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Give AI a specific audience, a real communication goal, approved brand guidance, and verified evidence; then have an accountable person reshape and check the draft before it is published. Generic copy usually reflects a generic brief or an unedited first draft—not an unavoidable quality of AI. The useful approach is to treat AI as a drafting aid, not as the source of your brand’s perspective or approval.
Why does AI-generated marketing content sound generic?
A model can produce fluent language without knowing what your customers actually need, what your organization believes, or which claims it can substantiate. If a prompt supplies only a subject—“write a post about our new service”—the system has little reason to produce anything beyond familiar category language. A polished result can still be interchangeable with copy from another company.
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LinkedIn’s guidance for professional content emphasizes that AI-assisted material should retain the author’s own voice, perspective, and experience. Its description of low-effort, repetitive material without a clear point of view as “AI slop” is platform guidance, not a measurement of all AI writing or a prediction about how a post will perform. The practical point is straightforward: the person or organization publishing the content must contribute something real.
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What should you give AI before asking it to write?
Start with the communication problem, not a request to “make this engaging.” A useful brief tells the system who the reader is, what matters to that reader, what the content should accomplish, and what the organization can responsibly say.
Build a brief with these fields
- Audience: Identify the intended reader and what they already know, need, or care about. “Small-business owners comparing payroll processes” is more useful than “everyone interested in business.”
- Purpose: State what a reader should understand, feel, or do after reading. Choose a real outcome rather than vague goals such as “raise awareness.”
- Channel and format: Specify whether the draft is an email, landing page, ad, or social post. Include length, structure, and any channel-specific constraints.
- Brand guidance: Provide approved terminology, tone, level of formality, and words or approaches to avoid. Include examples only when they are genuinely representative and approved for reuse.
- Point of view: Explain what the organization knows, does, or believes that is relevant to this particular message. This is where an actual customer insight or reason for communicating belongs.
- Evidence and boundaries: Supply verified facts, approved claims, examples, or customer insights that may be used. Identify what must not be invented or implied.
- Drafting request: Ask for a draft or a small number of meaningfully different angles. Explain the difference you want between them, rather than asking for a large batch of near-duplicates.
- Review requirements: Tell the team what a human must check, including factual support, brand fit, claims, privacy, and internal approvals.
Harvard SEAS’s prompt guidance recommends clarity and specificity, and its brand-voice guidance supports consistent instructions. The brief above turns those principles into a working document; it is not a template quoted from Harvard.
Reusable brief template
Copy and adapt this as a starting point. Replace each instruction with approved, campaign-specific information rather than asking the model to fill in unknown facts.
Audience: [who will read this and what they already know or care about]
Purpose: [what the reader should understand, feel, or do]
Channel and format: [where it will appear, length, and constraints]
Brand guidance: [approved tone, terms, and language to avoid]
Point of view: [relevant organizational knowledge, belief, or customer insight]
Evidence: [verified facts and approved claims the draft may use]
Do not invent: [missing facts, outcomes, comparisons, testimonials, or statistics]
Draft request: [one draft or a few distinct angles, with the difference specified]
Review: [checks and approvals required before publication]A model cannot verify that this brief represents the brand merely because it has received the text. A person who knows the brand still has to decide whether the instructions and resulting copy fit.
How do you get useful options without generating more filler?
Use the model to explore a decision, not just to multiply wording. Ask for a few distinct approaches tied to a real difference in audience need, message emphasis, or format, then select and develop the one that best serves the communication goal.
For example, a team might ask for one angle that explains a practical problem, one that addresses a common objection, and one that clarifies a product’s intended use. Those are useful alternatives only if the organization has evidence and a genuine reason to make each point. If the model cannot distinguish the options using the brief, add relevant context or write the key insight yourself.
Do not treat a high number of variations as proof of originality. The system can rephrase a generic premise repeatedly without producing a meaningful new idea. Human judgment should determine which angle is worth developing and what concrete information makes it specific.
How should you edit an AI draft to make it sound like your brand?
Edit in layers: first make the message useful and accurate, then make its expression fit the brand. Changing a few adjectives or adding a slogan will not fix a draft whose underlying point could belong to any company.
1. Check whether there is a real point
Identify the main thing the reader should take away. If the draft contains only broad praise, familiar promises, or a summary of the topic, add the organization’s relevant perspective or rewrite the angle. Do not invent an insight simply to make the copy feel distinctive.
2. Replace vague wording with supportable specifics
Look for claims that could apply to nearly any product or business. Where the organization has verified details, use the detail that helps this audience understand the message. If there is no evidence for a claim, remove it or narrow it to what the organization can actually support.
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3. Apply the brand’s real vocabulary and voice
Use approved terms and the level of formality the organization actually uses. Check that examples and phrases reflect the current brand rather than one convenient sample. A voice guide should help an editor make a decision; it should not become a checklist of surface traits that obscures the message.
4. Remove familiar filler and unsupported certainty
Cut language that takes up space without adding meaning. Be especially careful with superlatives, comparisons, performance claims, statistics, testimonials, and promises: fluent phrasing is not evidence. Keep only statements the organization can verify and is authorized to make.
5. Read it as the intended reader
Ask whether the draft answers that reader’s actual question in this channel and format. A technically accurate paragraph may still be irrelevant, too broad, or poorly suited to the placement. Revise for comprehension and usefulness before polishing rhythm.
Experian’s brand guidance frames AI output as a first draft to refine. That is a sound editorial standard: AI can help produce material to work on, but the final wording should express an approved organizational point of view and be supported by facts.
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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteWhat must a human check before publication?
A named person should own the final decision to publish. That review is more than proofreading: it is a check that the content is appropriate for its audience, accurate, consistent with the brand, and cleared under the organization’s processes.
- Audience and purpose: Does the content address the reader and do the job the brief specifies?
- Brand fit: Does the message reflect the organization’s approved voice and relevant perspective rather than generic category language?
- Accuracy and substantiation: Can the team support every factual statement, comparison, testimonial, statistic, and superlative?
- Privacy and data: Does the draft or the workflow expose confidential information or customer data in a way the organization has not approved?
- Rights and consent: If the content uses a person’s likeness or other material requiring permission, has the relevant consent been obtained?
- Approvals: Have the necessary legal, compliance, brand, or campaign reviewers signed off under the organization’s current process?
These checks align with responsible-marketing considerations raised by the American Association of Advertising Agencies (AAMA), including human creative direction, factual claims, confidential information, customer data, and synthetic social proof. They are workflow considerations, not a substitute for applicable law or an organization’s own policies.
Should you tell readers that marketing content used AI?
There is no single disclosure rule that fits every kind of AI assistance. The decision should reflect the content, its potential impact, and how much AI contributed or changed its meaning; check applicable local law and the organization’s current policy for a real campaign.
Google Search Central advises web publishers to focus on accuracy, quality, and relevance when content is automatically generated, and says it can make sense to give users context about how automation was used. Its people-first guidance also treats explanations of automation as useful when that context helps readers. This is not a claim that AI-assisted content is automatically unsuitable: the focus is whether the content is useful and represented accurately.
The International Chamber of Commerce’s guide dated March 20, 2026, applies its Advertising and Marketing Communications Code to AI used to create, target, or deliver marketing. Its stated topics include transparency, responsibility, substantiation of claims, data use, consent for likenesses, and governance. The National AI Centre’s guidance dated April 22, 2026, says disclosure depends on context, potential impact, and the extent to which AI contributed or changed meaning. Neither general guidance replaces advice about the rules that apply to a particular campaign or location.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How can a team compare AI-assisted content workflows?
Compare the process against the work it must support, rather than assuming a platform or a larger volume of output will make the writing distinctive. The relevant question is whether the team can provide good guidance, make substantive edits, check claims, and approve the final material responsibly.
| What to compare | Questions for the team |
|---|---|
| Brand guidance | Can staff supply and maintain approved terminology, tone, and relevant context? |
| Human review | Can reviewers make meaningful changes and approve the final version? |
| Claims review | Does the workflow support checking factual statements and advertising claims against evidence? |
| Audience and format | Does it fit the intended readers, channel, and content format? |
| Confidentiality and customer information | How are sensitive information, access, retention, and applicable contractual protections handled? |
| Context and disclosure | Can the process provide useful context when AI materially creates or changes content? |
These are decision criteria, not a product ranking. Choose a workflow that makes responsibilities clear and fits the sensitivity and approval needs of the material being produced.
What should you measure after changing the process?
Do not assume a prompt change improved performance because the copy sounds more polished. No directly relevant published statistic in the sources reviewed establishes how often AI marketing copy sounds generic or quantifies the effect of these editing practices.
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Frequently Asked Questions
Can AI learn my brand voice from a few examples?
Examples can illustrate preferred language, but they do not establish that every new draft fits the brand or campaign. Keep an approved voice guide and have someone familiar with the brand judge each final piece.
Will AI detectors tell me whether marketing copy is generic?
Genericness is a question of substance, audience fit, and point of view, not simply whether text was produced by AI. The cited guidance does not establish an AI detector as a reliable way to assess those qualities.
Can I use customer reviews or testimonials in an AI prompt?
Only use customer material in ways permitted by your privacy, consent, and content policies. A draft should not turn a review into a fabricated endorsement or imply a customer said something they did not.
Does Google penalize every page written with AI?
Google Search Central’s guidance focuses on accuracy, quality, and relevance rather than treating AI assistance alone as disqualifying. A page still needs to serve readers and represent its content honestly.
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