When deciding who should review AI-generated content, match the reviewer to the subject, audience, and potential impact of the message. The employee who prompted the AI should check every draft, but that person may not be the only reviewer. Customer-facing answers, business reports, and content involving specialized expertise can call for a knowledgeable second reviewer with authority to edit, reject, or escalate the output.
The goal is not to send every draft through a lengthy approval chain. It is to make sure the right person verifies important details before the content is used, and that employees know what to do if an answer is uncertain or has already gone out.
Assign the reviewer based on risk and expertise
Start by asking what the content is for, who may rely on it, and what a mistake could mean for the business or its audience. A routine internal draft has a different review need from a customer answer that could shape someone’s decision or a report containing specialized recommendations.
- Routine, low-impact drafts: The employee who used AI can check the draft before using it. This may suit internal brainstorming or a message that will be edited further and is not making important promises or claims.
- Customer-facing or consequential content: The author should check the draft, then send it to a second person who understands the topic and audience. That reviewer should be able to revise it, decline approval, or refer it to someone with deeper expertise.
- Specialized or regulated work: A qualified professional responsible for the subject matter should review the content before it is used. A general manager may coordinate the workflow, but should not substitute for the expertise needed to verify a professional answer.
This risk-based approach reflects the kind of governance and accountability discussed in the NIST Generative AI Profile. For a business, the practical point is straightforward: the approver needs both enough knowledge to assess the output and enough authority to stop or correct it.
Who should check emails, reports, and customer answers?
AI-generated emails
For a routine internal email, the sender should check that the wording is accurate, appropriate, and complete before sending. If the email goes to a customer, supplier, or another external audience, consider a second review when it includes commitments, sensitive information, a difficult explanation, or a claim the sender cannot independently verify.
The reviewer does not need to be a manager just because AI was used. Choose someone who understands the relationship and the subject of the email. A manager or designated approver is appropriate when the message sets expectations, makes a business commitment, or could be difficult to correct once sent.
AI-generated reports
The report’s author should verify its purpose, inputs, and conclusions. A subject-matter expert should check claims, sources, calculations, and recommendations when the report may inform a significant business decision or requires expertise the author does not have. Do not treat polished writing as evidence that the analysis is sound.
If the report includes information drawn from company systems, confirm that the information is current and that it is appropriate to include. If someone cannot trace an important statement to a reliable source or verify how a conclusion was reached, pause approval and investigate rather than passing it along as fact.
AI-generated customer answers
A customer-service employee should review a response before it is sent, especially when it addresses a complaint, an unusual request, or a question about a product, service, account, or business commitment. Teams can define which routine answers may be sent after the employee’s own review and which topics always need a supervisor or specialist.
Escalate when the answer is uncertain, conflicts with approved information, requests sensitive details, involves a complaint that needs human judgment, or asks for advice outside the employee’s role. Research on chatbots in consumer finance discusses concerns that can arise when people rely on automated customer interactions. For your own workflow, provide a clear path to a person who can understand the issue and respond appropriately.
A practical AI content review checklist
Give reviewers a short, repeatable set of questions. The checklist should help them decide whether to approve, edit, or escalate, rather than encourage a quick read-through that misses substantive errors.
- Facts and sources: Can the key claims be verified? Are names, dates, figures, links, and references correct and relevant?
- Completeness: Does the draft answer the real question, or has it skipped an important condition, exception, or context?
- Promises and commitments: Does it imply the business will do something, meet a deadline, or provide an outcome that has not been approved?
- Privacy and access: Does it expose information that should not be shared with this audience? Check that the review itself follows the organization’s rules for handling sensitive data.
- Tone and audience: Is the message respectful, clear, and suitable for the recipient? Could a phrase sound dismissive or misleading in context?
- Need for escalation: Does the subject require a manager, technical specialist, or appropriately qualified professional to verify it?
In legal work, the reviewer should be the responsible legal professional, not simply the employee who asked an AI tool to draft text. The Florida Bar’s Opinion 24-1 addresses lawyers’ use of generative AI. Businesses handling legal work should establish a review path that puts professional judgment with the appropriate professional.
Make the approval process usable
Assign a workflow owner who maintains the rules for AI-assisted communications and documents. This person can define which content needs only an author check, which requires a second reviewer, and which must go to a subject-matter expert. The workflow owner should also make it clear who can approve each category and where employees should send questions.
Keep an approval record for content that carries meaningful business or customer impact. A simple record can note the content type, who reviewed it, whether it was approved or changed, and any follow-up needed. Avoid creating paperwork for every low-impact draft; recordkeeping should support accountability without making ordinary work unnecessarily difficult.
Plan for correction after release, too. Employees need a way to report an inaccurate response, notify the appropriate owner, and correct information through the right channel. If a customer needs help that the AI response cannot provide, the process should make it easy to bring in a person rather than continuing to generate uncertain answers.
Review procedures also depend on the tools and systems employees use. A cybersecurity risk assessment can help a business consider technology-related risks and controls, while clear responsibility for IT support can help employees know where to raise technical issues. Zevonix provides cybersecurity and IT consulting and strategy for businesses in Daytona Beach and surrounding areas.
Frequently asked questions
Should the person who used AI be responsible for checking its output?
Yes. The person using AI should check the draft before relying on it or passing it to someone else. For content with higher impact or specialized claims, that initial check does not replace review by a knowledgeable second person or qualified professional.
Can employees send AI-written customer replies without a manager reviewing them?
A business can define routine, low-impact replies that employees may send after checking them against approved information. Set clear boundaries and require escalation for uncertain, sensitive, unusual, or consequential questions.
Do all AI-generated emails and reports need a second reviewer?
No. The review level can depend on the audience, subject, and potential impact. The author can check a routine internal draft; customer-facing or specialized content may need a second reviewer with relevant knowledge.
When should an AI-generated answer be escalated to a person?
Escalate when the answer is uncertain, involves sensitive information or a significant commitment, falls outside the employee’s expertise, or requires judgment the approved process does not cover.
Build a review process people can follow
AI-generated content should not be approved simply because it sounds convincing. Assign review to someone who understands the subject and audience, scale the review to the content’s potential impact, and provide a clear route for corrections and escalation. If you want help aligning AI workflows with cybersecurity or technology planning, contact Zevonix at (386) 260-0777.