AI content affects SEO the same way any content does: Google ranks based on quality signals like expertise, user satisfaction, and originality, not whether a human or algorithm wrote it. The search engine's March 2024 guidance explicitly states they don't penalize AI-generated content by default. What matters is whether the content is helpful, accurate, and demonstrates first-hand expertise or original insight. The practical problem is that most raw AI output fails on those fronts. ChatGPT and similar models produce generic explanations anyone could generate, lack specific examples or data, and often hallucinate facts. If you publish 50 AI articles that all sound the same and add nothing new to the topic, you'll see poor engagement metrics (high bounce rates, low dwell time), few backlinks, and eventual ranking drops. Google's helpful content system is built to detect this pattern. Where AI works in SEO is as a drafting or research tool under human oversight. At Ottawa SEO, we use AI to outline content structures, generate meta description variations, or pull initial research, but every piece gets edited by someone who actually knows the topic. We add client-specific data, real examples from our 500-domain portfolio, and perspectives you won't find in ten other articles. That editorial layer is what separates content that ranks from content that gets buried. Watch out for these AI-content mistakes: publishing without fact-checking (models confidently state wrong information), ignoring E-E-A-T signals (no author bio, no credentials, no unique angle), and scaling content faster than you can maintain quality. If you're pumping out 20 AI posts a week with no subject-matter expert reviewing them, you're building a liability. One manual action or algorithm update can wipe out months of work. The short version: AI is a tool. A poorly-used hammer builds a bad house. Use AI to speed up research and drafting, then apply real expertise to make the content worth ranking.