Most website audits in India still check for the same things they checked five years ago: page speed, mobile responsiveness, broken links, and keyword placement. A useful audit in 2026 needs an additional layer that checks whether a page can be cleanly read, understood, and confidently reused by an AI system. Here is the checklist version of that layer.
Check your robots.txt and server logs for whether GPTBot, PerplexityBot, Google-Extended, and ClaudeBot are being allowed or blocked. Many Indian websites blocked these crawlers reflexively during early AI-scraping concerns and never revisited the decision, which silently removes them from consideration for citation entirely, regardless of content quality.
For your 10 most important pages, ask: if a model read only the first three sentences of each major section, would it get a correct, complete answer? If the real answer is buried two paragraphs down after scene-setting and context, restructure it so the direct answer leads.
Audit which pages carry Article, FAQPage, HowTo, Organization, and Product schema versus which have none. Free schema testing tools can validate implementation; the gap analysis (which page types are missing schema entirely) usually matters more than fixing minor errors in schema that already exists.
Check whether content is attributed to a named person with a linked bio, versus an anonymous "Team" or "Admin" byline. Verify that name, title, and company details are consistent across your website, LinkedIn, and any third-party directories, since inconsistency undermines the credibility signal even when each individual instance is accurate.
Check whether pages display a visible last-updated date, and whether that date is actually accurate relative to when the content was last substantively revised (not just a template that auto-updates on every deploy). This matters disproportionately for pricing, regulatory, and comparison content, where generative engines actively favour more recent information.
Check whether your company, product names, and key terms are used consistently across the site, or whether inconsistent naming (a product called three slightly different things across different pages) makes it harder for a model to confidently connect mentions of your brand across sources.
The same technical SEO issue that has always hurt rankings also confuses AI extraction: near-duplicate pages targeting slightly different keywords dilute which version a model treats as authoritative, and thin pages provide too little substance to be confidently cited over a more complete competitor page.
How to run this without new tooling: most of this audit can be done manually with your existing CMS, robots.txt, and a schema validator over one to two working days for a typical Indian B2B site of 50 to 150 pages. Start with your highest-traffic and highest-intent pages rather than attempting full-site coverage in the first pass.