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Will AI Replace Technical Writers?

· 4 min read
Dr Colin Hillis, FISTC
Dr Colin Hillis, FISTC
Technical Writing Consultant, Founder of Technically Write Ltd.

Beyond the AI Buzz - The Enduring Value of Technical Writers

Some managers wave AI around like a magic wand that will zap technical writers (and many other roles) out of existence. However, every “AI-generated” technical doc that we have seen to date reads like an overcaffeinated brain dump, full of gaps, noise, and lacking clear direction. Rather than solving problems, our experience is that unless it has existing content to work from (thereby presenting legitimate security concerns), the output is largely unusable. It guarantees that Support teams will be buried under follow‑up tickets. Annalong FC 2

At Technically Write Ltd. , we believe that AI is unlikely to “wipe out” technical writing careers. Instead, it will shift the balance between human expertise and machine assistance.

Undoubtedly, companies always have and always will chase cost-savings, so that the mere suggestion of AI replacing head count sounds like an amazing prospect in principle, but it is not as straightforward as what it might seem. Despite all the push-back from nay-sayers, each year LLM models become better at understanding and generating technical prose, code snippets, tables and even basic diagrams. This cannot be denied. However, there are some blockers that will slow and prevent wholesale replacement:

  • Deep domain expertise & accuracy - Technical docs must be 100% correct, reflect constantly evolving products, standards and APIs, and often require hands-on experimentation. AI models still struggle with subtle specification changes, lack context at times, and can hallucinate details.
  • Complex context & stakeholder management - Writing often involves interviewing engineers, understanding edge-case workflows, negotiating priorities with product teams and legal/compliance groups. Those soft skills and diplomatic savvy are still very human.
  • Toolchain integration & maintenance - Truly end-to-end doc pipelines (from source code to CI/CD-driven publishing, versioning, translations, accessibility checks, diagrams, interactive snippets) require custom engineering. Building that around black-box AI isn’t trivial.
  • Trust & review overhead - Organizations rightly demand review cycles and sign-offs. If AI drafts drift from reality, this creates more work, not less. Teams will push back until reliability is rock-solid.
  • Regulatory & legal constraints - In industries like healthcare, aerospace or finance, every sentence often needs legal review or FDA/CE approval. Nothing that a model spits out can bypass that. Secondly, many industries have legitimate security concerns around making their intellectual property and/or code base available to AI servers. So much so, that certain industries have a blanket ban on use of AI on work infrastructure.

What the Future Holds

AI will transform technical writing workflows, handling first drafts, boilerplate procedures, contextual principles, consistency checks, release note templates, or perhaps even draft diagrams. This will free writers’ time for higher-value work, such as doc strategy, UX, complex problem framing, continuous improvement, but also research of new features and concepts. The bottom line is that AI cannot deep-dive a new feature that is not already documented or recorded elsewhere. Even if it is documented elsewhere, this source content must be made available to the AI platform and suitable prompts crafted to interrogate the content sources. This requires knowledge to write and knowledge to review the subsequent output for accuracy. So, rather than fearing elimination, we encourage technical writers to embrace AI as a force-multiplier, adapt to the future, and focus on the deeply human parts of the craft that machines cannot touch.

As an experiment, we asked several AI to estimate the probability of technical writer roles being outsourced entirely to AI within the next 5–10 years, with minimal human intervention. Here are the results:

  • Junior Technical Writer - Often handle boilerplate, basic style edits and template-driven tasks – very automatable. Probability of replacement = 60 %
  • Mid-level Technical Writer - Still juggle interviews and structure, but a chunk of drafting could be AI-driven. Probability of replacement = 35 %
  • Senior Technical Writer - Bring strategic content architecture, cross-team orchestration and high-stakes quality checks -difficult to replace. Probability of replacement = 20 %
  • Technical Writing Manager - Combine leadership, process design, coaching and stakeholder buy-in - human skills that will remain in demand. Probability of replacement = 10 %

The answers match the rationale that we have for this question. Junior roles will invariably be more at risk, with less risk for senior writers. We predict that this will lead to a more limited intake of junior writers in the short-medium term, which will eventually cause a shortage of new senior writers. Therefore, those who are already senior writers will likely find themselves in higher demand in the future. If you would like to find out more about how we can help your company to prepare for and leverage AI in technical writing, please Contact Us.