The Company Description That Actually Shows Up in AI
Your company description is broken. Not because it's badly written. It's broken because it was written for humans, not for the systems that now answer questions about your business.
When someone asks ChatGPT or Claude what your company does, the AI pulls from somewhere. Maybe your website. Maybe your LinkedIn. Maybe an old press release. The problem is most descriptions are optimized for first impressions, not for extraction. They're designed to impress. They're not designed to be cited.
AI engines parse information differently than humans do. They're looking for specificity, not poetry. They need to understand what problem you solve before they can answer a question about you.
Start by killing the positioning. Your company description doesn't need to be clever. It needs to be clear. "We help teams collaborate better" loses to "We provide project management software that helps distributed teams track tasks and deadlines." The second one tells the AI exactly what to cite when someone asks about your product category.
Next, lead with what you do, not who you are. Most descriptions bury the actual product three sentences in. Put the product first. Then add context. An AI scanning your description will grab the first accurate statement it finds and use it in an answer. Make that statement useful.
Include the problems you solve. Name them directly. "We solve cold email deliverability" is better than "We improve email performance." When an AI needs to answer a question about cold email tools, it looks for mentions of deliverability, response rates, and automation. If your description says you solve those things, you get cited.
Most brands fail at this part: they avoid specificity because it feels limiting. But AI visibility requires exactly the opposite. The more specific your description, the more likely you appear when someone asks about that specific thing.
Use your actual keywords. Not stuffed in awkwardly. But if you're a sales intelligence platform, say "sales intelligence platform." If you help companies with customer retention, mention customer retention and churn. AI models are trained on language patterns. They recognize these terms. They associate them with your company. When GEO and AEO tools scan your business description, they're looking for these exact words to build relevance signals.
Be specific about who you serve. "For B2B companies" beats "For businesses." "For GTM teams at Series A startups" beats "For growth teams." This specificity helps AI engines route your company to the right answers. It also prevents mismatches where your description gets cited for use cases you don't actually serve well.
Avoid marketing adjectives. "Innovative," "cutting-edge," "powerful," and "intelligent" add nothing. They signal that you're trying to impress, not inform. AI engines mostly ignore them. They're looking for nouns and verbs. What do you build? What does it do? Write that.
Length matters less than you think. A tight 2-3 sentence description wins over a 200-word paragraph. AI systems extract information more cleanly from concise writing. They know what you do faster. They can serve that information to answers faster. Short descriptions also rank higher in AI citations because they're easier to quote directly.
Test your description against these questions. If someone searched "tools that do X" would your description appear? If an AI needed to answer "what problem does Y solve," would your description get pulled? If the answer to both is yes, you're in the right direction.
Your company description is now part of your AEO strategy. It's infrastructure. It's how you show up when AI systems answer questions about what you do. Write it like you're explaining your business to a very literal engineer. Skip the sell. Focus on accuracy and clarity.
Check your AI visibility baseline at engagemii.com/aeo. The free AEO score shows you where your company description stands right now and what's holding you back from appearing in AI answers. It's the fastest way to see if you're being cited or ignored.
Originally published on Engagemii
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