Artificial intelligence (AI) gives anyone the power to publish content faster and easier than ever before, but whose words are they? Are they generic AI slop that smacks of sameness or are they the beginning of content that supports your brand voice and influences your customers? If they are like the first type, then it’s likely those words are failing to excite your customers (at best) or causing them to look at alternative and competitive brands (at worst). That’s why only human AI writers can protect your brand’s authentic voice in the age of AI. They take on the challenge of making sure that your AI-generated content sounds like you, not like everyone else.
The risk of losing your brand voice to AI is real. The Large Language Models (LLMs) that are the foundation of today’s generative AI are exposed to huge datasets that contain all kinds of text, articles, websites, and more. During this training phase, they learn to understand the context and flow of language. In the end, the text generated by AI is based on complex algorithms of word probability. So AI tools are essentially sophisticated next-word prediction machines. That’s what we get as output when we prompt an AI tool.
Why AI Needs a Human Editor
Knowing how AI creates text goes a long way toward understanding its limitations. Because it predicts the most likely next word based on patterns in its training data, its writing drifts toward the average: competent, but missing the rhythm, attitude, and individuality that define human writing. Its default tone is meant to be neutral and safe, yet it still produces confident factual errors, as too many instances have shown.
If you simply accept AI’s first draft, you end up with generic copy that dilutes your brand voice and gives potential customers little reason to choose you. Bland messaging loses readers’ attention as your voice disappears into the noise, while factual errors or the wrong tone can damage your reputation. Over time, these missteps erode trust, loyalty, and revenue.
How much that matters depends on the organization. If customers choose you on price or convenience or your content is mostly functional, generic AI output may serve you fine. But in regulated industries, in companies where content earns trust, and where content teams and agencies write on behalf of a brand, voice is a competitive asset worth protecting. For CMOs, chief communications officers, content directors, and agency owners in those settings, the question isn’t whether to teach AI the brand’s voice, but how well. There are three ways to do it, and they produce very different results.
Teaching AI Your Brand Voice: Three Levels
Level 1: Simple Training With a Single Prompt
Use only one example: The simplest approach to training is to provide the AI model with a single ideal piece of content that encapsulates the brand’s desired tone and voice. This could be a blog post, marketing copy, or any other written material that represents the brand in its best light. It’s fast, and it works for a quick test. But from one piece, the model can’t tell which features are voice and which are incidental so it copies the surface: the topic, the structure, and even specific phrases. If you ask for a different format, it falls back to generic AI prose. It also has no sense of what your brand would never say.
The process is simple:
- Access a generative AI tool like ChatGPT, Claude, or your chosen AI tool
- Input the following prompt: “Please analyze the tone and voice of the text below and provide a detailed description”
- Paste the sample content into the input field
- Click the Send Arrow or Return Symbol
Level 2: Curated Examples Plus Explicit Rules
Use three to five curated examples plus explicit rules and a do-not list: Choose three to five strong pieces that vary in format and topic so the model can find what they have in common, which is the voice. Pair them with written rules that turn vague adjectives into instructions. “Confident” becomes “lead with the claim, limit qualifiers, never open with ‘we believe.’” Add a short list of words and phrases the brand avoids. Also add one before-and-after rewrite showing off-voice and on-voice versions of the same content. This is the minimum working voice system for an organization, and it’s where most of the improvement comes from.
Level 3: A Managed Voice System
Use a curated library, organized by format, plus rules, guardrails, and a review process: Build a curated library of examples organized by format. Include only two or three relevant pieces for any given task, such as LinkedIn examples for a LinkedIn post or press materials for a press release. The library may grow to 10 or more pieces, but more examples help only when they’re better examples. Keep the same core rules and guardrails across every format, including compliance boundaries in regulated industries. Then add what keeps the system working over time: A clear owner, human review for high-stakes content, and regular audits to catch drift.
Notice what changes from one level to the next. It isn’t the tool, and it isn’t the number of examples. It’s the amount of human judgment built into the system: Which examples to choose, what rules they reveal, and what the brand must never say. AI can follow a well-defined voice. Defining it and noticing when the output drifts still takes an experienced human editor.
No matter which level you choose, the system is only as good as the person running it. The strongest results come from experienced humans in charge of the process: People who have worked as both writers and editors; understand marketing, public relations, or advertising; and know an industry well enough to spot what AI gets wrong. Few organizations have all of that in one person, whether internal or external, but the closer you can get, the better your AI-assisted content will be.
The Role of the Human AI Writer
Teaching AI to write in your brand voice is only part of the job. Even the best-configured system produces drafts, not finished work, and it has no idea what that work is supposed to achieve. When those drafts pass through an experienced human writer and editor who understands the strategy behind them, the result is content that is sharper, more persuasive, and unmistakably yours.
That’s where I come in. I work as what I call a human AI writer and editor: Someone who brings strategic and editorial judgment to AI-assisted content.
In senior roles at Edelman and Ruder Finn and as the first head of Edelman Editorial, I have spent my career crafting messages that are designed to shape opinions and drive decisions. What I’ve learned is that good writing depends on simplicity, clarity, and emotional intelligence, and that the best writing starts with knowing exactly what it needs to accomplish.
My work with clients covers the full system described above. I help decide where AI belongs in your content process and where it doesn’t. Routine content can start with an AI draft. Executive communications, crisis messaging, and anything regulators will read should start with a human. I help define your voice: Choosing the examples that truly represent it, turning vague adjectives into usable rules, and spelling out what the brand never says, including compliance boundaries in regulated industries. Then I review and refine what AI produces so every piece sounds like you.
A good editor improves a writer’s work without erasing the writer’s style. The same discipline applies to AI drafts. The human AI editor makes sure the brand’s voice comes through in the finished text, and that job can’t be handed off to AI detectors or “humanizer” tools.
How I Work With AI Drafts
My process starts before I edit a word. I ask what the piece needs to accomplish: Who it’s for, what they should think or do after reading, and what makes your perspective different from your competitors. Those answers shape every decision that follows. AI can’t answer those questions. It doesn’t know your business goals, your market, or what your audience already believes.
Next comes accuracy. I check every claim to confirm it’s true and can be substantiated. If it can’t, I cut it or replace it with one that can.
Then I add what AI can’t: Perspective, a point of view, and the sense that a real person is speaking. Humanizing AI content means shaping the rhythm and personality that define your brand. Without that, AI content sounds neutral at best and tone-deaf at worst, and either way it’s forgettable. AI can describe joy, frustration, or nostalgia, but it can’t feel them, and readers can tell the difference.
Finally, I protect consistency over time. When AI-assisted content drifts in tone and no one catches it, readers notice even if they can’t say what feels off, and that feeling erodes credibility. Regular review keeps the voice steady across every piece, writer, and channel.
Have something valuable to say but need help shaping it for your audience?
Let’s talk about what you’re working on and what you need to accomplish.