create content with AI or hire writers?

It depends on the project. AI helps speed up research and drafts, but strategic, technical or brand topics still need human judgement. Often the best model is a hybrid one.