A new article from Search Engine Journal describes a practical way some SEO professionals are using AI: not as a full replacement for specialists, but as a support layer inside technical audit workflows. The model presented is simple: use deterministic tools to identify technical facts, a local large language model to help explain those findings, and a human expert to decide what matters and what action should follow.

For European businesses, this is relevant because many marketing and web teams are under pressure to increase output with AI while avoiding inaccurate recommendations, brand risk and poor website changes. In SEO, where technical decisions can affect traffic, conversion and visibility, that distinction matters.

What happened

According to the Search Engine Journal article, one technical SEO workflow splits tasks into three layers:

• Deterministic checks to verify factual issues such as crawl, indexation or page-level technical signals.
• A local LLM to turn those findings into explanations that are easier to review and discuss.
• Human judgement to assess business relevance, prioritise fixes and avoid weak or misleading conclusions.

The underlying point is not that AI can perform SEO end to end on its own, but that it can reduce manual effort around interpretation and communication when used within a controlled process.

Why it matters for European businesses

Many SMEs, e-commerce businesses and in-house marketing teams are experimenting with AI for SEO, content and website optimisation. The practical challenge is that SEO contains both measurable technical facts and context-dependent decisions.

AI can help summarise site issues, explain technical findings for non-specialists and support internal reporting. However, businesses still need people to validate recommendations against commercial priorities, website architecture, analytics data and brand considerations.

This is especially important for companies operating across multiple European markets, languages and CMS setups. Automated outputs may sound convincing but still miss local search intent, multilingual site complexity or the business trade-offs behind technical changes.

The workflow described also aligns with a broader business need: using AI where it adds efficiency, while keeping accountability with people. For agencies and internal teams, that can mean faster audits without fully outsourcing judgement to a model.

Who may be affected

• SMEs using AI tools to reduce SEO and content costs.
• E-commerce companies managing large catalogues, faceted navigation and technical SEO complexity.
• Marketing teams that need to translate technical website issues into business actions.
• IT and web teams responsible for implementing fixes suggested by SEO tools or AI systems.
• Digital agencies building repeatable audit workflows across multiple client websites.

What companies should consider

• Separate facts from interpretation. Use established crawlers, analytics platforms and technical tools for factual checks rather than relying on an LLM to detect issues on its own.
• Use AI for explanation, not final authority. LLMs can help draft summaries or prioritisation notes, but recommendations should still be reviewed by someone with SEO and business context.
• Check implementation risk. Technical SEO changes can affect templates, internal linking, page rendering and tracking. Review proposed fixes before deployment.
• Consider privacy and data handling. If audit data is sent to third-party AI services, companies should review supplier terms, access controls and data protection implications.
• Build repeatable internal workflows. The greatest value may come from standardising how teams audit, explain and approve changes, rather than from using AI as a standalone decision-maker.

For European businesses, the practical lesson is clear: AI can improve SEO productivity, but reliable performance still depends on structured processes and expert review. Companies looking to scale website optimisation should focus on human-supervised workflows rather than assuming AI can replace technical and strategic judgement.