Writing is Thinking: Why Knowledge Workers Must Maintain Their Writing Skills

Since generative AI can produce polished text in seconds, it’s tempting to ask: Why write at all? If the end result, like a report, an email, a memo, or a presentation, looks the same whether written by a human or GenAI, why not just let the technology do the work? Because writing isn’t just about producing text. Writing is thinking.

If you’re a knowledge worker, your mind is your most valuable tool. Your job is to analyze, synthesize, and communicate information in ways that create value. When you write, you question assumptions, challenge ideas, and discover insights through the act of writing itself. Writing is a strenuous cognitive process that directly contributes to forming ideas. In fact, trying to make a difficult idea work in writing may cause you pivot to an important new insight, which would only arise through the act of writing. The effort that you put into writing about an idea is a large part of what makes your work valuable to (and usable by) others.

If you let GenAI do the hardest writing for you, you may get instant text, but you won’t get the intellectual work behind the writing. Christopher Newfield, in “The Fight About AI,” warns that if AI-generated text becomes so common that it replaces effortful human writing—and we accept that replacement—then professionals learn that they need not think to get their work done. But what value is a knowledge worker who does not think?

Writing as a Process of Thought and Discovery

The notion that writing is thinking is not just an idea that I’ve cooked up to sell editing software, it is borne out by cognitive science, literacy research, composition theory, and learning theory. Writing truly does help you figure out what you think.

In their work that changed how we think about and teach writing composition, “Cognitive Process Theory of Writing,” Linda Flower and John R. Hayes presented a new model of the writing process based on cognitive psychology. They introduced the recursive writing process that frames writing as an active process of meaning-making and emphasized that writing is not merely the transcription of pre-formed thoughts. Their model shows that writing involves continuous cognitive engagement, where ideas are generated, evaluated, and revised cyclically and in real time.

In “The Writing Effect,” education journalist and co-author of The Writing Revolution 2.0, Natalie Wexler, explains how writing strengthens information retrieval (bringing information back from memory) and elaboration (connecting new knowledge to existing knowledge), which reinforces understanding, exposes gaps in reasoning, and helps improve ideas.

In More Than Words, John Warner writes: “Writing involves both the expression of an idea and the exploration of an idea—that is, when writing, you set out with an intention to say something, but as part of the attempt to capture an idea, the idea itself is altered through the thinking that happens as you consider your subject.”

Writing is not just a way to record ideas; it’s how you develop them. It’s also slow, hard work.

Writing demands engagement with complexity and encourages deeper reflection. It forces whatever you think you know through an intellectual filter as many times as necessary until it becomes digestible for others in a written form.

But GenAI does not engage in this intellectual process: It predicts the next likely word based on statistical probabilities, matching patterns and structures, but not wrestling with meaning. While AI can produce grammatically correct and syntactically fluent text, it does not engage in the intellectual labor that defines important writing, which means that something will always be missing, no matter how fluent the output may sound.

The Danger of Outsourcing Too Much Thinking

I admit that GenAI is an impressive and powerful tool. Used well, it can accelerate work. But if used constantly and thoughtlessly, it can erode the skills that make knowledge workers valuable.

If work is divided into hard and easy tasks, as MIT economist Daron Acemoglu does in “The Simple Macroeconomics of AI,” then the future of knowledge worker value comes from doing the tasks that are hard. Acemoglu argues that AI excels at easy tasks—those with clear, measurable outcomes, like summarizing data or drafting standard reports, and that will bring productivity gains. But hard tasks—those requiring analysis, synthesis, strategic decision-making, and judgment—are not easily automated and will remain the domain of humans. According to Acemoglu, the “productivity gains in hard tasks will be approximately one-quarter of the easy ones.”

Writing falls into the hard task category because it forces you to decide what matters, structure thoughts logically, identify gaps in reasoning, and refine messy ideas into clear ones.

This is why the highest-paid professionals will not be the ones who press the “generate text” button. They will be the ones who think critically, dig into unstated assumptions, and make the complexity of a difficult concept seem simple. People who rely too heavily on AI will become replaceable by it; people who retain the ability to write, and, by extension, to think, will remain essential employees.

Concern for the future of writing and critical thinking that goes with it are widespread outside of the technology world. Jane Rosenzweig, director of the Harvard College Writing Center, warns: “Writing—in the classroom, in your journal, in a memo at work—is a way of bringing order to our thinking or of breaking apart that order as we challenge our ideas. If a machine is doing the writing, then we are not doing the thinking.”

Newfield warns that AI is “making human learning worse” by enabling professionals to sidestep cognitive effort. Warner worries that the illusion of effortless writing, and the desire for it, will encourage humans to stop thinking critically because they don’t think they need to engage the mental effort of writing anymore. The common theme is not a fear that GenAI will take over, but that people will give up.

The Deliberate Effort Is the Point

Bringing GenAI into our workplace and our writing processes is not an all-or-nothing choice. There are times when it’s helpful and well-suited to the task. And there are times when it’s not. Is it faster? is not the determining factor.

Writing takes time. But since our culture prioritizes speed, this can feel inefficient and pointless. Why spend an hour explaining your research in a memo when a GenAI tool can generate something in seconds?

In “15 Times to use AI, and 5 Not to,” Wharton Professor Ethan Mollick outlines several cases where GenAI should not be used, including those where the effort is the point. He argues that true learning happens through struggle, not shortcuts. Asking GenAI for a summary is not the same as reading and engaging directly with a text, grappling with its ideas, and forming independent conclusions. Similarly, when faced with complex problems, the process of working through them—testing theories and revisiting assumptions—is key for creating the mental frameworks that help develop subject matter expertise. GenAI may offer an easy answer, but it cannot replicate intellectual labor and its benefits.

If you’re a knowledge worker, the effort is not an obstacle—it is the point. If you let your writing and critical thinking skills fade, your value disappears.

Don’t Let Fixation with Form Distract You from Substance

In Why They Can’t Write: Killing the Five-Paragraph Essay and Other Necessities, John Warner criticizes the way students (and professionals) are trained to write, calling it a formulaic, “paint-by-numbers” approach that prioritizes surface correctness over deep thinking. In More Than Words, Warner argues that our generations-long fixation with easily identifiable, easily explained, easily replicated writing characteristics led us to conflate these surface-level features with meaning and intelligence. In short, we have trained ourselves to prioritize “correct” over meaningful. And this fixation with surface-level criteria, primed us to value “the things ChatGPT outputs with ease: grammatically and syntactically correct prose.” With that history, it’s no surprise that what GenAI offers is a seductive solution to the difficult problem of thinking.

It’s not that Warner believes grammar and syntax don’t matter—and I would certainly not make such an argument—it’s that the ease of quantifying these features encouraged us to neglect others, which reduced engagement and made writing feel like a slog. GenAI gave disenchanted writers an easy way to produce text that met the form we’ve been telling them mattered most. Some of those disenchanted writers are knowledge workers.

The dream of instant, effortless, formula-conforming writing is here at last. For the disenchanted, this is a magical wish come true. For the future of knowledge, it’s a warning. Writing is not just about form: it’s about engagement with ideas.

Thoughtful Writing is Your Competitive Advantage

In one last appeal to convince you not to cede all workplace writing to GenAI, remember that writing well signals expertise and authority and is necessary for professional advancement amongst knowledge workers. Even if your boss can’t explain what good writing is, she knows that she prefers it and is reluctant to promote someone who can’t do it.

Clear, well-structured writing shows your judgment, problem-solving ability, and interest in sharing your ideas with others. Neither your colleagues nor your clients want to waste their time reading anything less valuable from anyone less prepared.

The knowledge workers who build and retain their writing skills will become more valuable, not less, as AI-generated text floods the workplace. When you write, take the time to show that you can:

Focus on what matters and leave out what doesn’t.
Distinguish between real insight and generic output.
Structure an argument and communicate complex ideas.
Refine your writing so that every sentence serves a purpose.
Ask the right questions, challenge assumptions, and drive original thinking.

Conclusion

Writing well is hard because thinking well is hard. Don’t lose tolerance for the struggle. The slowness and difficulty of writing are features, not flaws. The discomfort is a sign that you are doing valuable work of thinking, not just assembling words, but making meaning.

Re-center knowledge in your knowledge work. The future belongs to people who can think deeply and communicate clearly.

When you’re ready to invest in clear communication, try WordRake editing software. It engages your attention and empowers your decision-making so you can deliver your message clearly. Try it free for 7 days.

About Ivy B. Grey

Ivy B. Grey is the Chief Strategy & Growth Officer for WordRake. Before joining the team, she practiced bankruptcy law for ten years. In 2020, Ivy was recognized as an Influential Woman in Legal Tech by ILTA. She has also been recognized as a Fastcase 50 Honoree and included in the Women of Legal Tech list by the ABA Legal Technology Resource Center. Follow Ivy on Twitter @IvyBGrey or connect with her on LinkedIn.