I saw a CMO posting about how GEO and AEO have transformed their user acquisition strategy. It got me wondering-how many of us in large companies have had our jobs repurposed?
With traditional SEO, the rules were clear: crawling, indexing, rankings, links. You knew what to optimise. But now, with AI search, the questions become fuzzy. What outputs do you track beyond citations? Are we chasing keywords, intent, or categories? How do you test an AI's interpretation of your brand, especially when your own site and the wider web contain conflicting information?
For companies operating across multiple verticals, this gets messy fast. Imagine having 400 pages to analyse, spending 20-30 minutes each-that's a full-time effort just on assessment before any testing or deployment.
I'm curious what people are actually doing in practice. What are you reporting to leadership or clients as deliverables? Technical SEO used to mean helping search engines access pages. Now that AI understands more than just keywords, what does your test-stack look like?
Someone in the thread pointed out that we've moved from deterministic to probabilistic reporting. You can't prove a specific prompt led to a specific visit-you can only derive trends from event logs and prompt tracking tools. I've tried a handful of enterprise-focused tools recently and the ones that stood out for larger organisations include Profound, Scrunch, and Promptwatch. Promptwatch, which I use daily, offers detailed log tracking, sitemap linkages, and technical recommendations suited to bigger companies.
Your job has undoubtedly shifted, but there aren't many experts showing how technical AEO should work for large corporations in the age of AI. Maybe that will be you one day.
