AI Reputation & Search
People no longer merely search: they ask. And generative systems answer by describing your organisation too, in words nobody in the company wrote. Antropic analyses that representation and brings it back under governance.
The brand is narrated by systems nobody instructed.
When a client, a candidate or an analyst asks a generative system who you are, the answer is assembled from sources, weightings and syntheses outside your direct control.
That answer may be accurate, dated, incomplete or wrong. Either way it shapes decisions: on purchases, careers, investment, press coverage.
The methodological foundation of this module is LLMO, the method documented in the book "Fatti trovare da ChatGPT", the first Italian book dedicated to the subject.
Senior leadership
How generative answers represent the organisation is a matter of reputation, not of technique.
Communications and brand functions
Those who guard identity and messaging discover a new channel, where the brand is narrated by third-party systems.
Investor relations and public affairs
Analysts, journalists and stakeholders consult generative systems before they ever meet the company.
From the picture to the direction.
The analysis follows the institute's method: primary sources, verification, an executive read. Execution stays with the organisation, guided by clear lines.
The initial picture questions the main generative systems under repeatable protocols: the same questions, different contexts, documented answers. What is not repeatable does not enter the analysis.
The results reach senior leadership as an executive read: where the representation helps, where it exposes, what to address first.
01
A picture of the representation
How the main generative systems describe the organisation today: accuracy, completeness, tone, implicit sources.
02
Comparison with the positioning
The distance between what the systems narrate and what the organisation wants to communicate to clients, talent and the market.
03
Direction for the presence
Strategic lines on content, sources and oversight, grounded in the LLMO method documented in the institute's publications.
04
Monitoring over time
System answers change with the models and with the sources: the representation is observed, not photographed once.
Why does reputation in generative engines concern senior leadership?
Because a growing share of clients, candidates, analysts and journalists asks generative systems before forming a view. What those systems answer about the organisation is reputation in every sense, and reputation answers to the top.
How does this work differ from SEO?
SEO tends the position in lists of results. Here the matter is how language models describe the organisation inside an answer. The logic changes, the sources that count change, and so does the way of measuring. The reference method is LLMO, documented in the institute's book.
What is the methodological basis of the analysis?
The LLMO method described in "Fatti trovare da ChatGPT", the first Italian book dedicated to the subject, written by the institute's founder with AIPIA, the Italian association of AI professionals. The analysis applies that method to the organisation's specific case.
Does the institute also work on the content?
The institute sets the direction: what to say, where, with which sources and priorities. Execution stays with the organisation's internal teams or agencies, who receive clear, verifiable lines.
How often should the analysis be repeated?
Models and their sources change several times a year. A half-yearly check is a sound starting point; crises and extraordinary transactions call for dedicated observation.