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Give the AI a real audience, a clear communication goal, your brand’s approved voice and perspective, and evidence it can use; then have an accountable person edit and verify the draft before publication. AI output is a starting point, not a substitute for knowing what your organization wants to say or approving what it claims.
Why does AI-generated marketing content sound generic?
A draft often feels generic when the brief names only a topic—such as “write a product announcement”—without explaining who needs the message, what they need from it, or what the organization can contribute that is specific and useful. The resulting copy may be grammatically smooth while saying little that distinguishes this message from a broad summary of the subject.
The problem is not solved by asking for “more personality” or adding a longer list of tone adjectives. Those requests still leave the system without a concrete point of view, customer insight, approved evidence, or clear purpose. Nor does generating many versions guarantee a strong result: options are useful only when they give a human meaningfully different ideas to assess.
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What should you give the AI before it drafts?
Start with a brief that explains the communication problem, rather than asking for copy about a topic in isolation. Harvard SEAS recommends being clear and specific in prompts and maintaining a consistent brand voice; the brief below turns that guidance into a practical working checklist.
- Audience: Identify who will read the content and what they already know, need, or care about. Avoid treating a broad label such as “customers” as enough context if the message is meant for a more specific group.
- Purpose: State what the reader should understand, feel, or do after reading. Choose the primary outcome so the draft has a reason to include each point.
- Channel and format: Name the placement—such as an email, landing page, ad, or social post—and include the format, length, and constraints that matter for that placement.
- Brand guidance: Supply approved terms, preferred terminology, tone, formality, humor, and language to avoid. Include examples when available, but ask a human to judge whether the result fits rather than assuming a few examples fully describe the brand.
- Point of view: Explain what the organization knows, believes, or does that is relevant to this particular audience and message. This is where a real reason for the communication belongs, not a slogan added to dress up an otherwise broad draft.
- Evidence and boundaries: List the verified facts, customer insights, examples, or approved claims the draft may use. State what must not be invented, and do not ask the model to fill gaps with plausible-sounding specifics.
- Drafting request: Ask for a draft or a small set of genuinely different angles. Specify the material difference you want to explore—such as a different reader concern or emphasis—instead of requesting a large batch of near-duplicates.
- Review plan: Decide who will check substance, voice, factual support, claims, privacy, and required approvals before the draft is published.
A short brief with real information is more useful than a long prompt made mostly of vague style directions. If a detail is not known or approved, say so plainly and have the writer resolve it with the appropriate person rather than inviting the AI to guess.
How do you turn the brief into a useful first draft?
Use the model to explore and organize material, not to certify the final message. A focused sequence helps a team see whether the draft has a distinct idea before it invests time in polishing sentences.
- Choose one communication problem. Write down the audience, what they need, and what the content should help them do. If the brief tries to serve several unrelated audiences or outcomes, narrow it or plan separate versions.
- Provide approved context. Include brand guidance, the relevant point of view, verified evidence, channel constraints, and explicit boundaries. Use information the team is allowed to share with the system.
- Ask for alternatives when there is a real choice. Request a few distinct approaches if the team is deciding which reader concern or message emphasis to lead with. Select an approach based on audience relevance and evidence, not simply because it sounds the most dramatic.
- Develop the chosen approach. Ask for a draft that follows the selected direction and respects the format. Treat the copy as editable material; do not publish it merely because it is complete or fluent.
- Review the substance before the style. Check whether the draft answers the intended reader’s need, reflects the organization’s perspective, and uses only supportable details. Editing sentence rhythm cannot rescue a draft whose central message is empty or unsupported.
- Revise and approve. Replace weak or vague passages with accurate specifics, verify each material claim, and route the final version through the organization’s applicable review process. An accountable human—not the model—makes the publication decision.
This order matters: a team that polishes first can spend time improving the sound of a message that still has no useful point. LinkedIn’s guidance recommends reviewing, editing, and approving AI-assisted content and makes the author responsible for what is posted.
How do you edit a draft so it sounds like your brand?
Make the draft more distinctive by adding accurate information and a clear organizational perspective, not by sprinkling in catchphrases or intensifying the tone. Edit at the level of meaning first, then align vocabulary and phrasing with approved brand guidance.
Replace broad statements with supported specifics
Mark sentences that could be pasted unchanged into almost any company’s campaign. Ask what concrete, verified detail would make each one relevant to this organization and this audience. That detail might be an approved fact, an actual customer insight, an example the organization can stand behind, or a clearer explanation of what the message means for the reader. If the team cannot support a more specific claim, remove or narrow the statement instead of inventing one.
Make the point of view visible
Check whether the draft explains why the organization is communicating this message and what perspective it can credibly offer. A brand’s point of view is not merely a confident tone: it should connect to what the organization knows, believes, or does in a way that matters to the reader. If a paragraph contains only general advice or familiar marketing language, reconsider its purpose.
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Use the brand’s vocabulary deliberately
Compare terms, formality, humor, and phrasing against the approved guidance. Replace terms the organization avoids, and use preferred terms where they clarify the message. Do not force every sentence to sound quirky or conversational if that is not the right fit for the audience or channel.
Remove filler and unsupported certainty
Cut familiar openings, empty transitions, repeated benefits, and claims that sound impressive but do not add information. Check comparisons, superlatives, testimonials, and statistics particularly carefully: each needs support the organization can substantiate. When the draft cannot establish the basis for a claim, do not leave it in simply because the wording is persuasive.
Read the finished copy as its intended audience
Ask whether the reader can tell what matters, why the message is relevant, and what to do next if the format calls for an action. Check that each detail serves the purpose and that the voice fits the placement. A distinctive brand voice should make the message clearer and more recognizable, not distract from what the reader needs to understand.
What should a human reviewer check before publication?
Assign a person with appropriate responsibility to approve the final material. Review should cover more than grammar: AI-assisted copy can be fluent while still missing the audience, misrepresenting the brand, or making a claim the organization cannot support.
- Audience fit: Does the content address the intended reader’s actual need and suit the channel?
- Brand fit: Does it reflect approved terminology, tone, and the organization’s real perspective?
- Accuracy and substantiation: Can the team verify factual statements, comparisons, superlatives, testimonials, and statistics? Are claims presented no more broadly than their evidence allows?
- Privacy and data use: Was any confidential or customer information shared with the system, and was its use permitted under the organization’s rules and applicable protections?
- Approvals: Has the content passed the organization’s relevant review process before it goes live?
- Disclosure and context: Would readers benefit from knowing how AI was used, given the content’s potential impact and how much AI created or changed it?
Google Search Central advises focusing on accuracy, quality, and relevance when creating web content, including automatically generated content. Its people-first guidance also treats authorship and explaining automation as context questions: provide users with information about automation when it helps them understand the content. This is not a claim that AI-assisted content is inherently unsuitable; the practical test is whether the page is useful, accurate, and represented honestly.
Disclosure is not a one-size-fits-all wording decision. The National AI Centre’s April 22, 2026 guidance says the decision depends on context, potential impact, and how much AI contributed or changed meaning. The ICC’s March 20, 2026 guide addresses AI in creating, targeting, or delivering marketing, including transparency, responsibility, claim substantiation, data use, consent for likenesses, and governance. For a particular campaign, check applicable local law and the organization’s current policy; general guidance is not legal advice.
How should a team compare AI-assisted content workflows?
Compare the process around the tool as carefully as the drafting itself. The useful question is whether the workflow lets the team provide approved context, make meaningful edits, check claims, protect information, and approve the final content.
- Can the team provide and maintain approved brand guidance and relevant audience context?
- Can reviewers edit meaningfully and approve the final material?
- Does the workflow support review of facts and advertising claims?
- Does it fit the channel, audience, and format being used?
- Are confidentiality, customer information, retention, access, and applicable contractual protections handled appropriately?
- Can the process provide useful context or disclosure when AI materially creates or changes the content?
These are workflow review criteria, not a ranking of products. A team should assess them against its own content, policies, and review responsibilities rather than assuming that a particular feature or tool guarantees original, on-brand writing.
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Generic copy is often a process problem: a team gives the system little real context, asks it to substitute for a decision, or treats completion as approval. Avoid these failure modes:
- Prompting with only a topic: Add the reader, purpose, placement, brand perspective, and usable evidence before requesting copy.
- Using tone words as a substitute for insight: “Warm,” “bold,” or “witty” cannot supply a real customer need or organizational point of view.
- Requesting volume instead of useful choices: Ask for distinct angles only when there is a decision to make, then select and develop one.
- Publishing the first fluent draft: Have a human edit the substance, voice, accuracy, claims, privacy, and approvals.
- Leaving unsupported claims in place: Verify claims and remove or narrow what the organization cannot substantiate.
- Assuming disclosure is always identical: Consider the content’s context and impact, how materially AI changed it, applicable local requirements, and current organizational policy.
LinkedIn describes low-effort, generic, repetitive content without a clear point of view or substance as “AI slop” in its platform guidance. That is LinkedIn’s description, not a universal measurement of AI-written content or a guarantee about how any post will be distributed. Its practical relevance is straightforward: put substance and a real perspective ahead of output volume.
How do you prevent generic AI marketing copy?
Give the system a specific audience, purpose, channel, approved brand guidance, real organizational perspective, and verified evidence. Use it to explore or draft, then have a responsible human add the missing specifics, remove filler, verify claims and information handling, and approve the final message. That process improves the odds that the copy is useful and recognizable without pretending any prompt can guarantee originality.
Frequently Asked Questions
Should I put customer data in a prompt to make marketing copy more specific?
Use only information your organization is permitted to share with the system, and follow its rules for confidential and customer data. When individual-level detail is not necessary, provide an approved, generalized insight instead of identifiable customer information.
Can I ask AI to write in a competitor’s or a specific person’s voice?
A more reliable brief describes your own approved brand characteristics and the reader’s needs rather than using another party’s identity as a shortcut. That gives reviewers criteria they can evaluate against your brand guidance and the actual purpose of the message.
How can I tell whether a draft is genuinely on-brand?
Have a reviewer compare it with approved terminology, tone, audience expectations, and the organization’s real perspective—not just with other AI drafts. Ask the reviewer to identify what in the copy is specific to this message and whether that specificity is supported.
Does using AI mean I need to disclose it in every marketing message?
The guidance cited here does not prescribe one universal disclosure for every use. Consider context, potential impact, and how much AI contributed or changed meaning, then check current local requirements and your organization’s policy.
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