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Just imagine: you commission ChatGPT to write a post for Instagram. And instead of a lively and recognizable “brand voice,” you get a dry message like “Dear users, in today’s digital marketing world…”. The text seems to be correct, but it is colorless, devoid of emotion and intonation that keep the audience’s attention.
This is the main risk of working with neural networks in SMM: they are great at generating words, but they don’t understand how to sound like a brand. As a result, your posts turn into a generic corporate template that gets unsubscribed from faster than emails with banal greetings.
How to teach AI to speak your language: to convey your brand’s character, emotional tone, and unique style. We will show you how to create a simple Tone of Voice guide, how to formulate queries to neural networks correctly, and why your content will always sound “alien” without it.
Neural networks can work with language, but not always with intonation. They are excellent at composing grammatically correct texts, but this “correctness” often becomes a problem. AI produces material that looks smooth but lacks character. And while a human copywriter can “read” the style, a machine without the right settings produces a faceless template.
ChatGPT or any other text generator strives to be correct and as versatile as possible. As a result, instead of a lively post, you get an official message in the style of “good afternoon, we are happy to inform you”. On social media, such a tone sounds artificial and repels the audience.
For AI, irony or internal community jokes are “dark matter”. If you don’t give examples, it takes everything literally. A post that is supposed to be witty turns into a flat and overly serious one.
Without clear instructions, AI tends to reproduce bureaucratic language: “in the modern world”, “in a dynamic market”, “effective business solutions”. Such vocabulary sounds the same in the posts of a bank, a cosmetics brand, and a gaming service. The uniqueness of the brand is disappearing.
AI without instructions: “In the modern world, it is important to take care of your finances. Our service will help you control expenses.” The same message with a ToV guide: “Money doesn’t grow on trees, but with our service, it definitely won’t disappear without a trace. Cost control is now in your pocket.”
The difference is obvious: the first text sounds like abstract advice from a textbook, while the second is about how content lives, which can be imagined in a real social media feed.
In order for the neural network to start sounding like your brand, it needs to be given a “character dictionary”. Otherwise, it will never know where the line is between irony and formality, between a friendly joke and excessive levity. For this purpose, it is worth creating a short but clear Tone of Voice-guide.
Are you witty and daring? Or are you serious and reliable? Or emotional and inspirational? Give simple adjectives that fit your style. For example: “ironic, direct, no-nonsense” or “warm, caring, supportive”.
AI learns from patterns. If you show it a few reference texts on your page, it will better reproduce the desired rhythm and vocabulary. It’s not enough to say “be a meme” – it’s better to show a meme that has already been shared by your audience.
It is equally important to explain what should not be. Forbid bureaucracy, clichés, and formulas “in the modern world”. Make it clear that you don’t use “dear users” or an excessive number of emojis.
Create a few fictional posts in your style – short texts from different situations: product announcement, reaction to a trend, joke. This will serve as a guideline for AI to understand what exactly you consider your “voice.”
Such a ToV guide should not be a thick document of a hundred pages. Two or three pages describing the brand’s character, examples, and prohibitions are enough. The main thing is to make it practical: any AI can reproduce your tone of voice after reading it.
The Tone of Voice guide is the basis. However, for AI to start working in the right way, it needs to be properly “launched”. This is where prompt engineering comes into play: the art of formulating queries so that the machine gives texts similar to yours, not general phrases.
AI perceives context. If you ask it to “write a post,” it will do it in the most convenient neutral style for itself. If you say:
“Imagine that you are the SMM manager of the [name] brand. Our tone is: [description]. We talk like this: [examples of posts]. Write a post for [Instagram/Telegram] about [topic] in our style” and you will get a completely different result.
Don’t limit yourself to a general description. Add 2-3 texts that you consider “reference” and ask AI to generate something in the same vein. Examples work as training data for the neural network.
Clearly indicate the length of the text (“up to 500 characters”), the emotional tone (“friendly, ironic”), and the presence or absence of a call to action. Specifics save time on editing.
The same prompt can be asked to be completed three times. This will allow you to choose the best option or combine several.
Don’t ask AI to write a text, choose a meme, and come up with hashtags at once. Break it down into stages: first, the text, then the tone, then the visual idea. This improves the quality of the final result.
Prompt without instructions:
“Write a post about our new mobile app for expense control. Result: “In the modern world, it is important to keep track of finances. Our app will help you…”
Prompt from ToV:
“Imagine you are an SMM manager of a fintech startup. Our style is ironic, simple, and without bureaucracy. We joke about money, but always give a sense of control. An example of a post: “Money doesn’t grow on trees, but with our app, it definitely won’t disappear without a trace.” Write a post for Instagram about the launch of the mobile app, up to 400 characters, with one joke and one call to download.”
The result: a lively, recognizable tone that works for the brand.
Even the best prompt does not guarantee that AI will hit the mark the first time. That’s why it’s important to check the result in the same way you would edit texts from a copywriter. This is not bureaucracy, but a way to maintain brand recognition.
Put your new AI text and some real posts that have performed well in your community side by side. If the difference is too obvious, you should adjust the prompt or add examples to the ToV guide.
The most honest way to understand whether the audience “hears” your voice is to test it. Take two posts on the same topic: one written by AI and the other by a human. Post them on social media and see which one works better in terms of reactions, shares, and clicks.
AI can provide the basis, but the final tone is often shaped by the editor. Sometimes it’s enough to change one sentence or add a brand-specific phrase to make the text come alive.
AI: “Download our financial control app today”. Human: “Your money doesn’t like chaos. The app is already waiting in your smartphone.” The second version immediately feels live, not generated.
AI is a tool that strengthens the team, but without a clear framework, it can easily turn into a source of problems. When working with neural networks, the same mistakes are often made.
AI tends to create smooth, flawless wording. The problem is that they sound like a corporate brochure, not a live social media post. The audience feels that it is not a brand speaking to them, but a faceless “robot”.
When asked to write “emotionally,” AI often exaggerates: it adds an excessive number of exclamations and emoticons that make the text look caricatured. Instead of sincerity, it creates artificial “hyper-joy”.
Without any specific prohibitions, AI likes to use words like “effective solutions”, “modern trends”, “best in class” in the text. And if you work in Ukrainian, it can translate English expressions verbatim, which makes the content look alien and unnatural.
AI can provide correct information, but not “your voice”. The result is a text that could belong to any company on the market. This is the biggest risk: the loss of uniqueness, for which Tone of Voice was built.
AI without settings: “Our service provides effective cost management. Download now!” The right tone of voice: “Money loves order. Our app will help to bring it to order without any extra effort.”
Today, neural networks are already writing texts faster than any copywriter, generating ideas for content, and even helping to plan headings. But despite this, the main question remains: can AI completely replace humans in SMM?
AI works seven days a week, doesn’t need inspiration, and can generate dozens of variants on one topic in minutes. It saves time and budget. For routine tasks, such as text adaptation, idea generation, and keyword selection, it is indispensable.
A neural network does not have its own experience, does not feel cultural nuances, and does not know the context of the community as well as a live SMM specialist. It can “imitate” irony or jokes, but it is not able to catch subtle changes in the mood of the community. Where you need sensitivity and creativity, you can’t do without a human.
AI does not replace copywriters, it changes their role. Now the task of an SMM specialist is not only to write but also to manage the process: create Tone of Voice, build promos, select the best results, and add final accents. In other words, a neural network is a powerful tool, but it is a human who determines how it will sound.
AI in SMM is not a magic wand or an enemy that takes away work. It’s a tool that works as well as you set it up. If you leave the neural network to its own devices, you will get standard “dear users” and faceless corporate texts. But if you give it a Tone of Voice guide, examples, and specific samples, it will speak in the voice of your brand.
The bottom line is simple: AI writes, but you speak for the brand. And it’s up to you to make sure that voice sounds authentic, recognizable, and compelling.
So try it today: take one of your posts, run it through a neural network with clear ToV instructions, and compare it to the original. You may be surprised how quickly the machine learns to “catch” your vibe.