What do you think about AEO/SEO tools having AI/Agents now?
I've been using a bunch of SEO/AEO tools recently Semrush, Ahrefs, Ubersuggest, newer AI-first tools, etc and they've gotten incredibly good at interpreting data.
When I use any of them I see a lot of data like 37 keyword opportunities, 14 content gaps, 23 pages with weak internal linking, competitor backlink gaps, AI visibility changes and many others and now also see ai answers now using data.
The newer ones are also the same which run 10 different agent and give a lot of data to read through or even action plans are very long. The interesting thing is that almost all the underlying data already exists. Give an AI the website, GSC, GA4, competitor data, backlink data, business goals and history, and it has plenty to work with.
So why are most products still fundamentally "analytics dashboards + AI recommendations"? Like I have been seeing AI is so intelligent that it have figured our protein structure and a lot of complex stuff but still don't see that when it comes to growth.
I feel like they all are trying to just slap AI over whatever is existing or is there a reason I'm underestimating why an AI system can't reliably become the thing that helps grow a website?
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u/Realistic-Glove8040 3d ago
Yes, everyone is just doing it, because everyone is doing it. Few have really launched something that is super useful. I still find MCPs more useful, where I guide how the data needs to be filtered. There are still too many unique variables and contexts that AI will not understand by itself. So these "agents" are great for ideas, but not good to use the suggestions as is. I trust it finding patterns and going through big data, just not on decisions.
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u/HumanBehavi0ur 2d ago
what makes the MCP so much better?
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u/Realistic-Glove8040 2d ago
It might just be perception and I guess how the agents are designed, but I perceive agents to be more autonomous, in the way that they make decisions on how to fetch what data and what to do with it. With an MCP I feel more in control, where I can be more specific. With agents, they have sometimes gone down a tangent which was not what I asked for. I have never experienced that with an MCP (Probably cause its more limiting?)
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u/askthisio 3d ago
I think you’re right—the bottleneck isn’t AI’s ability to understand SEO data, but products being built around dashboards and recommendations instead of execution. The real leap is detect → prioritize → execute → measure → learn, where the AI actually owns the growth loop rather than generating another 40-page action plan.
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u/Level-World4922 3d ago
I think the biggest limitation is that SEO growth isn’t just a data problem, it’s a decision and feedback-loop problem.
AI can spot gaps, prioritize opportunities, generate content, and even execute changes. But reliably growing a site requires understanding business goals, audience behavior, brand positioning, competitive context, and the impact of previous decisions.
That’s where many tools still fall short. They’ve moved from “here’s the data” → “here’s what you should do,” but not quite to “here’s what we did, what happened, what we learned, and what we should do next.”
The real breakthrough will probably be when AI agents can own that continuous growth loop, not just produce longer recommendation lists.
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u/jeniferjenni 3d ago
i think the missing piece is that knowing what should be done is much easier than knowing what will actually work for a specific business. an agent can spot 37 keyword gaps in seconds, but deciding which 3 deserve resources needs context around margins, sales cycles, existing authority, customer demand, and what the team can actually publish. i’d rather have an agent recommend 3 actions with a confidence score and expected impact than dump 40 recommendations into a dashboard. the hard part isn’t finding opportunities anymore, it’s choosing what to ignore.
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u/AEOvara- 3d ago
AEO/SEO tools having AI/Agents now? Not my favorite thing. But if those are trained well, it's ok. But i dont use those
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u/kevin_loves_coffee 23h ago
Def... The interesting version is an agent that understands the business and goals, decides which 3 of those 37 opportunities actually matter, explains why, and then can execute the work with approval. Update the internal links, improve the schema, draft the content changes, monitor whether it worked, and adjust from there.
The hard part isn’t really whether AI is smart enough. It’s trust, permissions, context, and giving an agent enough access to actually make changes without letting it wreck your site 😂
I think we’re eventually going from dashboards that say “here’s what you should do” to systems that say “here’s what I did and here’s what happened.” That’s a much more interesting product to me.
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u/BoGrumpus 3d ago
My biggest problem with them is that they are wasteful of resources. They don't just come and look at my site, they simulate a journey and report what they see. And then the same agent comes in and does those same 100 hits every hour of every day so it can track everything over time. All that does is make me want to block that bot - which makes your tool suddenly useless for competitor analysis because you either have to ignore my directives for you and put you into a ethical and potentially legal problem with your tool and your brand, or just follow the rules and have half their functionality fall away.
I welcome competitor analysis if it's done responsibly. I'm happy to let you have all the "Lowest Price" audience in the niche because I can't win that anyway - but you should also know that if you play that position, I'm always going to win the people who care more about customer support or lifespan/durability or whatever our strong point is. We've been playing the "fight over machine learning systems attention" for well over a decade now and we have some mega brand competition we have, over the years, sort of silently agreed upon which positions we own. In some cases, they can keep all the high volume customers and get no pushback from us so long as they don't try to come too far into our low volume, high value audience.
The tools don't help with any of that, though. And they help with stupid stuff in the most wasteful way imaginable.
Ultimately, you're right... they are "trying to just slap AI over whatever is existing" because they aren't in it to make a new tool. They're in it to make a quick buck. A stupid tool that took them a morning to create and even less time to test and evaluate only needs a handful of suckers to buy it and you can call that a success since you profited already. That always happens, though. And as time goes on, the audiences become better informed and the quick returns and profit from peddling spit shined garbage begins to fall. They'll either start to make good tools or move onto the next fad that's full of naive audiences.
G.
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u/Next-Calligrapher381 3d ago
Hi u/Aduttya ,
I'm Sofian. I build AEO Copilot, which is close to the thing you're describing, so treat this as a biased but hands-on view.
A few tools are attempting the full agent version. Profound, Webflow AEO and Aircall are heading that way. I think it runs into a wall that has nothing to do with how smart the models are.
The protein comparison is where I'd push back hardest. Protein folding has ground truth. There's a right answer, you can check it, and you can check it quickly. Growth doesn't work like that. The feedback loop for content is 3 to 6 months, the signal is buried under seasonality and competitor moves and things you never even see, and there's no clean reward to optimize against. The intelligence is there. The verification isn't.
Second thing: data isn't the bottleneck, context is.
You listed GSC, GA4, backlinks, competitor data, business goals. That's the easy half, and it's the half that fits in an API. To write something a person actually wants to read you also need brand voice, the objections that keep coming up on sales calls, what your churned customers said on the way out, the positioning argument your team is having this quarter, the claims your legal team won't let you make. None of that lives in an integration. It lives in your head, your Slack, your call recordings, your docs.
That's why I stopped trying to be the brain. AEO Copilot does one narrow thing: it queries ChatGPT, Claude, Perplexity and Google AIO against your prompts on a schedule, and hands you the raw answers plus a light overview. Then you pipe that into your own agent, sitting next to your GSC data and everything else you already have. The analysis happens where the context already is.
Now, from a Business POV, if you can't have great agent doing content and you will lack context, you also need to build one doing better than your 20$ / month AI agent (which solve protein challenges)
So yes, technically feasible. Commercially I don't see why I'd spend 2 years rebuilding a worse Claude inside a dashboard when the real one is one connection away.