Technical SEO covers a broad range of topics:

• Crawlability: Can Google reach and index all pages?
• Site speed: Does the site load fast enough on mobile and desktop?
• Structured data: Is schema markup correctly implemented?
• Canonicalisation: Which URL is the primary version of a page?
• Redirects: Are 301 redirects correctly set up when URLs change?
• Hreflang: Is the language attribution correct for multilingual sites?
• Core Web Vitals: Does the site meet Google's performance standards?

These are technical questions typically solved by developers and technical SEO specialists.

AI has several useful applications within technical SEO:

Crawl data analysis: AI can analyse large volumes of crawl data from tools like Screaming Frog and identify patterns, such as pages being systematically skipped or status code errors concentrated on a specific page category.

Schema markup generation: AI can generate JSON-LD markup for common schema types (Article, FAQ, Product, LocalBusiness). You provide the content, AI generates the markup.

Hreflang checking: AI can analyse a hreflang implementation and identify inconsistencies in the language attributes.

Technical documentation: AI can help write technical specifications for developers based on SEO requirements.

Pattern recognition in log files: AI can analyse server log files for Googlebot crawl patterns.

One of the most useful AI applications is generating schema markup. Give AI the content of a page and the instruction: "Generate JSON-LD markup for this FAQ block in schema.org format." The output is directly usable but must always be validated via Google's Rich Results Test.

The same applies to Product schema, Article schema or LocalBusiness schema. AI creates the framework, a technical SEO specialist validates the implementation.

AI cannot make website changes. It provides advice and generates markup, but cannot modify server settings, deploy code or adjust crawl settings.

With more complex technical questions, AI is also limited:

• Page speed optimisation: Rendering performance, Critical Rendering Path, Core Web Vitals fixes require hands-on development work
• Migrations: URL migrations, server migrations or CMS migrations with SEO impact require careful manual planning
• Custom situations: Technical SEO problems are often site-specific. Generic AI advice falls short here

Mach8 combines AI analysis with technical expertise for clients wanting to improve their technical SEO.

The most meaningful way to use AI for technical SEO is as an analysis tool: searching through large volumes of data, recognising patterns and formulating hypotheses. Execution requires a technical specialist who translates findings into concrete adjustments.

This makes AI useful as part of a broader technical SEO workflow, not as a replacement for it.

AI is a valuable complement to technical SEO work, particularly for data analysis and generating structured data. But complex technical execution remains human work. Anyone expecting AI tools to replace technical expertise will find the results disappointing.

Want to combine technical SEO and AI content in one approach? View our SEO content services or get in touch with Mach8.