Key takeaways
- Traditional SEO keyword tools (Semrush, Ahrefs, Moz) are built for Google rankings -- they don't tell you what prompts people type into ChatGPT, Claude, or Perplexity.
- AI search engines cite content based on topical authority, question coverage, and citation patterns -- not just keyword density or backlinks.
- A new category of GEO (Generative Engine Optimization) tools has emerged specifically to track and improve AI search visibility.
- The best approach in 2026 is a hybrid: use traditional tools for Google SEO fundamentals, then layer in GEO tools to optimize for AI citation.
- Prompt-based research -- understanding what questions AI users actually ask -- is the new keyword research.
There's a version of this guide that could have been written two years ago. It would have ranked Semrush first, praised Ahrefs for its backlink database, given Moz credit for Domain Authority, and called it a day.
That guide would be wrong now.
Not because those tools got worse -- they didn't. But the question has changed. "How do I rank for keywords?" has quietly become "How do I get cited by ChatGPT?" And those are very different problems.
This guide covers both. We'll look at what the traditional tools actually do well (and where they fall short for AI search), then walk through the GEO alternatives that are purpose-built for the new reality.
Why traditional keyword tools don't solve the AI ranking problem
Semrush, Ahrefs, and Moz were designed around one core assumption: Google is the search engine that matters. You find keywords people type into Google, you optimize pages for those keywords, and you track where those pages rank in Google's results.
That model still works for Google. But AI search engines like ChatGPT, Perplexity, Claude, and Gemini don't work the same way. They don't return a list of ranked URLs. They synthesize an answer and cite sources they consider authoritative and relevant. The "ranking" question becomes: does your content get cited in the response, and does your brand get mentioned favorably?
Three things drive AI citation that traditional keyword tools don't measure:
- Whether your content directly answers the specific prompts people type into AI tools
- Whether AI crawlers can actually access and read your pages
- Whether your brand appears in the sources AI models already trust (Reddit threads, YouTube, third-party review sites)
None of that shows up in a keyword difficulty score.
The traditional tools: what they're actually good for
Before writing them off, it's worth being precise about what Semrush, Ahrefs, and Moz still do well -- because the fundamentals of good content still matter for AI citation too.
Semrush
Semrush has the broadest feature set of the three. Its keyword database is enormous, its competitor analysis is genuinely useful, and the Content Marketing Toolkit helps with topic research and content briefs. If you want to understand what your competitors rank for on Google, Semrush is hard to beat.
Where it falls short: the keyword data is Google-centric, the prompts it uses for any AI tracking are fixed (you can't customize them to match how your actual customers ask questions), and there's no AI traffic attribution to connect visibility to revenue.
Pricing starts at $139.95/month, which is a lot if your main goal is AI search visibility rather than traditional SEO.
Ahrefs
Ahrefs is the tool most SEO professionals reach for when they want reliable data. Its backlink database -- 28.7 billion keywords, 380 billion indexed pages -- is genuinely impressive, and its keyword difficulty scores are considered more accurate than Semrush's by many practitioners.
The Brand Radar feature does offer some AI search monitoring, but it uses fixed prompts and has no AI traffic attribution. You can see some data, but you can't customize what you're tracking or connect it to actual business outcomes.
The credit system is another friction point. You can burn through credits quickly when analyzing large domains, which makes exploratory research frustrating.
Moz
Moz is the most approachable of the three. Domain Authority and Page Authority remain widely used metrics, and the interface is genuinely easier to learn than Semrush or Ahrefs. For teams that are newer to SEO or have simpler needs, Moz Pro at $49/month is a reasonable starting point.
But Moz has less depth than the other two, and it has essentially no AI search capabilities. It's a solid Google SEO tool and not much more.
How the three compare head-to-head
| Feature | Semrush | Ahrefs | Moz Pro |
|---|---|---|---|
| Keyword database size | Very large | Very large (28.7B keywords) | Large |
| Backlink analysis | Strong | Best-in-class | Good |
| AI search monitoring | Limited (fixed prompts) | Limited (Brand Radar, fixed prompts) | None |
| AI traffic attribution | No | No | No |
| Content generation | Basic | None | None |
| Ease of use | Moderate | Moderate | Easiest |
| Starting price | $139.95/mo | $129/mo | $49/mo |
| Best for | Breadth, competitor research | Accuracy, backlinks | Simplicity, DA/PA metrics |
The honest summary: Semrush leads on breadth, Ahrefs leads on accuracy, Moz leads on simplicity. But none of them were built for AI search, and it shows.
What "keyword research" actually means for AI ranking
When someone types a query into ChatGPT or Perplexity, they're not typing a keyword. They're asking a question, often a long and specific one. "What's the best project management tool for a 10-person remote team with a tight budget?" is a prompt, not a keyword.
AI models respond to these prompts by pulling from content that directly and comprehensively answers the question. That means the research task isn't "find keywords with high volume and low difficulty." It's "find the specific prompts your target audience is typing into AI tools, then create content that answers those prompts better than anyone else."
This is a meaningfully different workflow, and it requires different tools.
GEO tools built for AI search visibility
A new category of platforms has emerged to handle this. They vary a lot in depth -- some are basic monitoring dashboards, others are full optimization platforms. Here's how the main ones stack up.
Promptwatch: the full-loop option
Promptwatch is the platform that goes furthest beyond monitoring. Where most tools show you data and leave you to figure out what to do with it, Promptwatch is built around an action loop: find the gaps, create content that fills them, then track whether it worked.
The Answer Gap Analysis is particularly useful for the "keyword research" equivalent in AI search. It shows you exactly which prompts your competitors are appearing in that you're not -- the specific questions AI models are answering without citing your content. That's the closest thing to keyword opportunity research that exists for AI search right now.
The built-in AI writing agent then generates content grounded in actual citation data (880M+ citations analyzed), so the output is engineered to get cited rather than just to fill a content calendar. And the crawler logs show you which AI crawlers are hitting your site, which pages they're reading, and whether they're hitting errors -- the kind of technical visibility that most tools don't offer at all.
Pricing: $99/mo (Essential), $249/mo (Professional), $579/mo (Business).
Otterly.AI
Otterly.AI is a more affordable entry point for AI visibility monitoring. It tracks brand mentions across several AI models and gives you a basic sense of where you're appearing. Good for teams that are just starting to pay attention to AI search and want a low-cost way to monitor.
The limitation is that it stops at monitoring. There's no content gap analysis, no content generation, and no crawler logs. You can see where you're invisible, but you're on your own to fix it.
Profound
Profound targets enterprise teams and has a strong feature set for monitoring AI visibility at scale. The data is solid and the reporting is detailed.
It's more expensive than most alternatives and, like Otterly, is primarily a monitoring tool. Content optimization and generation aren't part of the workflow.
SE Ranking
SE Ranking sits in an interesting middle ground. It's a traditional SEO platform that has added AI visibility features, so it can handle both Google rank tracking and some AI search monitoring in one place.
If you want to consolidate tools and don't need deep AI search capabilities, SE Ranking is worth a look. The AI features are less developed than dedicated GEO platforms, but the overall value for the price is good.
Scrunch AI
Scrunch AI focuses on monitoring how AI assistants like ChatGPT and Claude represent your brand. It's particularly useful for brand sentiment tracking in AI responses.
GEO tools comparison
| Tool | AI models monitored | Content gap analysis | Content generation | Crawler logs | Starting price |
|---|---|---|---|---|---|
| Promptwatch | 10+ (ChatGPT, Claude, Perplexity, Gemini, Grok, etc.) | Yes | Yes (AI writing agent) | Yes | $99/mo |
| Otterly.AI | Several | No | No | No | Lower tier |
| Profound | Several | Limited | No | No | Enterprise |
| SE Ranking | Several | No | No | No | $65/mo |
| Scrunch AI | Several | No | No | No | Varies |
| Ahrefs Brand Radar | Limited | No | No | No | Add-on |
| Semrush | Limited (fixed prompts) | No | Basic | No | $139.95/mo |
Complementary tools worth knowing
Beyond the main platforms, a few specialized tools are useful for specific parts of the AI keyword research workflow.
For question-based keyword discovery: Answer Socrates pulls from Google Autosuggest, People Also Ask, and Google Trends to surface real questions people are asking. It's not an AI search tool per se, but the questions it surfaces often overlap with what people ask AI models. At $9/month, it's a cheap complement to a GEO platform.
For content optimization: Surfer SEO and Clearscope are strong for optimizing content once you know what to write. They won't tell you what prompts to target in AI search, but they help ensure the content you create is well-structured and comprehensive.
For topical authority building: Topical Map AI helps you plan content clusters that establish authority on a topic -- which matters for AI citation because models tend to cite sources that cover a topic comprehensively rather than just one angle.
For tracking Reddit and YouTube influence: Both platforms heavily influence what AI models cite. Promptwatch tracks Reddit and YouTube mentions specifically because of this. BuzzSumo is another option for surfacing high-engagement discussions on a topic.
A practical workflow for 2026
Here's how to actually combine these tools into a research workflow that covers both Google and AI search:
Step 1: Use Semrush or Ahrefs for Google fundamentals. Understand what keywords your target audience searches on Google, what your competitors rank for, and where your backlink gaps are. This still matters -- Google traffic is still significant, and good content that ranks on Google often gets cited by AI models too.
Step 2: Use a GEO platform to find AI-specific prompt gaps. Promptwatch's Answer Gap Analysis (or a similar feature from another GEO tool) shows you which prompts your competitors appear in that you don't. These are your AI search "keywords."
Step 3: Create content that answers those prompts directly. This is where the traditional SEO workflow diverges from AI search. The content needs to directly and comprehensively answer the specific question, not just include the keyword phrase. Tools like Surfer SEO or Clearscope help with optimization; Promptwatch's AI writing agent generates the content directly from citation data.
Step 4: Check your technical AI accessibility. Use crawler logs (Promptwatch has these; most tools don't) to confirm that AI crawlers can actually access your content. A page that's invisible to AI crawlers won't get cited regardless of how good the content is.
Step 5: Track citation and connect it to traffic. Monitor which pages are getting cited by which AI models, and use traffic attribution to connect those citations to actual visits and conversions. This closes the loop and tells you which content investments are actually paying off.
Which tool should you actually use?
It depends on where you are and what you're trying to do.
If you're primarily focused on Google SEO and want to add some AI visibility monitoring without switching platforms, Semrush or Ahrefs with their limited AI features is a reasonable starting point. You won't get deep AI search data, but you'll keep your existing workflow intact.
If AI search visibility is a priority and you want to actually improve it (not just monitor it), Promptwatch is the most complete option. The combination of prompt gap analysis, content generation grounded in citation data, and crawler logs covers the full workflow in a way that no other single platform does right now.
If budget is the main constraint, SE Ranking gives you a reasonable mix of traditional SEO and basic AI monitoring at a lower price point, and Otterly.AI handles basic AI monitoring cheaply.
The one thing I'd push back on: treating AI search visibility as a "nice to have" to check on occasionally. ChatGPT, Perplexity, and Claude are where a growing share of purchase research happens now. The brands that figure out how to get cited consistently in those responses have a real advantage -- and the window to build that advantage before competitors do is narrowing.
Traditional keyword research tools are still useful. They're just not sufficient anymore.