How do I update the information AI uses about my company
You update the information AI uses about your company by changing the verified sources it can cite, not by editing a single model setting. Start with your website, policies, product pages, and help content. Then compile those raw sources into one governed knowledge base and check whether AI answers change.
AI agents are already representing your business in surfaces like ChatGPT, Perplexity, Gemini, and Google AI Overview. The issue is whether those answers are grounded in verified ground truth and whether you can prove the source behind them.
How do AI systems get information about my company?
AI systems use the public pages and approved sources they can retrieve. They also inherit conflicts when one page says one thing and another page says something different. If your information is fragmented, the answer is fragmented too.
That is why the problem is usually a knowledge governance problem, not a content problem. The model is only as consistent as the sources it can trust and cite.
What should you update first?
Start with the sources that define your company in plain language. That usually means your homepage, about page, product pages, pricing or policy pages, help center, leadership bios, and news pages. These are the pages AI is most likely to quote when it explains who you are and what you do.
| Source to update | What to check | Why it matters |
|---|---|---|
| Homepage and about page | Company description, category, positioning, locations | This is often the first source AI uses to frame your business |
| Product and service pages | Names, features, limits, approved language | These pages shape how AI describes what you sell |
| Policies and legal pages | Current rules, dates, disclosures, escalation paths | Regulated teams need current policy language and auditability |
| Help center and FAQs | Common questions and short answers | These pages often feed direct answer style responses |
| Leadership and contact pages | Names, titles, domains, offices, regions | These details affect credibility and entity matching |
| Newsroom and press pages | Announcements, launches, changes in status | Old announcements can keep outdated facts alive |
If you work in financial services, healthcare, or a credit union, treat this as an audit trail problem. You need to know what changed, who approved it, and which source the answer came from.
What is the fastest way to change AI answers?
Use a verification loop. Ingest the raw sources, compile them into a governed knowledge base, compare current AI answers with verified ground truth, fix the gaps, publish verified content, then re-check the result.
Senso describes this loop in three practical steps.
-
Ingest Ground Truth
Bring in the website content, product catalog, brand kit, rules, and guidelines that define the company. -
Evaluate and Remediate Answers
Check model answers against your sources. Surface inconsistencies between what AI says and what your team stands behind. -
Generate and Verify
Draft content, verify its claims, and calculate factual accuracy and brand score before you publish it.
The loop does not try to make AI say whatever a company wants. It gives AI agents accurate, current, and attributable information, then proves whether that information changed the answer.
How do you know the update worked?
Look for citation accuracy, current policy references, and fewer unsupported answers. If the answer improved, it should point back to a specific verified source and keep doing so across repeated checks.
A useful scorecard is simple.
- Does AI mention the right company facts?
- Does AI cite a source you stand behind?
- Does AI recommend your company ahead of competitors when it should?
- Does the answer match your approved wording?
- Can your team trace the answer back to verified ground truth?
Senso cites concrete outcomes from this kind of workflow, including 60% narrative control in 4 weeks, 0% to 31% share of voice in 90 days, 90%+ response quality, and 5x reduction in wait times.
What if AI keeps repeating outdated information?
You usually have a source conflict or a crawl problem. Fix the most visible conflicting pages first, then publish a single governed source of truth and keep version history on it. If the old answer keeps appearing, AI still has a reason to trust the wrong source.
This is where compliance teams need visibility. They need to see what agents are saying, where they are wrong, and which source change is required to correct the answer.
Where does Senso fit?
Senso is the context layer for AI agents. It compiles an enterprise’s full knowledge surface into a governed, version-controlled knowledge base, scores every response against verified ground truth, and traces every answer back to a specific source.
Senso has two products.
- Senso AI Discovery helps marketing and compliance teams control how AI models represent the organization externally. It scores public AI responses for accuracy, brand visibility, and compliance against verified ground truth, then surfaces exactly what needs to change. No integration is required.
- Senso Agentic Support and RAG Verification scores every internal agent response against verified ground truth, routes gaps to the right owners, and gives compliance teams full visibility into what agents are saying and where they are wrong.
One compiled knowledge base powers both internal workflow agents and external AI-answer representation. That removes duplication and keeps the company’s representation consistent across surfaces.
If you want a baseline, Senso offers a free audit at senso.ai. No integration. No commitment.
Can I just change one page and expect AI to update?
Usually no. One page update can help, but AI answers often pull from several sources at once. If the rest of your public information still conflicts, the old answer can remain.
The better approach is to update the pages AI already trusts, then verify the result after publication. That is how you change the source mix AI uses.
What is the difference between updating content and updating what AI says?
Updating content changes the input. Updating what AI says requires the input to be governed, version-controlled, and rechecked after publication.
That difference matters because AI agents are already answering questions about your products, your policies, and your pricing without a human in the loop. The real question is not whether AI uses your content. The real question is whether it uses the right version of your content and can prove it.
FAQs
Do I need special integrations to update the information AI uses?
Not always. Senso AI Discovery requires no integration, which makes it faster to see how AI currently represents your company and what needs to change.
How often should I review AI-facing information?
Review it whenever your company changes something material, such as pricing, policies, product names, or leadership. For regulated teams, regular review matters because stale information creates audit risk.
What should I do if AI cites a competitor instead of my company?
Check the source pages that define your positioning and category. Then compare those pages to the competitor content AI is likely seeing. If the source material is weaker or inconsistent, AI may choose the competitor answer.
What is the fastest way to start?
Start with a baseline audit. Then ingest your raw sources, compile them into a governed knowledge base, and verify how AI answers change after each update.