How AI is Reshaping Technical Writing: Structure

Optimizing your technical documentation is core to a positive product experience. Historically, technical documentation teams provided users with bound books and manuals, but the shift to digital documentation has transformed how information is delivered. Printed materials have given way to more modular, topic-focused resources such as articles, knowledge bases, interactive documentation, and even AI-generated replies to questions so that users don’t even have to read the source material. While this evolution has made information more accessible, it has also introduced new challenges in structuring and maintaining consistent content that is adaptable to evolving technologies like AI applications.

To guide teams through these challenges, I prepared a series of three articles where each one dives into a key component for modern documentation. In this first article, we dig into how structure brings value to digital technical documentation in an AI world.

How Documentation Publishing is Shifting

As digital content delivery becomes the norm, businesses are moving away from static, document-based publishing. At the same time, emerging technologies are redesigning user interfaces and redefining how people interact with information due to expectations of modern accessibility, content freshness, and information findability.

Companies that haven’t yet transitioned will need to do so in the coming years, especially with customer demand and regulations like the Machinery Directive 2023/1230/EU driving the changeover.

It’s time to look beyond traditional document-based content and to understand how new technologies are impacting information delivery:

• AI-powered assistants: Platforms and devices like ChatGPT, Google Assistant, and Amazon Alexa generate instant, contextual responses.
• Voice-first and multimodal interfaces: These applications integrate text, speech, and visual elements for more seamless interactions.
• Augmented Reality (AR) and Virtual Reality (VR): These technologies overlay or immerse users in contextualized knowledge.
• Wearable devices: Smart glasses and other wearables provide real-time, hands-free guidance for safer, more effective workflows.

To keep pace with these advancements, companies are adopting dynamic content delivery, ensuring that information remains personalized, accurate, and accessible across these different endpoints.

The Challenge of Modern Digital Publishing

Information professionals must consider how these technologies ingest and deliver content. After all, no one asks an AI chatbot a simple question and wants the text of a 3-page PDF typed out in response.

Our answer to this challenge is to implement known, approved practices that create a high-quality Content Value Path:

1. Structure
2. Metadata
3. Semantics

Let’s get started with structure — what it is, why you need it, and how to do it well.

What is Structured Content?

Structured content refers to content that is broken down into individual component parts, also called topics, that may be a few lines or a few paragraphs. Documentation writers create structured documents by assembling the components together with a map, like a table of contents. Also, by classifying these topics using metadata, structured content allows teams to reuse and personalize components for specific users and platforms easily.

How to Implement Structured Content

Documentation teams prepare structured content using well-known writing standards like DITA and S1000D. These standards allow writers to optimize content production and avoid long, monolithic Word documents. Specifically, structured authoring tools provide multiple benefits for technical documentation teams:

• Enhancing content production and maintenance for large volumes of documentation through in-parallel authoring and real-time collaboration,
• Reducing duplicate content thanks to content reuse functionalities,
• Facilitating text modifications by updating that topic across all instances where it is present,
• Streamlining the translation workflow and cutting costs by automating processes and reusing approved translation segments.

In structured writing, how authors break down content into topics is incredibly important. It is a key enabler of content reuse. But when considering the use by AI, each topic should also align with the broader subject to ensure clarity, consistency, and completeness.

This step allows search algorithms and new technologies that ingest content to work with consistently complete fragments of information so that these technologies can determine which fragments are needed to provide effective and unambiguous responses to user questions and search queries. Hence, it may be necessary to adapt the granularity of the topics:

• For excessively long topics that cover multiple subjects simultaneously, authors must break them down into more granular topics.
• For excessively short topics consisting of a single phrase or fragment, authors should assemble them with intermediate maps. Even if these maps aren’t intended for publication, this step helps authors define a more consistent level of information.

Continuing Down the Content Value Path

Structured content is the first tenet of crafting a Content Value Path — critical to publishing documentation to modern technologies and devices. However, structured content isn’t the only required element.

Documentation teams also need to add metadata and semantically enable the text to provide a truly optimized digital content experience to their users. These elements enhance content findability, personalization, and more, all of which are prerequisites to any AI project.

Read part two of this series, “How AI is Reshaping Technical Writing: Metadata” to explore the second vital piece to this three-part equation. Then wrap up the Content Value Path with part three, “How AI is Reshaping Technical Writing: Semantic Enablement”. There, we dive into how to add text tags that help algorithms clearly identify and extract information from content.