Google's official position (Search Central, 2023): the way content is made is not relevant — quality is. Google's systems are designed to reward helpful, reliable, people-first content, regardless of whether a human or AI wrote it.

Concretely this means:

• AI content that is informative, accurate and well-structured can rank well
• AI content that is generic, superficial or factually incorrect ranks poorly
• Bulk spam — large quantities of thin content without value — is actively downranked

The criterion is quality, not origin.

Depth and specificity: Generic content about a broad topic performs poorly. Content that thoroughly answers a specific question performs better. AI can do this — provided you make the prompt specific enough.

E-E-A-T signals: Google evaluates Experience, Expertise, Authoritativeness and Trustworthiness. AI content naturally lacks personal experience. You can compensate by:

• Adding concrete examples and figures
• Human editorial review
• Author pages with genuine expertise background

Unique insights: Purely AI-generated content is a remixing of existing content. Add original data, client cases or insights that cannot be found elsewhere.

Technical SEO structure: Correct heading hierarchy (H1, H2, H3), internal links, meta titles and descriptions. AI can follow this structure if you instruct it to.

AI is good at naturally integrating search terms into text — better than many human writers who tend toward keyword stuffing. The approach:

1. Do your keyword research first (AI can help, but validate with tools)
2. Include the primary keyword and semantically related terms in the prompt
3. Specify where the primary keyword should appear (title, first paragraph, H2s)
4. Let the model naturally integrate the rest

Avoid explicit density instructions ("use the keyword 15 times") — this leads to unnatural texts.

• Informational guides: "What is X", "How does Y work" — AI can produce broad informational content
• Comparison pages: Comparing products, services or options — structurally strong
• FAQ pages: Direct answers to specific questions — good for featured snippets
• Product category texts: E-commerce category descriptions at scale
• Local landing pages: The same basic structure, adapted per city or region

• Factual verification: AI hallucinates statistics and sources. Always check
• Unique angle: Add perspective that exists nowhere else
• Brand-specific tone: Consistency with your content strategy and brand personality
• Current information: AI training data has a cutoff date; update time-sensitive content

1. Keyword research and prioritisation (manual or with AI tools)
2. Content briefing per article (topic, purpose, target audience, search term)
3. AI generation based on briefing
4. Human review and addition of unique insights
5. Publication and monitoring of rankings

This process makes it possible to produce 10x more content without 10x more editorial staff.

AI SEO content works — but only if you see it as a production accelerator, not a fully automated solution. The best results come from collaboration: AI produces the skeleton, humans add the detail and uniqueness that actually ranks.

Curious what an SEO content workflow could look like for your organisation? View our SEO content service or schedule a call.