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Pause before you act or share it. Check each consequential claim against the original business record or a reliable primary source, restore any missing context, and correct anything already circulated. An AI answer is a draft—not a source of truth—and a follow-up from the same AI does not independently verify it.
Can you trust the answer enough to move forward?
Not until the claims that matter have been checked. AI tools can produce fluent, confident answers that contain incorrect facts, invented quotations or citations, stale information, or oversimplified advice. OpenAI cautions that confidence is not reliability in its ChatGPT guidance; Anthropic likewise describes misleading or ungrounded responses in its Claude guidance.
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Match the response to the stakes. A minor wording issue in an internal draft may need a quick correction; a false customer commitment, financial decision, or advice with legal, medical, or financial consequences calls for more careful review and appropriate subject-matter expertise. There is no single escalation threshold that fits every organization.
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- Source access: Can you inspect the original record or authoritative source?
- Reach: Has the answer stayed internal, or reached customers, leadership, or the public?
- Repeatability: Is this a one-off error or a pattern in a prompt, workflow, or system?
- Urgency and reversibility: Is a live process underway, and can the resulting action be undone?
What should you do immediately?
1. Stop the answer from spreading
Do not paste the questionable output into a customer email, report, policy, public post, or decision until it is checked. If it has already been shared or acted on, identify where it went and who may rely on it. Correct or withdraw the affected material promptly under your company’s procedures. Keep only the records needed to review the incident, following applicable privacy, confidentiality, and retention rules.
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2. Break the answer into claims and verify them
Check each material statement against the best available evidence: the original file or database, an approved contract or policy, an authoritative public source, or a responsible subject-matter owner. Verify names, dates, amounts, quotations, calculations, versions, and geographic or customer assumptions. If the AI supplied citations, open the original pages and confirm that the relevant passage supports the claim in context; a citation is not proof by itself.
A second answer from the same tool is not independent confirmation. You can ask the AI to identify assumptions or point out claims needing verification, but confirm the result against evidence. Microsoft puts the limit plainly: “Copilot can help you validate its output—but it can’t certify its own correctness.” Its validation guidance offers four useful checks:
- Source: Does the answer match the original material?
- Verified: Have consequential details been independently confirmed?
- Context: Are caveats, dependencies, or exceptions missing?
- Resilient: Would the answer remain sound for other scenarios, regions, or audiences?
3. Look for what the answer left out
An answer can contain no obvious false sentence and still lead to a bad decision if it omits a condition that changes the meaning. Ask what assumptions it made, whether its source material is current, and whether the conclusion applies to the relevant customer, product, region, or business unit. Microsoft notes that omissions can make AI output appear complete when a missing condition matters.
4. Correct, notify, and report
Replace or retract the inaccurate material wherever it was used. Notify affected colleagues or customers in a way proportionate to the risk and consistent with your incident procedures. Whether disclosure is required depends on the jurisdiction, industry, information, and impact; consult your legal or compliance lead for a real incident.
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You can also report the error through the product’s available feedback feature. Treat that report as feedback to the provider, not as a correction to your own records: your business still needs to fix its work product and communicate the correction to anyone who may rely on it. Review what you are submitting first. Do not send sensitive, confidential, or proprietary material through a feedback process without appropriate permission and data review.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How can your business reduce repeat errors?
Set a review rule for staff
Make the rule simple: AI output is a draft until a responsible person checks material claims against sources. Train staff to spot unsupported claims and missing context, and require review by a qualified person when an error could have significant consequences. OpenAI’s workplace guidance recommends human review and trusted-source checks, with expert review for important legal, medical, or financial decisions.
Improve a business-built AI workflow iteratively
If inaccurate answers recur in a system your organization built, treat the issue as a workflow risk to investigate rather than a prompt problem to guess at. Microsoft’s responsible AI guidance for Azure OpenAI systems organizes this work around identifying, measuring, mitigating, and operating, with testing in relevant scenarios and measurement after mitigations.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errors- Identify plausible harms and the situations in which they could occur.
- Create representative test cases and measure error frequency and severity in the real use context.
- Try suitable mitigations, such as constrained input or output formats, human review, or source references where appropriate.
- Measure again, record whether the change helped, and keep monitoring as the workflow changes.
Track the error type, where it occurred, its effect, and whether the fix worked. Controls such as prompts, citations, or guardrails can reduce particular risks, but they do not make errors impossible; appropriate controls depend on the scenario.
Keep accountability with the business
Using an AI tool does not move responsibility for a business decision or communication to the tool’s provider. Microsoft states, “Using AI doesn’t transfer accountability.” Assign a person to review consequential output, make the decision, and ensure corrections reach the people affected.
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