Know where AI is shaping demand. Build the strategy to win it.
Strengthening Upwork's position in AI-powered hiring discovery
Published LLM Listed case study
Turning AI discovery into a new opportunity for legal inquiries
Published LLM Listed case study
Making Valimail a leading AI recommendation for email security
Published LLM Listed case study
AI Discovery & Strategy
Before a buyer fills in a form, they may ask an AI assistant to define the problem, compare approaches, name credible providers and challenge the shortlist they already have. AI Discovery & Strategy shows where your brand appears in that journey, what the major answer engines say about you and which actions are most likely to improve the answer.
Our approach
Before a buyer fills in a form, they may ask an AI assistant to define the problem, compare approaches, name credible providers and challenge the shortlist they already have. AI Discovery & Strategy shows where your brand appears in that journey, what the major answer engines say about you and which actions are most likely to improve the answer.
This is not a one-model screenshot or a generic SEO audit with “AI” added to the title. LLM Listed maps the questions buyers ask, tests them across ChatGPT, Claude, Gemini and Perplexity, examines the sources behind the answers, and turns the evidence into a commercial roadmap. You leave with a defensible baseline, a clear view of competitors and a prioritized plan your content, PR, product, analytics and leadership teams can act on.
Discovery map
AI discovery has become part of the buyer journey
Search did not disappear when conversational AI arrived. The journey became more fragmented.
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Search did not disappear when conversational AI arrived. The journey became more fragmented. A buyer can begin with a broad question in Google’s AI features, continue the research in ChatGPT, ask Perplexity for sources and use Claude or Gemini to compare a proposal. Each system may retrieve different evidence, interpret the brand differently and produce a different shortlist.
The scale is no longer theoretical. Google reported in June 2026 that AI Overviews had more than 2.5 billion monthly users and AI Mode had surpassed one billion monthly users. Those figures describe usage of Google’s own AI search experiences, not the whole AI discovery market, but they show why visibility inside generated answers deserves its own measurement and strategy. (Google, June 2026)
Traditional analytics usually begins after a click. AI discovery often happens before one. A buyer may learn your strengths, weaknesses, pricing assumptions and alternatives without visiting the site. That makes the answer itself a commercial surface. The practical question is not “Are we doing AI?” It is: for the prompts that influence revenue, are we understood accurately, cited credibly and recommended appropriately?
What AI Discovery & Strategy answers
What we examine
Prompt demand and buyer language. Interviews, search and sales evidence are used to define the questions buyers ask at discovery, comparison and decision stages.
Explore the scope
Prompt demand and buyer language. Interviews, search and sales evidence are used to define the questions buyers ask at discovery, comparison and decision stages. A typical program can begin with a focused set and expand as the category map becomes clearer.
Multi-platform answer behavior. Prompts are tested across ChatGPT, Claude, Gemini and Perplexity using a documented setup. Results are timestamped because answers can change by model, mode, location, personalization and retrieval state.
Brand mention and recommendation share. We record whether the brand appears, its relative position, the language used and whether it is cited, recommended, compared or merely named.
Answer accuracy and sentiment. We check commercially important facts and describe the practical severity of any error. A wrong office location and an invented safety claim are not treated as equivalent.
Citation and source patterns. We identify the domains and page types surfaced in answers, then compare the evidence footprint with competitors. A source appearing beside an answer is not automatically proof that it caused the answer, so the report distinguishes observation from inference.
Entity and technical foundations. We review whether the site and external profiles consistently explain who the organization is, what it offers, who it serves and how its products, people and locations relate. This includes indexability, structured data, canonicalisation, internal linking and clear factual pages.
Competitive visibility. Competitors are assessed by prompt cluster rather than a single league table. One brand may dominate category discovery while another owns comparison or implementation questions.
Measurement readiness. We assess whether analytics, CRM fields and sales discovery can capture AI-influenced demand. The aim is not perfect attribution; it is a useful evidence chain from answer visibility to commercial outcomes.
The engagement: from uncertainty to a prioritized roadmap
What you receive
A commercial AI discovery workshop and agreed measurement scope. A structured prompt map covering discovery, comparison, validation and decision questions.
Explore the scope
A commercial AI discovery workshop and agreed measurement scope.
A structured prompt map covering discovery, comparison, validation and decision questions.
A timestamped baseline across the agreed AI platforms.
Competitor mention, position and citation analysis by prompt cluster.
Accuracy and brand-risk findings with severity and evidence.
A source and entity-gap review spanning owned and third-party surfaces.
A prioritized 90-day plan across content, technical, digital PR, product data and measurement.
An executive readout explaining what is known, what is inferred and what should happen next.
A repeatable measurement framework for future tracking.
The output is a strategy, not a score
A single visibility score can be useful for reporting, but it cannot decide what the business should do. A brand can improve its score by appearing more often in low-value answers while remaining absent from the questions that create revenue.
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A single visibility score can be useful for reporting, but it cannot decide what the business should do. A brand can improve its score by appearing more often in low-value answers while remaining absent from the questions that create revenue. It can also be visible for the wrong audience or for claims that need correcting.
LLM Listed treats measurement as a decision system. The work connects a prompt cluster to an answer pattern, an evidence gap, an action and a business signal. That is how an audit becomes a strategy rather than a PDF that is reviewed once and forgotten.
Upwork: mapping discovery at marketplace scale
In LLM Listed’s published Upwork case study, the program mapped more than 180,000 buyer prompts spanning hiring use cases, roles, skills, regions and competitor comparisons. The case study reports a 318% increase in AI recommendation share and a top position for “hire a freelancer” style prompts across the tracked set. Those are client-specific results, not a forecast for every engagement; the relevant lesson is the operating model: define the demand surface, build content and authority around it, then track the same prompt set over time. Read the Upwork case study.
Who this service is for
AI Discovery & Strategy is designed for organizations that need an evidence-based starting point or a reset. It is particularly useful before a website migration, brand or product launch, category repositioning, major content program, digital PR investment or board decision about AI search.
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AI Discovery & Strategy is designed for organizations that need an evidence-based starting point or a reset. It is particularly useful before a website migration, brand or product launch, category repositioning, major content program, digital PR investment or board decision about AI search. It also works for teams already producing content but unable to explain why visibility is changing.
It is not a promise to reverse-engineer a proprietary model. No responsible agency can guarantee a particular answer. It is a rigorous way to observe the market, improve the evidence available to answer engines and make better investment decisions.
The practical details
Frequently asked questions
See what buyers are being told before you decide what to build.
Start with a free visibility scan. If there is a meaningful gap, a senior strategist will explain where a deeper discovery program can create commercial value. If there is not, we will say so.