Semrush AI Review: What You Get for $99 AI Visibility Toolkit

Semrush AI Visibility Toolkit combines AI search research, competitor analysis, brand perception, citation intelligence, and daily prompt tracking. We tested the platform across 15 websites to see which reports produce useful decisions and which still require manual filtering.

The dedicated AI Visibility Base plan starts at $99 per domain when billed annually. The $199 Starter plan combines the AI Visibility functionality with Semrush's broader SEO toolkit, while our hands-on testing used Pro+ at $299 per month.

Quick facts

How We Tested Semrush AI Visibility Toolkit

We tested Semrush AI Visibility across 15 websites, focusing on how quickly its research, brand analysis, citation data, and prompt monitoring turn into decisions. We reviewed the underlying AI answers as well as the dashboards, rather than treating headline scores as conclusions.

Our testing focused on the AI Visibility Toolkit, not the wider Semrush SEO suite.

We evaluated four main workflows:

• AI visibility research: Visibility scores, mentions, citations, cited pages, estimated audience, country distribution, and platform distribution.
• Competitive and prompt research: Missing topics, AI Volume, intent, source opportunities, individual prompts, and the AI answers behind them.
• Brand analysis: Share of Voice, sentiment, business drivers, feature-level perception, cited sources, and the questions shaping how brands are described.
• Prompt monitoring: Daily prompt results, positions, mentions, cited pages, and automatically discovered competitors.

Platform coverage changes by report.

That distinction matters because the reports do not use one universal dataset. AI Analysis is built for broad market discovery, Brand Performance provides a separate view of positioning and perception, and Prompt Tracking monitors a controlled set of prompts daily.

We also checked productivity. For every useful-looking opportunity, we followed the data back to the prompt, AI response, cited page, or competitive result. That exposed where Semrush saves research time and where its automated interpretation still needs verification.

For Prompt Tracking, we ran a five-prompt commercial query set through the complete monitoring workflow. We use those results to assess the product, not as evidence that Semrush improved visibility over time.

Visibility Overview: AI Visibility, Mentions, and Citations

Semrush Visibility Overview gives a fast benchmark of how often a brand appears in AI-generated answers, where those mentions come from, and which pages earn citations. We used it to separate broad visibility signals from the underlying platform, country, topic, and source data.

For one brand we tested, Semrush returned an AI Visibility Score of 14/100, with 144 mentions, 503 citations, and 475 cited pages.

The distinction between these metrics is useful. A mention measures brand presence. A citation measures source visibility. A website can influence an AI answer without the brand being recommended, so the two metrics should not be treated as interchangeable.

Monthly Audience needs even more caution. Semrush defines it as estimated query audience across topics where the brand appears. It is not traffic, impressions, or the number of people who actually saw the brand.

The Distribution by LLM view showed 64 mentions in Google AI Mode, 31 in ChatGPT, 29 in Google AI Overviews, and 20 in Gemini. The same report can also break results down geographically. In our test, the US generated 60 mentions, or 41.7% of the total.

This is where Visibility Overview becomes more useful than a single score. You can identify which AI platforms and markets already produce visibility, then drill into performing topics, individual prompts, cited sources, and cited pages.

The practical workflow is straightforward: protect pages already earning citations, identify valuable topics where visibility is weak, and avoid optimizing toward a global score without understanding what sits underneath it.

This is where Semrush becomes useful for GEO and AEO rather than just AI visibility reporting. For GEO, the data shows which topics, platforms, competitors, and third-party sources shape whether a brand appears in generated answers.

For AEO, the citation and cited-page reports reveal which owned pages are already being used as sources and where stronger answer-focused content could increase inclusion.

Competitor Research: Topic Gaps and Source Opportunities

Semrush Competitor Research compares a domain against up to four rivals and surfaces the topics, prompts, and sources where competitors appear more often. We used it to test whether those gaps translate into useful content and outreach priorities, or simply generate more data to filter.

One comparison returned 2,774 competitive topics. The brand we tested was missing from 2,735, while 15 were shared, two were classified as strong, and 22 were unique.

That makes competitive gap discovery extremely fast. Semrush defines missing opportunities as prompts or topics where selected competitors appear and the analyzed brand does not.

The problem is relevance.

Some of the highest-volume gaps in our test belonged to topics well outside the brand's commercial focus. One unrelated cluster carried an estimated 19.3M AI Volume, and an automated insight suggested targeting it because of its modeled audience opportunity.

Technically, the gap existed. Strategically, it was useless.

This happens because competitor selection determines the universe Semrush explores. If a selected competitor operates across adjacent categories, those unrelated areas can flood the missing-topic report.

The Sources view applies similar competitive logic to citations. Our comparison produced:

This data is more actionable when used selectively. You can open a cited source, inspect the prompts and AI responses associated with it, and decide whether it belongs in digital PR, partnerships, content distribution, or nowhere in the plan.

Semrush removes most of the mechanical work of finding competitor topic and citation gaps. The bottleneck moves from discovery to prioritization. That is a productivity gain, but only if the competitive set is carefully chosen and irrelevant results are filtered aggressively.

Prompt Research: AI Volume, Intent, and Source Discovery

Semrush Prompt Research turns a broad topic into related AI topics, individual prompts, intent patterns, mentioned brands, and cited sources. We used it to test whether AI demand estimates and answer-level evidence can shorten research time and help prioritize content, monitoring, and outreach.

For one commercial topic, Semrush returned:

The intent analysis classified 57% of the prompt set as informational, 17% commercial, 14% navigational, 8% transactional, and 4% task-based.

This immediately makes a 31,000-prompt dataset more manageable. Instead of treating every discovered prompt equally, you can isolate comparison, purchase, educational, or task-driven demand and build different workflows around each.

AI Volume should not be read like traditional exact-match keyword volume. Semrush describes it as estimated AI search activity at the topic level. Prompt Research groups related questions into topics and uses its AI dataset to estimate demand.

The best part of Prompt Research is the drill-down. Each topic can be expanded into individual prompts, full AI responses, mentioned entities, and cited sources. Relevant prompts can then move directly into Prompt Tracking.

We also found classification noise. Broad or ambiguous queries can receive strong relevance labels, while the Brands view can mix direct competitors with other entities associated with the topic.

That means the discovery layer should produce a research shortlist, not an automatic content calendar.

The productivity benefit is significant. One query can replace much of the manual process of brainstorming prompts, checking intent, running AI searches, recording mentioned entities, collecting citations, and deciding what deserves ongoing measurement.

Brand Performance: Share of Voice and Business Drivers

Semrush Brand Performance brings Share of Voice, sentiment, and business-driver frequency into one competitive view. We used it to see whether the platform can move beyond simple visibility tracking and show why a brand is winning or losing attention inside AI-generated answers.

For the brand we tested, Semrush reported 1% Share of Voice and 75% favorable sentiment. The strongest competitor in the selected comparison reached 10% Share of Voice, while the highest favorable sentiment score was 81%.

That contrast is useful. A brand can be described positively when it appears but still be largely absent from the answers that influence discovery.

Semrush's Brand Performance reports support up to nine selected competitors and analyze ChatGPT, Google AI Mode, Perplexity, and Gemini, individually or as an aggregated view.

The Key Business Drivers by Frequency widget gives the headline metrics more context.

These counts do not prove that one product is objectively better. They show how frequently AI associates each brand with particular attributes.

That makes them useful for positioning work. If competitors repeatedly own an attribute in AI answers, you can inspect why, review the underlying responses and sources, then decide whether the gap requires stronger product evidence, comparison pages, clearer messaging, or third-party coverage.

Semrush also generates AI Strategic Opportunities from the report. We found these useful as prompts for investigation, but less reliable than the underlying data. Recommendations still need to be checked against the source metrics and actual AI responses before resources are committed.

Perception: Brand Sentiment and Feature Analysis

Semrush Perception breaks AI sentiment into competitive scores, feature categories, strengths, weaknesses, and the descriptions behind them. We used it to see whether a favorable headline score actually explains brand positioning, and whether the underlying mentions are substantial enough to guide content and messaging decisions.

The brand we tested received 75% favorable sentiment and 25% general sentiment. Competitors in the selected comparison ranged from 56% to 81% favorable sentiment.

Semrush bases the Perception report's sentiment analysis on non-branded queries, which makes it more relevant to broader discovery than simply measuring answers where users explicitly ask for the brand.

The useful information sits beneath the percentage.

Key Sentiment Drivers grouped recurring strengths and areas for improvement. We could see which themes AI associated positively with the brand and which topics repeatedly created weaker descriptions.

The Sentiment by Feature Category view goes further by splitting perception across areas such as pricing, usability, privacy, support, or product capabilities.

This also exposed one of the report's biggest limitations: sample size.

One feature category in our test displayed 100% favorable sentiment from only two mentions. Another showed 0% favorable sentiment from a single mention.

Those percentages are mathematically correct inside the sample, but they are not strong evidence of broad market perception.

Semrush helps by showing Mentions by Feature Category alongside sentiment and by allowing users to inspect the answers behind individual descriptions. That context should be part of the workflow.

Perception is therefore more valuable as a diagnostic tool than as a scorecard. It compresses large numbers of AI descriptions into themes quickly, but decisions should be based on the combination of sentiment, mention volume, and the actual answers producing the classification.

Narrative Drivers & Questions: AI Rankings, Citations, and Search Intent

Semrush Narrative Drivers and Questions connect competitive visibility with the prompts and sources shaping AI answers. We used them to see where the tested brand appears, how prominently it is positioned, which publishers influence responses, and what question types deserve content attention.

Narrative Drivers combines Share of Voice, mentions, average position, citations, and question-level results.

For the brand we tested:

A 1% Share of Voice alone tells you very little about what to fix. Breakdown by Question makes the metric actionable.

In our test, the brand ranked first for some commercially relevant comparison questions while appearing much lower, or not at all, for others. That lets you work at query-cluster level instead of treating AI visibility as a site-wide problem.

The citation data adds an off-site dimension. Semrush's Top Cited Domains identifies the publishers and domains AI relies on for non-branded questions, while the question breakdown shows where those sources influence answers.

The Questions report organizes the same market around user intent.

Our test returned 70% comparison intent, 23% research, 7% education, 1% improvement, and 1% purchase. The displayed figures total slightly above 100% because the interface rounds percentages.

Semrush then groups questions into themes such as competitive positioning, pricing, security, product capabilities, reputation, and specific workflows.

Together, these two reports create a useful sequence: Narrative Drivers shows where the brand wins or loses, while Questions shows which themes deserve content, messaging, or authority work next.

Prompt Tracking: Daily Rankings, Sources, and Competitor Discovery

Semrush Prompt Tracking monitors a fixed set of AI queries every day and connects each result to rankings, citations, source pages, and competing domains. We used it to see whether selected prompts can become a practical measurement loop for content, outreach, and visibility improvements.

In one campaign, we monitored five commercially relevant prompts in ChatGPT.

The first collection produced:

• 1 of 5 prompts with a brand mention
• 47 cited source pages
• 19.68% AI Visibility
• 27 automatically discovered competing domains

The Rankings Overview made the visibility gap easy to understand. One prompt returned the brand at position 5, while the remaining four were marked Missed.

That is more useful operationally than a broad market score because the monitored prompt set is controlled. You decide which commercial questions matter and can keep measuring the same set after changing content, messaging, or off-site coverage.

The Sources report classified the 47 cited pages as:

This connects monitoring directly to action. A repeatedly cited owned page may deserve further investment. A relevant external page can become a PR or partnership target. An irrelevant citation can simply be ignored.

Competitors Discovery found 27 domains appearing in the same five prompts. This is useful because the competitor set comes from the answers being monitored rather than a generic market category.

Prompt Tracking currently supports ChatGPT Search, Google AI Mode, and Gemini, with daily updates for selected prompts.

The limitation in our test is time. One collection establishes a baseline, not a trend. Prompt Tracking becomes more valuable after optimization work, when the same queries can show whether mentions, positions, and source patterns actually changed.

A practical GEO and AEO strategy can therefore use Semrush as one connected workflow: Prompt Research identifies commercially relevant demand, Competitor Research exposes topic and citation gaps, Brand Performance shows how AI systems position the brand, and Prompt Tracking measures whether changes to content, messaging, and external authority improve visibility over time.

The value comes from moving from discovery to prioritization to measurement without rebuilding the dataset in separate tools.

Semrush AI Pricing: What You Get With Each Plan

Semrush sells the AI Visibility Toolkit on its own and also bundles it with the wider SEO platform. We compared the three plans most relevant to this review to see how much extra capacity, SEO data, and monitoring depth you actually gain as pricing increases.

The most important distinction is between AI Visibility Base and the SEO + AI Search plans.

Base is the dedicated AI product. Starter and Pro+ add the wider Semrush SEO workflow.

Semrush currently lists Base at $99 per month per domain when billed annually, with 25 daily tracked prompts, one Brand Performance domain, AI competitor analysis, Prompt Research, and AI-readiness auditing.

Starter at $199/month is the more relevant entry point if AI visibility sits inside an SEO workflow. It raises daily prompt tracking to 50 and adds five monitored websites, 500 daily tracked SEO keywords, keyword research, competitor tools, and the broader Semrush site and position tracking stack.

Pro+ at $299/month doubles the AI prompt allowance to 100 and increases capacity to 15 websites and 1,500 daily tracked SEO keywords. It also adds historical SEO data, content optimization, keyword cannibalization analysis, and multi-location/device tracking.

If AI visibility is the only requirement, Base covers the core toolkit for less. If AI search and traditional SEO are managed together, Starter is the more complete starting point. Pro+ is mainly justified by higher monitoring capacity and deeper SEO workflows.

Final Verdict

Semrush AI Visibility Toolkit is strongest at research and prioritization. Visibility Overview establishes where a brand appears, Competitor Research exposes gaps, Prompt Research expands those gaps into demand and intent, and Brand Performance explains how AI systems position the brand against competitors.

The depth is valuable because the platform lets you move from a headline score into the actual prompt, response, source, or business driver behind it. That cuts significant manual research from AI visibility work.

The weakness is the same breadth. Thousands of discovered topics and sources can create false priorities, sentiment percentages can rest on tiny samples, and automated strategic recommendations can be less reliable than the underlying tables. Semrush works best when its data accelerates judgment rather than replaces it.

At $199/month, Starter is the strongest fit if you want AI visibility integrated with SEO research, site auditing, keyword tracking, and competitor analysis. The $99 Base plan makes more sense when AI visibility is the only requirement. Pro+ becomes worthwhile when the additional prompt, website, and SEO tracking capacity is actually needed.