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# How AI is shaping your online reputation and credibility
- URL: https://capitolcommunicator.com/how-ai-is-shaping-your-online-reputation-and-credibility/
- Published: 2026-09-17T18:33:35.000Z
- Updated: 2026-09-17T18:33:35.000Z
- Author: Guest Columnist
- Tags: Insights, Technology, #wp-top-right-sponsored, #Import 2026-10-08 18:56

By [Issac Morgan](https://substack.com/@issac123?ref=capitolcommunicator.com)

**There’s a new sheriff in town when it comes to online reputation management** for professionals, and it’s probably not hard to guess.

Artificial intelligence.

AI has increasingly become a gatekeeper to professional reputation, meaning people’s expertise and credibility can be evaluated by machines based on information gathered from multiple sources, said **Erin Lanuti**, co-founder and CEO of [Lilypath](https://lilypath.com/?ref=capitolcommunicator.com).

Amid the AI era, people aren’t just deciding the credibility about professionals based on Google search results, according to the Lilypath team.

They are asking AI systems questions such as who the leading experts are in a field, whether an executive is credible or which business they should consider hiring for different services.

“That means someone’s reputation may be interpreted before the researcher ever visits a company website, reads an executive biography, or opens a LinkedIn profile,” Lanuti said in an interview with [EIN Presswire](https://www.einpresswire.com/?ref=capitolcommunicator.com).

Lanuti and her team at Lilypath, a company that helps professionals understand and improve how AI systems interpret their expertise, have underscored this shift in how people research companies and executives.

“Compare this to the past, where research looked like typing a few keywords into Google, scanning a page of links, and forming your own opinion. Now AI has pushed people to ask complete questions: Who are the strongest experts in this field? Is this executive credible? Who is the best orthopedic surgeon near me?” Lanuti said.

For communications teams, that means paying attention not only to what appears in the news or Google search results, but also to how AI systems interpret and describe their clients in AI-generated responses, Lilypath suggests.

“Search was primarily about being found. AI-mediated research is about what the system concludes once it finds you,” Lanuti told EIN Presswire.

In response to the growing role of AI in professional research, Lilypath has developed a suite of products designed to show people how AI systems currently interpret their professional authority.

It’s called Authority Intelligence, which also tracks how those assessments change over time. Lilypath works “with people of all professions and career stages,” and offers a product aimed at college students, Lanuti said.

The technology analyzes information about professionals, including their LinkedIn profiles, and gives users a detailed report on how AI systems interpret their expertise.

A March 2026 [report](https://www.tryprofound.com/blog/linkedin-is-the-most-cited-domain-for-professional-queries-in-ai-search?ref=capitolcommunicator.com) from AI search company Profound found that LinkedIn was the most-cited domain for professional search queries on major AI search platforms, showing how LinkedIn content can factor into how AI understands professionals.

Lanuti, who previously served in a leadership role at Omnicom Public Relations Group, [launched](https://www.prweek.com/article/1949179/omnicom-alum-erin-lanuti-launches-authority-intelligence-platform-lilypath?ref=capitolcommunicator.com) Lilypath alongside co-founders Dan Nestle and Todd Grossman in early 2026.

The launch comes as concerns over how accurately AI represents professionals become more relevant, as people turn to AI to research candidates, assess credibility and consider their options in the hiring process.

In the interview, Lanuti goes into depth about how Lilypath’s products work and which platforms are influencing the way AI interprets your credibility and expertise.

She also talks about what communicators should be doing to ensure AI systems accurately represent their clients, starting with LinkedIn profiles.

*Editor’s note: This interview has been slightly edited for length, clarity and brevity.*

**Q: How has reputation management changed over the years? And on that note, what exactly are “AI gatekeepers?”**

A: Reputation management has evolved in layers. It began with influencing journalists, editors, and other human gatekeepers. Search then added the need to manage rankings, reviews, and the first page of results. And social media then made reputation continuous and participatory.

AI adds another layer to reputation management in synthesis of information.

“AI gatekeepers” is shorthand for the systems that retrieve information, select which sources appear relevant, and turn those sources into an answer, comparison, or recommendation. They are not human decision-makers, and they do not all behave alike. But they can influence which people and companies enter someone’s consideration set.

The new risk is not limited to negative coverage. It can be silent omission, mistaken identity, outdated information, or an accomplished person being described so generically that their real expertise disappears.

It can also drift. An answer that is accurate today may change as models, sources, and retrieval systems change. That’s why Authority 360 monitors answers weekly and Authority Graph measures them repeatedly over time. Reputation can no longer be treated as a one-time repair.

**Q: Can you explain in layman’s terms how Lilypath’s technology, Authority Intelligence, actually works for professionals? And do you work with people in various professions?**

A: Authority Intelligence is a way to measure and improve how AI describes a person and their expertise.

Imagine AI is writing a school report about you using clues it finds online—your LinkedIn page, website, articles, interviews, and other sources. Sometimes it gets the story right. Sometimes it misses important facts, mixes you up with someone else, or doesn’t mention you at all.

Lilypath checks that “report,” compares it with the truth, and shows you:

- What AI thinks you know
- What it got wrong or left out
- Where it found its information
- What you can change to make the story more accurate
- Whether the answers improve or change over time

In simple terms: Authority Intelligence helps make sure AI gives people the right story about who you are and what you’re good at.

Our suite of solutions work with people of all professions and career stages, and Blueprints work with college students through C-Suite executives.

- **Authority 360** is designed for individual professionals, founders, and executives. It combines two LinkedIn Blueprint rebuilds each year with Progress Checks and a weekly AI Pulse across ChatGPT, Gemini, and Claude.
- **Authority Graph** is our enterprise and agency platform. It analyzes ChatGPT, Claude, Gemini, and Perplexity against a controlled Source of Truth, tracks changes over time, reveals the sources influencing the answers, and benchmarks people against relevant peers.
- **Authority Snapshot** is a free way to review a baseline score of your AI visibility on how AI engines currently describe and interpret your professional authority.

**Q: What specific platforms are having a major influence on the way AI systems interpret your credibility or expertise?**

A: There are two layers to consider: the AI platforms producing the answers and the public sources supplying the evidence.

On the answer side, ChatGPT, Gemini, Claude, Perplexity, and Google’s AI search experiences are increasingly important. Because each system retrieves and interprets information differently, Authority Graph and AI Pulse examine multiple leading platforms rather than treating “AI” as one monolithic audience.

On the evidence side, across 30 professionals and about 30,000 citations we have consistently seen LinkedIn as the number one source, with YouTube as a close second. The analysis consists of a variety of professionals including titans of finance, politicians, physical therapy practitioners, consultants, etc.

Beyond the top two sources, we see company websites, credible media coverage, personal websites, bylined articles, professional associations, conference biographies, podcasts and transcripts, and reputable directories can all help corroborate the story.

The important thing to distinguish here is that there is no universal source hierarchy. It changes by model, question, freshness, and context. And the strongest position is a clear professional record supported consistently across several credible sources.

**Q: What does this shift in reputation management mean for communications professionals?**

A: Communications professionals are moving from managing messages to managing the evidence that machines use to interpret those messages.

Media coverage, executive profiles, bylined content, speaking appearances, and corporate websites still matter. In many ways, they matter more because they can become inputs into an AI-generated answer. But communications teams now need to determine whether those inputs form a clear, consistent, verifiable record.

That expands the mandate. Teams must monitor not only coverage, sentiment, and search position, but also whether a client appears in relevant AI answers, how their authority is framed, whether they are recommended, which sources receive credit, and where factual drift is emerging.

Authority Graph makes that work measurable across multiple executives and AI platforms. It gives agencies and enterprise teams a shared view of reputation risk, competitive position, citation ownership, and the specific corrections that deserve priority.

The next generation of reputation management protects two things at once: what people think about you and what machines can substantiate about you.

**Q: What should communications teams do right now to better understand how large language models represent their clients?**

A: Start with a controlled audit. Create 8-10 realistic questions that a journalist, prospective client, investor, recruiter, or partner might ask. Run the same questions across ChatGPT, Gemini, Claude, and Perplexity, with web search enabled where available. Because answers can vary, test more than once and record the date, prompt, response, and cited sources.

Then look for five things: Does the client appear? Is the description accurate? Does the answer recognize their real expertise? Are they recommended or merely mentioned? Which competitors and sources appear instead?

Compare the findings with a verified Source of Truth. Correct the highest-value gaps first, beginning with foundational assets such as LinkedIn, the official biography, company leadership pages, and credible third-party coverage.

For one person, Authority 360 can automate much of that ongoing monitoring through its weekly AI Pulse. For agencies and organizations managing multiple leaders, Authority Graph creates a multi-engine system of record, benchmarks each person across five dimensions, and shows where intervention will have the greatest value.

Do not optimize around one strange answer. One response is an anecdote. Consistent patterns are intelligence.

**Q: Some have said there is a push to make sure AI tools are actually reading your content. How is doing that different from just managing your online reputation?**

A: I would challenge the premise slightly: no one can guarantee that an AI system will retrieve, use, or cite a particular piece of content.

Traditional online reputation management usually asks: What appears when someone searches my name, and is the overall impression positive or negative?

Authority Intelligence asks a different set of questions. Can the system identify you correctly? Does it understand your actual expertise? Can it verify your claims? Does it recommend you for the opportunities that fit your record? Which sources does it use to reach those conclusions?

That last question matters. Authority Graph includes deep citation intelligence that breaks citations down by five dimensions – Search Presence, Authority Framing, Drift, and Hallucination and then classifies each citation by its role e.g. Is it a Role Carrier, Displacer, etc.

Publishing more is not necessarily the solution. The information must be accessible, specific, consistent, and supported elsewhere. The goal is to make an accurate interpretation easier to retrieve and substantiate, not just produce a positive impression.

a new sheriff in town when it comes to online reputation management for professionals, and it’s probably not hard to guess.

Artificial intelligence.

AI has increasingly become a gatekeeper to professional reputation, meaning people’s expertise and credibility can be evaluated by machines based on information gathered from multiple sources, said Erin Lanuti, co-founder and CEO of [Lilypath](https://lilypath.com/?ref=capitolcommunicator.com).

Amid the AI era, people aren’t just deciding the credibility about professionals based on Google search results, according to the Lilypath team.

They are asking AI systems questions such as who the leading experts are in a field, whether an executive is credible or which business they should consider hiring for different services.

“That means someone’s reputation may be interpreted before the researcher ever visits a company website, reads an executive biography, or opens a LinkedIn profile,” Lanuti said in an interview with [EIN Presswire](https://www.einpresswire.com/?ref=capitolcommunicator.com).

Lanuti and her team at Lilypath, a company that helps professionals understand and improve how AI systems interpret their expertise, have underscored this shift in how people research companies and executives.

“Compare this to the past, where research looked like typing a few keywords into Google, scanning a page of links, and forming your own opinion. Now AI has pushed people to ask complete questions: Who are the strongest experts in this field? Is this executive credible? Who is the best orthopedic surgeon near me?” Lanuti said.

For communications teams, that means paying attention not only to what appears in the news or Google search results, but also to how AI systems interpret and describe their clients in AI-generated responses, Lilypath suggests.

“Search was primarily about being found. AI-mediated research is about what the system concludes once it finds you,” Lanuti told EIN Presswire.

In response to the growing role of AI in professional research, Lilypath has developed a suite of products designed to show people how AI systems currently interpret their professional authority.

It’s called Authority Intelligence, which also tracks how those assessments change over time. Lilypath works “with people of all professions and career stages,” and offers a product aimed at college students, Lanuti said.

The technology analyzes information about professionals, including their LinkedIn profiles, and gives users a detailed report on how AI systems interpret their expertise.

A March 2026 [report](https://www.tryprofound.com/blog/linkedin-is-the-most-cited-domain-for-professional-queries-in-ai-search?ref=capitolcommunicator.com) from AI search company Profound found that LinkedIn was the most-cited domain for professional search queries on major AI search platforms, showing how LinkedIn content can factor into how AI understands professionals.

Lanuti, who previously served in a leadership role at Omnicom Public Relations Group, [launched](https://www.prweek.com/article/1949179/omnicom-alum-erin-lanuti-launches-authority-intelligence-platform-lilypath?ref=capitolcommunicator.com) Lilypath alongside co-founders Dan Nestle and Todd Grossman in early 2026.

The launch comes as concerns over how accurately AI represents professionals become more relevant, as people turn to AI to research candidates, assess credibility and consider their options in the hiring process.

In the interview, Lanuti goes into depth about how Lilypath’s products work and which platforms are influencing the way AI interprets your credibility and expertise.

She also talks about what communicators should be doing to ensure AI systems accurately represent their clients, starting with LinkedIn profiles.

*Editor’s note: This interview has been slightly edited for length, clarity and brevity.*

**Q: How has reputation management changed over the years? And on that note, what exactly are “AI gatekeepers?”**

A: Reputation management has evolved in layers. It began with influencing journalists, editors, and other human gatekeepers. Search then added the need to manage rankings, reviews, and the first page of results. And social media then made reputation continuous and participatory.

AI adds another layer to reputation management in synthesis of information.

“AI gatekeepers” is shorthand for the systems that retrieve information, select which sources appear relevant, and turn those sources into an answer, comparison, or recommendation. They are not human decision-makers, and they do not all behave alike. But they can influence which people and companies enter someone’s consideration set.

The new risk is not limited to negative coverage. It can be silent omission, mistaken identity, outdated information, or an accomplished person being described so generically that their real expertise disappears.

It can also drift. An answer that is accurate today may change as models, sources, and retrieval systems change. That’s why Authority 360 monitors answers weekly and Authority Graph measures them repeatedly over time. Reputation can no longer be treated as a one-time repair.

**Q: Can you explain in layman’s terms how Lilypath’s technology, Authority Intelligence, actually works for professionals? And do you work with people in various professions?**

A: Authority Intelligence is a way to measure and improve how AI describes a person and their expertise.

Imagine AI is writing a school report about you using clues it finds online—your LinkedIn page, website, articles, interviews, and other sources. Sometimes it gets the story right. Sometimes it misses important facts, mixes you up with someone else, or doesn’t mention you at all.

Lilypath checks that “report,” compares it with the truth, and shows you:

- What AI thinks you know
- What it got wrong or left out
- Where it found its information
- What you can change to make the story more accurate
- Whether the answers improve or change over time

In simple terms: Authority Intelligence helps make sure AI gives people the right story about who you are and what you’re good at.

Our suite of solutions work with people of all professions and career stages, and Blueprints work with college students through C-Suite executives.

- **Authority 360** is designed for individual professionals, founders, and executives. It combines two LinkedIn Blueprint rebuilds each year with Progress Checks and a weekly AI Pulse across ChatGPT, Gemini, and Claude.
- **Authority Graph** is our enterprise and agency platform. It analyzes ChatGPT, Claude, Gemini, and Perplexity against a controlled Source of Truth, tracks changes over time, reveals the sources influencing the answers, and benchmarks people against relevant peers.
- **Authority Snapshot** is a free way to review a baseline score of your AI visibility on how AI engines currently describe and interpret your professional authority.

**Q: What specific platforms are having a major influence on the way AI systems interpret your credibility or expertise?**

A: There are two layers to consider: the AI platforms producing the answers and the public sources supplying the evidence.

On the answer side, ChatGPT, Gemini, Claude, Perplexity, and Google’s AI search experiences are increasingly important. Because each system retrieves and interprets information differently, Authority Graph and AI Pulse examine multiple leading platforms rather than treating “AI” as one monolithic audience.

On the evidence side, across 30 professionals and about 30,000 citations we have consistently seen LinkedIn as the number one source, with YouTube as a close second. The analysis consists of a variety of professionals including titans of finance, politicians, physical therapy practitioners, consultants, etc.

Beyond the top two sources, we see company websites, credible media coverage, personal websites, bylined articles, professional associations, conference biographies, podcasts and transcripts, and reputable directories can all help corroborate the story.

The important thing to distinguish here is that there is no universal source hierarchy. It changes by model, question, freshness, and context. And the strongest position is a clear professional record supported consistently across several credible sources.

**Q: What does this shift in reputation management mean for communications professionals?**

A: Communications professionals are moving from managing messages to managing the evidence that machines use to interpret those messages.

Media coverage, executive profiles, bylined content, speaking appearances, and corporate websites still matter. In many ways, they matter more because they can become inputs into an AI-generated answer. But communications teams now need to determine whether those inputs form a clear, consistent, verifiable record.

That expands the mandate. Teams must monitor not only coverage, sentiment, and search position, but also whether a client appears in relevant AI answers, how their authority is framed, whether they are recommended, which sources receive credit, and where factual drift is emerging.

Authority Graph makes that work measurable across multiple executives and AI platforms. It gives agencies and enterprise teams a shared view of reputation risk, competitive position, citation ownership, and the specific corrections that deserve priority.

The next generation of reputation management protects two things at once: what people think about you and what machines can substantiate about you.

**Q: What should communications teams do right now to better understand how large language models represent their clients?**

A: Start with a controlled audit. Create 8-10 realistic questions that a journalist, prospective client, investor, recruiter, or partner might ask. Run the same questions across ChatGPT, Gemini, Claude, and Perplexity, with web search enabled where available. Because answers can vary, test more than once and record the date, prompt, response, and cited sources.

Then look for five things: Does the client appear? Is the description accurate? Does the answer recognize their real expertise? Are they recommended or merely mentioned? Which competitors and sources appear instead?

Compare the findings with a verified Source of Truth. Correct the highest-value gaps first, beginning with foundational assets such as LinkedIn, the official biography, company leadership pages, and credible third-party coverage.

For one person, Authority 360 can automate much of that ongoing monitoring through its weekly AI Pulse. For agencies and organizations managing multiple leaders, Authority Graph creates a multi-engine system of record, benchmarks each person across five dimensions, and shows where intervention will have the greatest value.

Do not optimize around one strange answer. One response is an anecdote. Consistent patterns are intelligence.

**Q: Some have said there is a push to make sure AI tools are actually reading your content. How is doing that different from just managing your online reputation?**

A: I would challenge the premise slightly: no one can guarantee that an AI system will retrieve, use, or cite a particular piece of content.

Traditional online reputation management usually asks: What appears when someone searches my name, and is the overall impression positive or negative?

Authority Intelligence asks a different set of questions. Can the system identify you correctly? Does it understand your actual expertise? Can it verify your claims? Does it recommend you for the opportunities that fit your record? Which sources does it use to reach those conclusions?

That last question matters. Authority Graph includes deep citation intelligence that breaks citations down by five dimensions – Search Presence, Authority Framing, Drift, and Hallucination and then classifies each citation by its role e.g. Is it a Role Carrier, Displacer, etc.

Publishing more is not necessarily the solution. The information must be accessible, specific, consistent, and supported elsewhere. The goal is to make an accurate interpretation easier to retrieve and substantiate, not just produce a positive impression.

**This article was originally published by EIN Presswire and is reprinted here with permission.** 
**Read the original article here: https://substack.einpresswire.com/p/ai-is-shaping-credibility-before**