I asked seven AI engines for a mortgage recommendation. The results looked surprisingly old-school.

It’s understandable why there are so many articles on AI lately. Consumers increasingly ask ChatGPT, Claude, Gemini and other AI platforms questions they once typed into Google. So the new popular acronym – AEO (answer engine optimization) – for optimizing web content around AI engine results and recommendations is addressing a very real concern. But after running a small experiment, we’re probably making AEO more complicated than it currently is. I asked seven major AI platforms essentially the same question: “Who do you recommend to get a DSCR (debt service coverage ratio) loan from in Knoxville, Tennessee?” I deliberately chose a product and market where I should theoretically have been competitive. I actively originate DSCR loans, and I operate a website specifically devoted to rental property financing. I wasn’t in any of the seven engines’ recommendations. I wasn’t surprised I lost, but I was surprised by who beat me, and how familiar their tactics were. Some platforms surfaced large national investment property lenders. Others found brokers, specialty lenders or smaller lending websites. But many businesses being recommended didn’t have any connection to the Knoxville area. ...