Creating a website with AI speeds up project launch, but it doesn't eliminate the need for basic SEO testing. Meta tags and microdata directly impact how search engines interpret pages and how users see the site in search results. Therefore, after generating the structure, it's worth manually adjusting the settings—this usually takes less time than subsequent "fixing" of the results. First, AI can generate meta tags based on templates or averages. For example, the title and description may not reflect the true focus of a particular page, and the canonical URL may be incorrect. As a result, the search engine receives a signal: the page is either a duplicate of another page or does not match the user's search intent. What exactly is important to check in meta tags? The minimum set typically includes: title, meta description, canonical, correct headings (H1), and (if necessary) indexing parameters like robots. For commercial and informational pages, it's crucial that the description isn't generic, but rather focuses on a specific service or topic, and that the title is unique enough to avoid looking like a repetitive template. Secondly, the microdata (Schema.org and related specifications) must match the page content. If, for example, the AI ​​has provided "Organization," "LocalBusiness," or "Product" markup without precise fields (address, phone number, price, availability, IDs), the search engine robot may partially ignore the markup or interpret the data differently than you expect. This reduces the chances of rich results in search results. Why AI can make mistakes with microdata Schemas require strict relationships between entities: correct types, filled-in required fields, correspondence with the actual content on the page, and consistent identifiers (e.g., author/organization URLs). On "autogenerated" websites, there are situations where the markup exists, but it doesn't align with the text, gallery, product cards, or contact information—especially on pages with dynamic blocks. Another factor is scale. On a small site, an error in a single meta tag is barely noticeable, but on dozens of pages, it can have a systemic impact on indexing and snippet quality. Manual checking allows you to quickly identify common issues: duplicate titles, empty descriptions, incorrect canonicals, incorrect language/locale, errors in markup structure, and missing markup where it's really needed (for example, for FAQs, articles, breadcrumbs, or product pages). Finally, SEO isn't just about the presence of meta tags and microdata, but also about their alignment with the goals of communicating with search engines and users. Properly written meta tags improve click-through rates, while microdata helps search engines more accurately interpret the meaning of a page. Together, this accelerates a website's ranking in relevant search queries and improves the quality of traffic. If you want to approach the verification process as safely and effectively as possible, start with an audit: compare the generated title/description with the actual page content, ensure the uniqueness of meta tags, check canonical links, and test the correctness of the microdata. This approach usually produces immediate results and prevents errors from accumulating after the AI's "quick start."