Why AI is creating a growing demand for Technical Writers

One of the ironies of AI is that despite its vast capabilities, there’s a shortage of easily understandable documentation explaining its functionality. While providers like ChatGPT, Google Gemini, and Claude do offer quality technical material, particularly regarding their APIs, there is a noticeable lack of clear explanatory documentation from startups, new ventures, and even established development firms.

To me, this suggests there’s a gap in the market for skilled tech writers with knowledge of machine learning, neural networks, and APIs. If you’re interested in learning how to break into this area, follow this set of tutorials on the intersection of AI and technical writing.

Context: AI and Technical Writing

As artificial intelligence (AI) continues to disrupt industries, a new opportunity is emerging for skilled communicators. Technical writers are becoming increasingly vital in the documentation, development and deployment of AI systems. This article explores why the rise of AI is creating a surge in demand for technical writing expertise.

The AI Documentation Challenge

AI systems are complex, often operating as ‘black boxes’ that can be difficult to understand and explain.

This complexity creates three critical areas where technical writers are needed:

1. AI System Documentation

Technical writers are essential in creating documentation that explains the inner workings of AI systems.

This includes detailing:

  • Machine learning algorithms
  • Data processing methods
  • System architecture
  • Model training processes

For example, a technical writer with ML skills can explain how a computer vision model identifies objects in images, breaking down the process into understandable steps for both developers and non-technical stakeholders. I suspect the demand for this type of documentation is going to rise.

However, to land a role writing this type of material, you do need to understand how machine learning works. To get started, I’d highly recommend the following course on YouTube. Watch Daniel Bourke

2. User Guides and API Reference Documentation

As AI-powered products become ubiquitous, well-written documentation will be required to support them. As a technical writer, you can help to create:

  • Getting started instructions, especially for non-technical users
  • API reference documentation. Learn more about Open API specifications to get stared
  • Feature explanations and cookbooks
  • Troubleshooting and FAQ guides

Consider a chatbot for customer service: a technical writer would create guides explaining how to interact with the bot, its capabilities, and how to escalate to human support when needed.

This is a simple example, of course. You can also look at how specific industries, for example, Healthcare, Government or Finance are planning to use AI, the develop technical and writing skillsets that will allow you to help them explain their products to customers.

Remember, AI is only about ChatGPT, funny videos, and strange imagery. There’s a lot of new use cases coming online.

3. Ethical Guidelines and Policy Documents

Compliance, data protection, and privacy are going to be a major concern as AI products weave their way into everyday activities. Think of how an AI on your smartwatch captures, stores, and shares your data. What guardrails need to be in place to ensure this data is managed responsibly and ethically.

With growing concerns about AI ethics, technical writers play a key role in developing:

  • Ethical use guidelines
  • Bias mitigation strategies
  • Data privacy policies
  • Regulatory compliance documents

For instance, a writer might craft a policy document for an AI-driven hiring tool, outlining how the system ensures fair candidate evaluation and complies with anti-discrimination laws.

Writing About AI: Best Practices

So, how to get started? Here are five points to consider.

To effectively communicate about AI:

  1. Research thoroughly and consult with AI experts. Sign up to Andrew Ng’s courses. Many are free.
  2. Break down complex concepts into simple, relatable terms. Understand the terminology. Do you know what a vector database is? If not… ask ChatGPT. The main thing is that you immerse yourself in this area, learn everything you can, then promote these skills to others on platforms such as LinkedIn.
  3. Use analogies to explain abstract ideas (e.g., comparing neural networks to the human brain). You can think of others, right?
  4. Provide concrete examples of AI applications in everyday life.
  5. Address common concerns and misconceptions about AI.

The Future of Technical Writing in AI

AI is a juggernaut. It’s going to change many industries in ways we can’t anticipate.

As it continues to develop, the demand for skilled technical writers will only grow. Skilled writers, with genuine interests in AI and machine learning, will be crucial in:

  • Ensuring transparency in AI design, development and deployment
  • Facilitating the proper use of AI systems. Think of the ethical side of things.
  • Bridging the knowledge gap between AI experts and end-users. Right now, most documentation is written by developers for developers. That’s fine but we now need material written for non-technical users. Can you help with this?

Next Steps

If you’re considering a career in technical writing, specializing in AI documentation offers promising career opportunities. I’d recommend that you create 30-day plans to go deep into the technologies to give yourself and edge over other writers and carve out a lucrative career in this area.

Here are three resources to help you get started: