Recognition Lab Library
Research for understanding a changing information landscape.
A curated collection for communications and brand leaders examining how AI affects reputation throughout discovery and consideration. It also shows how to interpret the evidence responsibly.
AI discovery and purchasing behavior
AI is entering consideration before the first click.
These resources examine how people use AI to find products, compare options and narrow their choices, even when a purchase is completed somewhere else.
The resources below are published by third parties and open in a new tab. Recognition Lab summaries are provided for orientation.
Retailers split on AI checkout options
AI is already helping consumers decide what to buy, even when they complete the purchase somewhere else.
Read third-party articleOpens in a new tabConsumers want AI shopping help, but not AI purchase decisions
Consumers are more comfortable using AI to narrow their choices than allowing it to make a purchase for them.
Read third-party studyIs retail ready for the AI shopping shift?
Shoppers are asking AI for product recommendations, and retailers are working to understand how their products appear in the answers.
Read third-party articleCan AI do your Christmas shopping?
A real-world test shows that AI recommendations can favor large retailers, miss relevant options and change when the question changes.
Read third-party articleWalmart brings purchasing into ChatGPT
Consumers can now move from product research to purchase without leaving the AI conversation.
Read third-party articleCommunications and AI representation
Public evidence shapes the picture AI assembles.
These resources consider how company information, earned media, reviews, research, interviews and public discussion contribute to AI-generated representations.
The resources below are published by third parties and open in a new tab. Recognition Lab summaries are provided for orientation.
Preparing your brand for agentic AI
Pernod Ricard reviewed how AI represented its brands and found information that was incomplete or wrong.
Read third-party articleWhy the old rules of Google Search are being rewritten by AI
Brands are moving from competing for a place in search results to competing for inclusion in an AI-generated answer.
Open third-party PDFAI optimization enters the PR workflow
Many communications teams believe AI visibility matters, but they have not decided who owns it or how to measure it.
Read third-party studyBrand mentions and visibility in Google AI Overviews
Brands mentioned more often across the web were also more visible in Google AI Overviews. The study shows a relationship, not proof of cause.
Read third-party studyHow brands can stay visible in AI-driven search
Edelman explains why AI visibility is becoming part of brand trust, reputation and communications strategy.
Read third-party viewpointA communicator’s guide to generative engines
This guide recommends clear, consistent public information and credible third-party coverage across AI platforms.
Read third-party guideWhy PR has a new role in AI search
This industry viewpoint argues that news coverage, expert commentary and executive visibility can contribute to AI answers.
Read third-party viewpointMonitoring AI visibility doesn’t tell teams what to do next
Most surveyed marketers have invested in AI-visibility monitoring, but many still struggle to connect visibility scores to business outcomes. The reporting illustrates why communications teams need interpretation, not another dashboard.
Read third-party articleWhy AI has made the corporate website more important
PMI’s communications team is strengthening the company’s website so AI systems can find credible facts and evidence about its transformation. The example shows how owned information can support the reputation an organization wants recognized.
Read third-party articleMost AI citations in a global brand study came from third-party sources
A large multilingual study found that AI citation patterns varied by market and that third-party sources appeared far more often than brand-owned sources. The findings show why the source environment matters alongside the answer itself.
Read third-party studyResearch cautions and interpretation principles
AI representation can be studied. It cannot be controlled.
The resources in this Library can inform questions and decisions. They do not prove that one communications tactic will cause an AI response to change.
Check more than one answer
Results can change by system, question and time. One response is not enough to establish a pattern.
Do not confuse correlation with causation
A relationship between two measures does not prove that one caused the other.
Show the supporting evidence
Important conclusions should make their sources, scope and limitations visible.
Responsible interpretation means looking for recurring patterns, examining the evidence behind them and keeping human judgment in the decision.
The research below is published by a third party and opens in a new tab. The Recognition Lab summary is provided for orientation.
The same AI question doesn’t always produce the same answer
Research found substantial variation when identical queries were repeated and when results were compared across Gemini and ChatGPT. Although the study focused on local search, it demonstrates why responsible research requires repeated observations and more than one AI system.
Read third-party article