Is it the end of copywriters? Do we need authors in the age of AI

Neural networks are already writing articles, posts, and SEO texts. So what’s left for a person and what should a business pay for?

Working with texts is one of the first areas where artificial intelligence (AI) has entered. At first, he took on cheap SEO texts and template descriptions. Then it learned how to suggest topics, make the structure of a large article, choose the format, and now he knows how to imitate the tone of voice, if you correctly write it in the prompt.

Yes, the content marketing market has really changed. But the question is not whether the neural network will replace the copywriter, but which author will remain in demand. And the answer is pretty simple: someone who knows how to think, ask precise questions, edit and feel the task of the business. 

Irina Burenina, Lead Project Manager at 2L:

«I know companies where marketers have abandoned artisan authors. And this is true if the task, for example, is to make 20 product cards based on ready-made characteristics. Artificial intelligence undoubtedly speeds up operational work and reduces the cost of processes. The shallow descriptive copywriter is dead.

But at the same time, there came a demand for heavy artillery – technical authors and editors who manage the meanings. In 2026, a copywriter is a communications architect who knows how to extract experience from the heads of top managers and techies and repackage it so that it is understandable to the market.»

Who stayed in the market

There is a growing demand for specialists who can work with AI. It’s not about «I wrote a prompt and went out for coffee.» It’s about the ability to put expertise, context, style, and live examples into a task, and then bring the result to publication quality. The AI can provide a draft. Then the person makes a text that you are not ashamed to show to the market.

That is why today, not just the ability to write is valued, but the ability to manage meaning. It is important for the author to understand:

• what business task does the material solve;
• who was it written for;
• where should the text sell, and where should it explain;
• what tone should I use to avoid losing the trust;
• what can and cannot be automated in the material.

Three levels of content

At the 2L communications agency, we identify three levels of content:

1. Operational content (product cards, announcements, draft). Here, AI closes 90% of the work. A person is needed only as a fact corrector. This is a dead market for newbie copywriters.
2. Image content (blogs, case studies). AI provides a good structure and skeleton. But we have never used the neural network text in its original form, even in simple tasks. Because AI writes smoothly, but it doesn’t respond to the reader, it doesn’t catch on, so our authors fill the texts with vivid insights or stories, depending on the context.
3. Technical and expert content (software, automation, complex B2B). This is a gold mine of the profession, where AI is used to the smallest extent. Technical authors are in hot demand right now. They don’t write about how the button works, but about what problem the hardware solves. For example, the author holds an in-depth briefing with an engineer or technical director. He doesn’t ask what your software is doing. He asks why you chose this architecture, what was broken before, and how the client’s life changed after the implementation. A lively and technically well-versed author will understand where the key insight is hidden and get to the bottom of the truth.

In this sense, AI does not kill the profession, but pushes random people out of it. 

What can be delegated to AI

When a text request is not too complicated, it can really be closed using AI. But when it comes to reputation, positioning, media work, and accurate presentation of expertise, you can’t do it without a person. Not only words are important here, but also the accuracy of wording, fact checking, knowledge of editorial requirements and understanding how the material will live after publication.

Top 5 Text tasks for AI:

• generating ideas and topics;
• the initial draft of an article or post;
• structuring a large amount of information;
• reworking the brief into a clear text;
• adapting the material to different formats.

Top 5 NON-AI Text Tasks:

• developing a content strategy;
• choosing a key message, filling it with meanings and personal experience;
• packaging of expertise, expert interview, choice of metaphors;
• fine-tune the Tone of Voice for a specific audience;
• writing technically complex materials with analysis for a C-level audience.

Therefore, artisan performers are no longer needed by the market, but strategic authors remain. In conjunction with AI, their productivity increases significantly, but the quality does not decrease, because human expertise is behind the machine speed.