AI Writing Sounds Generic? Seven Steps to Make It Sound Like You

To make AI writing sound like your business, give it material before it writes: your product facts, customers' own words, a voice guide with real rules and samples of your best writing. Brief each piece with a specific angle and audience. Then edit out the stock phrases AI reaches for. Context does most of the work; editing does the rest.

How do you make AI writing sound like your business?

Give it your business before you give it the task. AI writes generically when it knows nothing specific, so it falls back on the average of everything it has read. Supply product facts, customer language, a voice guide and examples, brief each piece clearly, and edit with a short list of what to remove.

The explanation of why AI defaults to generic is in the guide to why AI sounds generic. This article is the practical side: seven steps, in order.

What should you give AI before it writes?

Four things: approved facts about your product and company, your customers' own words, a voice guide with concrete rules, and two or three samples of your best writing. Keep them in shared files every person's AI can read, so nobody has to paste them in each time.

Step 1: Give it the facts

Product capabilities, limits, prices and policies, each with a source. Specific facts produce specific sentences; without them, AI writes "powerful features" and "seamless integration".

Step 2: Give it your customers' words

Collect phrases from sales calls, reviews and interviews. A line like "we roster in a spreadsheet and it mostly works" will beat any copywriter's paraphrase, because it is how buyers actually think.

Step 3: Give it a voice guide

Replace adjectives with rules: typical sentence length, words you use and avoid, punctuation habits, how you open and close. The guide to brand voice for AI covers what to include.

Step 4: Give it examples

Two or three annotated samples of writing you are proud of teach more than pages of instructions.

How should you brief each piece?

Tell AI who the piece is for, what single point it must make, what the reader should know or do afterwards, and any specific facts, quotes or examples to use. A vague request produces a vague draft; a two-line brief with an angle produces something worth editing.

Step 5: Brief with an angle

Compare two requests. "Write a blog post about onboarding" produces the average onboarding post. "Write for operations managers at 50-person firms; argue that onboarding fails in week two, not week one; use the customer quote about the second Monday" produces something only your business could publish.

A strong brief answers four questions: who is reading, what is the one point, what should they do next, and what evidence must appear. That last question matters most, because evidence is what generic writing lacks.

What should you edit out of AI writing?

Edit out stock phrases, empty intensifiers, padded openings, unsupported claims and punctuation your company never uses. Then check that every paragraph says something specific to your business. If a sentence could appear on a competitor's site unchanged, rewrite it or cut it.

Step 6: Edit with a kill list

Keep a short list of phrases to remove on sight, and share it with the team:

• Stock openers: "In today's fast-paced world", "In the ever-evolving landscape".
• Hype words: unlock, leverage, seamless, game-changer, revolutionise, supercharge.
• Empty intensifiers: truly, incredibly, very, absolutely.
• Vague claims: "industry-leading", "best-in-class", without evidence.
• Unusual punctuation: marks your own writing never uses, such as long dashes.

Readers are noticing. Macquarie Dictionary named "AI slop" its 2025 Word of the Year, defining it as low-quality content created by generative AI, often containing errors. Generic copy now risks being read as exactly that. The guide to AI slop covers how to spot it.

How do you keep a whole team sounding consistent?

Put the facts, customer words, voice guide and samples in one shared place that every person's AI reads, rather than in individual chats. Share the kill list. Then review a few pieces each month against the voice guide and update it with whatever slipped through.

Step 7: Share the setup, not the skill

Individual prompting skill varies widely. According to Microsoft and LinkedIn's 2024 Work Trend Index, only 39% of people who use AI at work have had AI training from their employer. A shared setup means everyone starts from the same material, so results depend less on who asked.

People feel the difference. According to Atlassian's 2026 Pulse survey, only 12% of workers say their AI understands their organisation like a tenured senior colleague.

The shared material for steps one to four is what a company brain holds.

Skein builds that shared knowledge layer for growing teams, with voice files for the company and for named people. That suits a team where several people write with AI and the results vary. A solo writer can get most of the benefit from a single well-kept instructions file.

Frequently asked questions

How do I make ChatGPT sound like me?

Give it material rather than adjectives. Provide samples of your best writing, a short list of rules on sentence length, words you use and avoid, and punctuation, plus the facts and customer phrases the piece needs. Brief each piece with a clear angle, then edit out stock phrases.

Why does AI writing sound so generic?

Because AI predicts the most likely wording, and without specific material about your business it produces the average of everything similar it has read. Supplying your facts, customer language, voice rules and examples gives it distinctive choices to make instead of default ones.

What phrases should I remove from AI writing?

Remove stock openers such as "in today's fast-paced world", hype words such as unlock, leverage and seamless, empty intensifiers such as truly and incredibly, vague claims like "industry-leading" without evidence, and any punctuation your company's own writing never uses. Keep the list short and shared across the team.

Can AI match a brand voice?

Yes, reasonably well, if the voice is written down as concrete rules with real samples. Adjectives like "friendly" or "bold" do little. Rules on sentence length, vocabulary, banned phrases and punctuation, plus annotated examples, let AI reproduce a voice consistently, with a human edit for tone.

How do I keep AI writing consistent across a team?

Keep the facts, customer language, voice guide and writing samples in one shared place every person's AI reads, and share a common list of phrases to remove. Review a few pieces each month and update the voice guide with anything that slipped through.

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