How long does this seven-step workflow take for a single article?

It is hard to give a fixed figure; it depends on the depth of the topic, how quickly you can reach real data and the editor's availability. In practice the longest part is not drafting but step four, gathering real examples and data, followed by language editing. AI shortens the writing time, but you give part of that time back to editorial review. To speed things up, finish topic selection and source gathering before drafting starts.

Should we tell readers that content was prepared with AI?

There is no labelling requirement for ranking purposes; as the article explains, the test is whether the text is accurate and original, not who produced it. A real author byline, the organisation's name and contact details do, however, build trust. In health, legal or financial topics, or where your own publishing policy requires it, being open about the process is a sensible choice.

What happens if an AI detector flags our text as AI-generated?

These tools give probabilities, not definitive answers, and they often misjudge plain, technical or formulaic Turkish text. Google does not rank pages according to their output, so a flag is not a reason for a penalty in itself. A high score does often mean the text is too generic. Rather than trying to fool the tool, add real examples, data and experience, then read the text again.

Which topics should never rely on an AI draft?

Be careful wherever a wrong sentence has a direct cost: regulation, contract terms, health and financial advice, technical product specifications, tax and pricing details. Do not leave organisation-specific claims such as client names, case outcomes or certificates to the model; write them only from documents you hold. On these topics, use AI at most for structure and headings, and have a person write and verify the claim itself against its source.

Is it better to update old content than to write new articles?

On most sites, yes, because pages that have already built up signals usually respond faster. List the queries that appear between positions four and fifteen in Search Console, pick the matching pages and apply the same workflow to update them. Keep the URL, add missing sections, correct outdated information and note the change date. Scaling up new content after this clean-up usually works better.

AI Content Production: Turkish SEO Guide 2026

"Will Google penalise AI-written content?"

The short answer: being AI-generated is not, by itself, a reason for a penalty. The real risk is content that adds nothing for the reader and is produced at scale to manipulate rankings.

Google set out its position in February 2023 on the Search Central blog, in "Google Search's guidance about AI-generated content": Google Search focuses on the quality of content, not on how it was produced; appropriate use of AI is not against its guidelines; using automation, including AI, to manipulate search rankings violates its spam policies. The spam policies call this "scaled content abuse": generating many pages for the primary purpose of manipulating rankings rather than helping users. One of the examples given is using generative AI tools to produce many pages without adding value for users. Links to both sources are at the end of this article.

So the question is not "did AI write it?"; the question is "is the content accurate, original and genuinely helpful, and who is accountable for it?".

In this article we share our content production workflow: where AI is used, where a person makes the decision, and how editorial review works.

Why AI content alone is not enough

Three reasons:

1. Hallucination (fabricated information) ChatGPT, Claude and similar models can fabricate small details (figures, dates, sources). For example, a model may produce an unsourced statistic such as "the market grew 47% last year". Wrong information damages readers' trust and exposes your business; every figure should be checked against a source before publication.

2. Generic voice By default, AI writes stock sentences: "In this article, we will discuss the important aspects of digital marketing." Text like this adds nothing original for the reader, so it tends to perform poorly.

3. Lack of topical depth AI stays shallow. Asked "How do you fix measurement in Meta Ads?", it offers five bullet points, but it cannot provide the specific, first-hand observation you would expect from a writer with real experience.

Our content workflow: 7 steps

Step 1: Topic selection (human, not AI)

AI does not decide "which topic should we write about?". That is a strategy and customer-insight decision.

For the right topic selection:

The most frequent questions from customer and support conversations
Winnable queries sitting between positions 4 and 15 in Google Search Console
Topics that competitors in your sector have covered poorly (keyword research tools help here)
Seasonal and current events (campaign periods, regulatory changes, etc.)

Step 2: Outline (with AI, under editorial control)

Have AI produce the outline, not the content. Example prompt:

Topic: "Fixing measurement in Meta Ads"
Target audience: e-commerce owners in Türkiye
Tone: Professional but human, expert tone
Request: An outline of 7 main sections. 2-3 sub-headings per section.
Condition: Do NOT write any statistics or figures. Topic headings only.

The editor reviews the outline, changes it and sharpens the flow.

Step 3: Section-by-section draft (AI)

Once the outline is approved, have AI write each section separately. Again, do not ask for figures. Example prompt:

Write the section: "Pixel is no longer enough — the post-iOS 14.5 measurement problem"
Length: 250-350 words
Style: Professional, no emojis, warm, short sentences
Condition: Do NOT write specific figures (the editor will add them with sources)
Condition: Stay at general-knowledge level, do not invent experience-based examples

This discipline reduces the risk of hallucination, but does not remove it; the editor remains in control.

Step 4: Human intervention — real data and examples

This step is critical. The editor and subject expert:

Add real figures and statistics, with sources
Add specific examples from their own experience (client information is used only with consent)
Add sector-specific knowledge and terminology
Check the basis of every claim

This step turns "generic AI text" into "expert opinion". That is the essence of Google's E-E-A-T framework (experience, expertise, authoritativeness, trustworthiness).

Step 5: Language and tone editing

Clean up the stock phrasing AI leaves behind:

"In conclusion" → delete it and state the conclusion
"As we discussed in this article" → delete it (the reader is already reading the article)
"It is an important topic" → say specifically why it matters
"In some cases" → say which cases
Passive sentences → make them active

This step usually makes the text shorter and clearer.

Step 6: SEO editing

Once the content is ready, go back to AI with a different goal:

Title tag suggestions
Meta description (around 150-160 characters)
Keyword variants for 5-7 sub-headings (H2/H3)
Internal linking suggestions (to relevant pages on your site)
Appropriate structured data (e.g. Article)

Note: Google no longer shows FAQ or HowTo rich results; this markup is harmless but should not be presented as a visibility promise. Google also says no special schema or separate file is needed for its generative AI search features.

Step 7: Publish and measure

Around 30 days after publishing:

Which queries is the page appearing for in Google Search Console?
How is average position developing?
Is the click-through rate sufficient? Does the title need revising?
Does it appear in the generative AI performance report in Search Console? There is no official measurement tool for other AI assistants; you can test manually in tools such as ChatGPT and Perplexity.

Update under-performing content at regular intervals.

The 5 most common AI content mistakes

Mistake 1: Requesting an article with a single prompt

"Write a 500-word article on how to optimise Meta Ads" usually produces text you cannot use. Follow the outline → section by section → editor workflow.

Mistake 2: Taking figures from AI

AI can fabricate statistics. Check every figure yourself and find its source. If you cannot find a source, do not publish the figure, and do not replace it with an estimated range either.

Mistake 3: No human touch at all

A five-minute skim adds nothing but typo fixes to AI output. The editor and subject expert need to read and correct the text properly; how long that takes depends on the depth of the topic.

Mistake 4: Having AI write personal stories

If AI writes anecdotes such as "in a conversation with our client, this happened...", they read as fake and are not true. These parts must be written by a person, based on real events that can be shared.

Mistake 5: Applying the same prompt to every topic

Every topic needs its own prompt strategy. Relying on a single template makes the content generic.

Which AI tool should you choose for Turkish content?

Model names, versions and prices change quickly, so we do not recommend specific tools. When choosing, test the candidates on three real topics from your own sector:

Fluency and grammatical accuracy in Turkish
Hallucination rate (check every figure and source it produces)
Ability to cite sources and state uncertainty openly
Data privacy terms (how the text you enter is stored and used)

Scale: how many articles per month are possible?

Output depends on the team, the topic and how long it takes to gather sources. AI shortens drafting time, but part of the time saved goes into verification and editorial review. Speed targets should not override content quality and editorial control; producing many similar pages for scale can breach Google's spam policies.

Conclusion: AI is the tool; people are accountable for the content

AI is a useful tool in content production, but the publisher is responsible for every sentence that goes live.

The right approach: use AI for the outline and first draft; let people handle figures, examples, experience and tone, and verify every claim against a source.

We can review your current content workflow together in a free 30-minute initial call. For the scope of our content and visibility work, see our SEO and GEO service; for social media content, see social media management, or get in touch.

Sources (last checked: 5 October 2026)

Google Search Central Blog: Google Search's guidance about AI-generated content (February 2023)
Google Search Central: Spam policies for Google web search (section "Scaled content abuse")

AI-Assisted Content Production: A Practical Guide for Turkish SEO (2026)