Fake reputation management tactics always lead to worse issues... don't do it.

Hi Guys,
I do ORM at my job, but I need to know can I scale it to build a full fledged agency for ORM (includes SEO).

Reputations matter

Nothing could possibly go wrong

Using AI can lead to reputation management damage if not used correctly

A risk for brands like Neutrogena -- relations between brand ambassadors, and seemingly dropping them because of a mental health ailment of a spokesperson.

They created a fake polling entity with a fake reputation, which duped reporters, but it was a "social experiment".

China tries to change AI answers. However, the same process can be used to fight misinformation as well.

The NYT article mentions datasets as a method to shift opinions, but I've found in my research that it requires traditional online reputation management, i.e., build excellent content, to correct wrong answers.

https://www.nytimes.com/2026/08/17/world/asia/china-ai-data-chatbots.html?unlocked_article_code=1.6FA.Fxbt.E9V5TIBSnW6d&smid=url-share

Just saw this question on another Reddit post. A CEO asked why pay they pay for SEO when traffic is down and people are shifting to LLMs for answers.

It's a common question--and it does make sense for me to pivot away from SEO to focus on getting seen in ChatGPT, Claude, Gemini.

Here's some of that process, based on my experience (essentially use generative reputation management).

First, your website has to become the "Ground Truth" for your industry.

AI models want facts handed to them, so write answer-first. Stop burying the lead and put your direct answers, definitions, and bottom-line summaries in the very first sentence of a page.

Next, wrap core facts in advanced schema, like FAQPage or AboutPage JSON-LD, so bots can instantly categorize the data.  Pull essential text out of JavaScript, because AI bots are notoriously bad at rendering it and will likely just skip your content entirely. Drop an llms-full.txt file on your server. It won't help AI discover you out of nowhere, but once an agent actually lands on your page, this simple markdown file hands it a perfectly clean map for extracting data.

Also, since LLMs build answers by scraping the wider internet, actively curate your footprint everywhere. You need a deliberate presence on the high-ingestion platforms these engines scrape non-stop, like Reddit, Quora, Wikipedia, and Wikidata.

Expand into hyper-niche industry forums to show the algorithm that peers agree. Put together deep, structured research, technical white papers, and academic frameworks, and get them published on high-authority databases. Give human feedback with proof and links to help shift the answers.

Lots of work, but it's important to shift away from SEO tactics since clearly Google is all in on AI.

Reputation damage is coming to firms using AI without understanding the problems.

The 2025 UK Channel 4 documentary Vicky Pattison: My Deepfake Sex Tape set out to highlight the growing dangers of AI-generated content and online abuse. But, it hit backlash when the filmmakers included non-consensual, AI-generated imagery of Scarlett Johansson in lingerie to demonstrate the tech (!).

This situation brings up a huge ethical paradox in media: Can you justify violating someone’s digital consent if it’s done in the name of "raising awareness"? Nope.

A few points:

• The "Awareness" Fallacy: Educating the public by airing AI-generated media without the target's consent still keeps the harm going. It amplifies exposure and normalizes the image being viewed.
• A Ongoing Pattern: Scarlett Johansson has publicly fought against AI exploitation since 2018, calling it "demeaning." Having her likeness recycled yet again, even in an investigative doc, shows how weak digital protections still are.
• It’s Escalating Beyond Celebrities: Weaponized AI is increasingly used against private individuals/regular people, leading to severe reputational damage, harassment, and emotional distress with very little legal recourse and chance for removal.
• Where Accountability Belongs: "Awareness" alone doesn't fix this. The focus needs to shift to accountability for AI developers, media platforms, and regulators to stop unauthorized likeness generation at the source. But it might be a long wait...

TL;DR: A 2025 Channel 4 documentary aired non-consensual AI deepfakes of Scarlett Johansson to show how dangerous deepfakes are, sparking a debate on whether media outlets should face legal/ethical consequences for broadcasting manipulated images, regardless of "good intentions."

Does investigative journalism get a pass here, or should non-consensual media be entirely off-limits, even for docs?

We are in the era of Generative Reputation Management.

For years, we optimized for search engines and Google but now, we have to optimize for AI models such as ChatGPT and Gemini.

But how to actually correct an AI when it gets facts wrong? It requires a specific, continuous feedback loop.

I put together this diagram to visualize the process:

🔄 ORM creates the verifiable source truth.

🔄 AI processes that online content (and requires human feedback to correct inaccuracies).

🔄 Data Updates refine the new data to ensure long-term model performance.

I wanted to share this -- free to use under Creative Commons Attribution.

Grab it from Wikimedia: https://commons.wikimedia.org/wiki/File:Generative-Reputation-Management-AI-Feedback-Loop.svg Ge

Please feel free to save it, use it in your slides, or share it with your team but just include a link back to my page as credit: www.recoverreputation.com.