Google's official stance since February 2023 is clear: they evaluate content quality, not production method. AI-generated text ranks fine if it meets their E-E-A-T criteria (experience, expertise, authoritativeness, trust) and serves search intent better than competing pages. The problem is most AI content doesn't clear that bar. Tools like ChatGPT and Jasper tend to produce surface-level summaries that regurgitate common knowledge without fresh data, specific examples, or a distinct point of view. That generic output loses to human-written content that includes original research, case details, or practitioner insight. We've seen AI drafts rank when they're heavily edited to add specificity—real numbers, local context, or contrarian takes—but raw AI output usually plateaus in the 15–30 position range because it lacks differentiation. The risks come from three places. First, AI models sometimes hallucinate facts or dates, and publishing misinformation destroys trust signals fast. Second, overuse of the same prompts across sites creates near-duplicate content clusters that Google may suppress. Third, AI prose often carries tell-tale phrases (comprehensive guide, in today's digital landscape, it's important to note) that signal low editorial oversight, which correlates with thin content even if it's not a direct ranking factor. At Ottawa SEO we use AI for research synthesis and first-draft speed, then layer in original data from our 500+ domain portfolio, client case patterns, and Canada-specific angles. That hybrid approach cuts production time by 40–60% while keeping the expertise and originality that actually move rankings. If you're publishing AI content, run it through a plagiarism checker, fact-check every claim, and ask whether a competitor could generate the identical article with the same prompt—if yes, you haven't added value.