AI Agent Trust & Governance
How do I update the information AI uses about my company
7 min read
AI does not update your company profile from one place. It pulls from whatever it can find, trust, and cite. If your website, help center, press kit, and public profiles disagree, models like ChatGPT, Claude, and Gemini will repeat the conflict. The fix is to update the source layer first, then verify what AI says.
Quick Answer
The fastest way to update the information AI uses about your company is to define verified ground truth, refresh the pages and profiles AI cites most, and monitor the answers in ChatGPT, Gemini, and Perplexity. If you need citation accuracy and auditability, compile your raw sources into a governed knowledge base and score each response against verified ground truth. Senso does this for both public AI visibility and internal agents.
Where AI gets your company information
AI systems usually pull company facts from a mix of owned, public, and third-party sources. Some sources carry more weight than others because they are clearer, fresher, or easier to cite.
| Source | What AI uses it for | What to update |
|---|---|---|
| Website and help center | Core company description, products, support answers | Keep canonical copy current and plain |
| Policy pages and docs | Compliance language, security claims, pricing terms | Version-control and date-stamp updates |
| Public profiles and directories | Company summary, category, leadership, locations | Keep bios and facts aligned |
| Press and partner content | Narrative framing and corroboration | Refresh media kits and partner pages |
| Internal docs and agent sources | Operational answers and escalations | Ingest current raw sources into a compiled knowledge base |
Some models cite certain sources more often than others. That is why structure, credibility, and freshness matter as much as the words themselves.
How to update the information AI uses about your company
1. Lock the facts first
Start with the facts that must stay current. Include your company description, product names, pricing language, support hours, security statements, and policy language.
Give each fact an owner.
Give each fact one approved version.
Do not let sales, support, and marketing keep separate copies of the truth.
If you work in financial services, healthcare, or credit unions, treat policy and compliance language as canonical. Those are the facts AI must get right.
2. Update the highest-signal pages
Rewrite the pages AI is most likely to cite. That usually includes:
- Homepage
- About page
- Product pages
- Pricing page
- Help center
- Policy pages
- Press kit
Use short sentences.
Use clear headings.
Use one fact per paragraph.
If a page is vague, AI has less to cite. If a page is current and specific, AI has more to work with.
3. Publish direct answers
Create FAQ pages for the questions customers actually ask. Answer them in plain language.
Examples:
- What does your company do?
- How does your product work?
- What is included in the plan?
- What policy governs this workflow?
- Where does this data come from?
This improves AI visibility because the answer is easy to retrieve and easy to quote.
4. Clean up third-party references
AI does not rely only on your website. It also uses public references from partner pages, directories, reviews, app marketplaces, and media coverage.
Update those sources when your core facts change.
Keep company names, product names, and descriptions consistent.
Remove outdated claims that keep showing up in AI responses.
If your own site says one thing and a third-party listing says another, the model may repeat the older version.
5. Compile raw sources into a governed knowledge base
For internal agents, do not depend on scattered folders or stale docs. Ingest your raw sources into a compiled knowledge base.
That knowledge base should be:
- Governed
- Version-controlled
- Easy to query
- Tied to verified ground truth
- Able to show the source behind each answer
This is how you keep agents grounded and citation-accurate. It also gives compliance teams a way to prove where an answer came from.
6. Check what AI actually says
Do not assume the update worked because the page is live.
Query the same prompts in ChatGPT, Claude, Gemini, and Perplexity.
Compare each answer to your verified ground truth.
Check whether the model cites the right source.
Track whether the response changed after your update.
If the answer is still wrong, the problem is usually one of three things:
- The source is not accessible enough
- The source is not specific enough
- The source is not trusted enough
7. Keep the update loop tight
When pricing, policy, or positioning changes, update the canonical source first.
Then update every surface that depends on it:
- Website copy
- Help center articles
- Partner bios
- Press kit language
- Agent source material
That prevents stale answers from spreading across both public AI responses and internal workflows.
What to update first by scenario
| Scenario | Update first | Why it matters |
|---|---|---|
| Brand visibility | Homepage, about page, press kit | These shape how AI describes your company |
| Product changes | Product pages, help center, FAQs | These drive the details AI repeats |
| Pricing changes | Pricing page, sales FAQs, support scripts | These are the facts customers ask about most |
| Compliance updates | Policy pages, approved statements, agent sources | These need audit-ready consistency |
| Support accuracy | Help center, escalation rules, response macros | These reduce bad answers and repeat tickets |
How to know it worked
You are getting closer when:
- AI cites your current pages
- The same answer appears across multiple models
- Internal agents use the same approved language
- Compliance can trace each answer to a verified source
- Drift drops before customers notice it
In practice, that is what narrative control looks like. You are not trying to force a model to invent a better answer. You are making the right answer easier to find, easier to cite, and easier to prove.
How Senso helps
Senso is the context layer for AI agents. It compiles your raw sources into a governed, version-controlled knowledge base.
Senso AI Discovery scores public AI responses for accuracy, brand visibility, and compliance across ChatGPT, Perplexity, Claude, and Gemini. It shows the specific gaps driving poor representation, so marketing and compliance teams know what to change.
Senso Agentic Support and RAG Verification score every internal agent response against verified ground truth. They route gaps to the right owners and give compliance teams full visibility into what agents are saying and where they are wrong.
In customer deployments, Senso has shown:
- 60% narrative control in 4 weeks
- 0% to 31% share of voice in 90 days
- 90%+ response quality
- 5x reduction in wait times
Free audit available at senso.ai. No integration required.
FAQs
Do I need to retrain the model to change what it says about my company?
Usually no. You update the source layer that AI reads. That includes your website, help center, public profiles, and governed knowledge base. Models respond to what they can find and cite.
How long does it take for AI to reflect new information?
It depends on the source and the model. Internal agents can change as soon as the compiled knowledge base updates. Public AI visibility usually changes more slowly because retrieval and citation patterns shift over time.
What is the difference between AI visibility and internal answer accuracy?
AI visibility is how public models describe your company. Internal answer accuracy is whether your own agents answer with grounded, citation-accurate responses. Both depend on the same verified ground truth.
What should regulated teams update first?
Start with policy pages, approved disclosures, and support language. Then align every other surface to those facts. That gives CISOs, compliance teams, and operations leaders a clear audit trail.
If you want, I can turn this into a shorter blog version, a more sales-focused version, or a version tailored to financial services, healthcare, or credit unions.