A new generation of software tools is being developed to help marketers track how their brands appear inside AI-generated search answers, as attention shifts from traditional search engine rankings towards citations within tools such as ChatGPT, Gemini, Perplexity and Google AI Overviews.
Semrush, long regarded as a leading platform for tracking positions in conventional search results, has recently added AI visibility features to its existing suite, including AI Overview monitoring and keyword data for AI-influenced queries. However, according to a guide reviewing the market, its coverage focuses heavily on Google AI Overviews, Gemini, ChatGPT and Perplexity, leaving gaps around emerging assistants such as Meta AI, Copilot and Yahoo Scout.
The guide describes AI search visibility as distinct from traditional rank tracking. Where conventional search ranking depends on factors such as backlinks and keyword alignment, visibility inside AI-generated answers depends on whether a system can confidently interpret, extract and attribute a brand's content when compiling a response. Three measures are commonly used to assess this: citation frequency, share of voice relative to competitors, and the sentiment with which a brand is described.
Five alternative tools were highlighted as options for marketers, SEO specialists and demand generation teams evaluating their approach.
HubSpot AEO (Answer Engine Optimisation) was described as built specifically around tracking AI visibility rather than treating it as an add-on to existing SEO tools. It links citation data and share-of-voice figures to HubSpot's Marketing Hub and Smart CRM products, allowing marketing teams to connect visibility inside AI answers with pipeline and revenue data. A free companion tool, the AEO Grader, scores visibility across major AI engines. Peter Baraník, founder of ColorWee, said the tool provided "a visibility score, prompt tracking, citation analysis, and prioritised recommendations" across ChatGPT, Gemini and Perplexity, at a cost of around $50 a month, though he noted it does not currently cover platforms such as Claude, Grok or Google AI Mode.
LLM Pulse was identified as a dedicated AI visibility platform focused on citation analysis, sentiment tracking and what is termed "query fan-out" research, showing the range of prompts an AI engine might use to retrieve content on a given topic. Doug Darroch, managing director at Renaissance Digital Marketing, said the tool's strength lay in white-label reporting and its ability to show actual AI-generated responses, rather than aggregated scores alone, though he noted optimisation recommendations still rely on the user to carry out strategic work.
BrightEdge, an established enterprise SEO platform, has expanded into AI search tracking with features including AI Overview monitoring and large-scale keyword analysis. Baraník said the platform could be useful for organisations with existing enterprise SEO workflows but cautioned that "it's not enough if your problem is specifically AI search visibility", adding that its pricing and complexity make it more suited to larger teams with dedicated resources.
Authoritas measures how brands, products and competitors appear across AI search experiences, with a particular focus on Google. Raúl Menoyo, founder of Citora, said the platform's URL-level tracking of AI Overview citations was useful for identifying exactly which pages are being cited, but noted it was "thin on ChatGPT, Claude, and Perplexity", meaning it may need to be paired with another tool for broader assistant coverage.
Advanced Web Ranking tracks brand appearance across AI search results alongside competitor visibility over time. Manpreet Kaur, an SEO specialist, said the tool allowed tracking of ranking positions across locations, devices and search engines with historical trend data, describing it as useful for teams that need reliable reporting on visibility over time.
The guide suggests that the choice of tool should depend on where a brand's target buyers are searching and how a team needs to report data internally. It notes that some organisations are running AI visibility tracking alongside Semrush rather than replacing it, using Semrush for technical SEO tasks such as backlink analysis while adding a separate tool for citation monitoring inside AI-generated answers.
Recommended steps for teams starting an AI visibility strategy include testing a small set of realistic buyer queries manually across AI engines to establish a baseline before adopting any tracking software, and reviewing whether pages that perform well in traditional search results are nonetheless being overlooked by AI systems, which may indicate that content needs to be restructured for clarity and authority rather than purely for keyword targeting.
The guide notes that connecting citation data to actual business outcomes, such as leads or sales, remains one of the more difficult steps for marketing teams, often requiring contacts to be manually tagged by their AI-influenced discovery source unless a platform offers direct integration with a customer relationship management system.
