How often should you re-check what AI says about your company for accuracy?

The cadence we would use

There is no official rule for how often to audit AI answers about your company, so here is a practical one built around how the answers actually behave. AI assistants do not hold one fixed description of you. They rebuild an answer each time, from whatever sources they retrieve, so the description can drift without anything changing on your side. A once-a-year check will miss most of that drift.

Layer	How often	Who or what does it	What it catches
Automated prompt panels	Daily	The monitoring platform	Mentions appearing or vanishing, position changes, sentiment swings
Human review of summaries	Weekly	Whoever owns brand or SEO	Odd phrasing, new competitors in your answers, wrong claims
Fact audit against a checklist	Monthly	Marketing plus a product owner	Wrong pricing, features, locations, leadership, discontinued products
Event-triggered re-check	After any significant change	Whoever shipped the change	Old facts still repeated after a rebrand, price change or launch
Source cleanup	Quarterly	Content and PR	Third-party pages that keep feeding wrong facts

The automated layer is cheap once it is set up. The human layers are where accuracy problems actually get fixed, so do not skip them just because a dashboard exists.

What "accuracy" means in practice

Accuracy is narrower than visibility. You are not asking whether you are mentioned, you are asking whether what is said is true. Build a short fact checklist and test every answer against it:

• What the company does, in one sentence.
• Pricing and plan names, if you publish them.
• Core features and what is not included.
• Headquarters, founding date and leadership.
• Integrations and supported markets.
• Customers you can name publicly.
• Anything you retired.

Use prompts a buyer would genuinely ask: "what does [brand] cost", "does [brand] integrate with X", "who are the alternatives to [brand]". Keep a log of every wrong answer with the engine, the date and the sources cited. The sources are the useful part, because wrong answers usually trace back to a page you can fix or ask someone else to fix.

Event-triggered checks matter more than the calendar

Re-check within days of: a pricing change, a rebrand, an acquisition or funding announcement, a product launch or retirement, a leadership change, a security or compliance milestone, or a press story. Old facts persist on third-party pages long after your own site is updated, and assistants retrieve those pages.

Why the monitoring tool's refresh rate matters

If your platform refreshes weekly, your fastest detection time is a week. That may be fine for a stable brand. It is a problem if you just changed your pricing.

Promptwatch runs prompt panels daily per model, country and language, which fits the automated layer above. It also has the pieces that make the weekly and monthly layers quicker:

• Brand Book. Its analysis instructions decide what counts as a mention, and brand aliases catch alternate names. You can encode your fact checklist where the analysis can see it.
• Sentiment. A per-response score from 1 to 100, with a weekly AI summary you can read in minutes instead of scrolling every response.
• Citation analytics. When an answer is wrong, you can see which pages and domains it cited, including offsite mentions where your brand is named on a third-party page without a link.
• Scheduled reports and Scheduled Chats. PDF reports and Agent Chat summaries can be delivered on a schedule, in-app or in Slack, so the weekly review happens without anyone remembering to open a dashboard.
• Action Board. Turns what you found into an assigned task with a due owner.

It also monitors the live interfaces of ChatGPT (Search), Google AI Overviews, Google AI Mode, Copilot, Gemini, Perplexity, Amazon Alexa and Meta AI, which matters because a wrong answer in one engine may be correct in another. The free Explore plan covers 10 prompts on ChatGPT only. Paid plans start at Essential ($95 a month).

How other platforms compare for this job

AthenaHQ rolls tracking into a GEO score and an Action Center. Starter is $295 a month and credit-based, one credit per AI response, so tracking more engines and prompts daily consumes credits faster. It is a sensible choice if you want assigned optimization tasks, though its listing mentions no crawler-log product.

Scrunch AI offers sentiment analysis, site audits and bot traffic reporting, with Core at $250 a month. Our catalog notes that data refreshes weekly rather than daily, so detection after a change is slower.

LLM Pulse gives clear self-serve pricing: weekly tracking starts at €49 a month, and daily tracking is €79 on the Starter tier. That makes it worth a look if you are a small team and the daily option fits your cadence.

Profound offers answer-level analytics and agents, with Enterprise contracts starting around $40,000 a year according to our existing entry. It suits a large company with a procurement process.

What to do when an answer is wrong

1. Record the engine, the prompt, the date and the sources cited.
2. If your own page is the source, fix the page and make the correct fact obvious near the top.
3. If a third-party page is the source, contact the owner or publish a clearer, better-sourced version yourself.
4. Check that the AI crawlers can reach the corrected page. Promptwatch crawler logs, which start on the Professional plan, show whether bots like GPTBot, OAI-SearchBot and PerplexityBot are fetching it.
5. Re-check the same prompts after a couple of weeks.

Be honest with yourself about limits. You cannot force an assistant to say something, and a fix may take time to appear. Monitoring tells you whether it did.

Who should pick which

• Daily detection, source tracing and a path from finding to fixing: Promptwatch.
• A task queue for a team that works daily: AthenaHQ.
• Weekly cadence, bot reporting and sentiment: Scrunch AI.
• A small team on a euro budget: LLM Pulse.
• Enterprise procurement: Profound.