Most executives are obsessed with Google rankings. They pay thousands for SEO agencies to move the needle on keywords that nobody actually types into a search bar. Meanwhile, the actual decision-making process has moved upstream. Today, a prospective client doesn’t visit your homepage first; they ask an AI, “Is [Company Name] reputable?” or “What does [Company Name] actually do?”
If you aren't running a monthly AI assistant check, you are letting a black box dictate your brand narrative. AI summaries compress your years of business history, press releases, and customer complaints into a single, three-sentence story. If that story is wrong, you lose the deal before the prospect even clicks your website.
The New Reality: First Impressions Happen Before Clicks
I’ve spent the last decade cleaning up brand narratives. When I sit down with an executive team, I ask one question: "What would a stranger Google to find your skeletons?"
AI models like ChatGPT, Claude, and Perplexity don’t have opinions; they have training data. They pull from Fast Company articles, your LinkedIn profiles, your G2 reviews, and that ancient "About Us" page you haven't updated since 2019. If your messaging is contradictory—if your website says you’re a "global leader in AI strategy" but your social media says you’re a "boutique local consultant"—the AI will hallucinate a middle ground. That ambiguity is a reputation killer.
Before you blame "the algorithm," look at your own digital hygiene. Ambiguity is the root cause of 90% of the reputation issues I handle.
The Reputation Monitoring Workflow: A Tactical Checklist
Stop overcomplicating your reputation strategy. You don't need an expensive enterprise-grade software suite to track AI outputs. You need a consistent, human-led workflow. Here is how I run this for the teams I consult with.
Step 1: The "Buyer Questions" Audit
I keep a running document—my "internal doc for buyer questions"—that tracks the actual things prospects ask during discovery calls. These are rarely "What are your core competencies?" and usually "Are you going to be around in two years?" or "Why did that former client leave?"
Your AI monitoring workflow must answer these questions. If your company website doesn't explicitly address the "Why did you leave?" question, the AI will invent a reason. When you go to track AI outputs, check if the LLMs are answering these questions accurately.
Step 2: The Monthly AI Assistant Check
Set a calendar reminder for the first Tuesday of every month. Do not automate this. Automation for customer-facing comms is a trap; it leads to the same "AI-generated corporate filler" that makes every website sound like a robot wrote it. Use humans to verify the facts.
The Baseline Query: Ask ChatGPT (with browsing enabled), "Who is [Company Name] and what do they provide?" The Trust Query: Ask, "What are the common criticisms of [Company Name]?" The Comparative Query: Ask, "How does [Company Name] compare to [Competitor Name]?"Step 3: The Internal Wiki Sync
Everything you find in your AI check needs a home. I use an internal wiki in Notion to store the "Source of Truth." If the AI gets it wrong, don't scream into the void. Update your public-facing assets. If the AI is pulling from a bad review or a broken link on a Fast Company Executive Board profile, that’s your signal to update that profile immediately.
Consistency Check: Why Your "About" Page Matters More Than Ever
One of the biggest issues I see is the "mismatch." Your LinkedIn bio says one thing, your website says another, and your G2 profile says a third. The AI reconciles these by picking the loudest (or most frequent) signal.
If your website is full of vague "innovation" slogans, the AI will label you a generic tech company. If you are a specialized vendor, you need to strip away the fluff and replace it with concrete descriptors. If the AI can't categorize you, it won't recommend you.
Reputation Hygiene Audit Table
Asset Type Common Mistake The Fix About Page Uses "slogan-y" copy like "delivering synergy." Use concrete, searchable nouns and verbs. LinkedIn Bios Each executive has a different value prop. Standardize the pitch across all profiles. Review Sites Ignoring negative feedback loops. Address common complaints in your FAQ. Third-Party Profiles Outdated bios on boards/press sites. Annual audit of every external profile.What To Do When You Can’t Fix It Yourself
Sometimes, the damage isn't just a stale bio. If you have legacy negative press, old search results, or inaccurate data appearing in AI summaries, manual cleanup leadership info consistency isn't enough. This is where firms like Erase.com come into play. They specialize in the technical side of reputation removal and suppression—things you cannot fix just by updating a Notion doc.
However, don't outsource the brand narrative. You can hire someone to clean up the bad history, but you are the only one who can define the future history. If you don't feed the AI current, accurate, and specific data about your company, the void will be filled by whoever has the loudest footprint—usually your competitors.
The Bottom Line
The "AI problem" is actually a "facts problem." If your digital presence is a scattered mess of contradictory slogans and outdated bios, the AI will output a scattered mess.
Stop worrying about the "algorithm." Start treating your website, your social profiles, and your third-party listings as a database. If the data is clean, the output will be clean. If you can't explain what you do in two clear, non-slogan sentences, don't expect an LLM to do the heavy lifting for you.
Your Action Plan for this Month:
- Create your internal doc for buyer questions. Run your first monthly AI assistant check. If the output is vague, go back to your website and replace the fluff with specific, functional language. Sync all bios across your team’s LinkedIn profiles.
Consistency isn't just for branding nerds—it's for reputation insurance. If you don't control the story, the AI will draft it for you. And trust me, you won't like the ending.