5 steps to create AI-ready documentation

The way people consume documentation is changing. With users increasingly relying on AI tools over traditional search engines, documentation teams face a new challenge: ensuring that their content can be effectively processed by AI while remaining the authoritative source of product information. If AI systems can’t easily access and interpret your documentation, they may generate answers from other sources, which can be outdated, incomplete, or inaccurate.

Rather than working through a list of search results, many users now turn to AI assistants for direct answers. On ChatGPT, for example, only 0.69% of queries result in a clickthrough to an external website, suggesting that users tend to consume information within the chat rather than consult the original source.

To help address this challenge, we’ve put together practical steps you can take to improve how your documentation performs in an AI-driven landscape.

Step 1 – Metadata

Page titles and meta descriptions are key signals that AI systems use to understand your content’s purpose and scope:

• Page titles should state clearly what the content provides, using natural language that reflects user intent. For example: “How to create tables in Adobe FrameMaker”.
• Ensure that your descriptions provide context for both AI systems and readers. Rather than focusing on keywords, try to communicate the value or result of the content. For example: “Learn how to insert, structure, and format tables in Adobe FrameMaker, including row and column management, styles, and best practices for technical documents”.
• HTML tags and attributes such as alt, title, or figcaption are essential for images since their visual content is typically not a priority for AI to analyse.

Step 2 – Tables and lists

Tables and lists organise information into predictable structures that make relationships between information easier for AI systems to identify. In a way, they are sparing the model one extra processing step. If a paragraph describes multiple items with attributes, the model may internally represent those as grouped elements with associated properties. This is exactly what tables and lists aim to accomplish. Just remember to stick with good documentation practices and don’t go over the top with tables. Use them for actual tabular data such as comparisons, specifications, and reference information.

Step 3 – Questions and answers

Structuring content into the question-answer format can mimic how people search for information on AI tools. AI assistants can often reuse such structures verbatim in their generated responses. It can be a quick win to include some FAQ’s that answer questions you believe your customers would be searching for.

For example, on a help page about Adobe FrameMaker, you could write:

• Q: What outputs can FrameMaker publish?
• A: FrameMaker can publish technical content to a wide range of formats, including PDF, Responsive HTML5, and EPUB.

Step 4 – Punctuation

Use clear, consistent punctuation to improve how your documentation appears in AI tool results. Avoid decorative punctuation like ellipses, excessive em-dashes, or multiple exclamation marks, as stylised language can confuse AI. When in doubt, favour clarity over emphasis.

For example, use quotation marks for actual quotations, and not to express irony. Use hyphens inside words and dashes for interruptions or clarifications, and don’t mix them up. If you decide to use curly quotation marks, don’t use them interchangeably with the straight ones. Consistency is the key.

Step 5 – Style

Style plays a key role in how easily your output is interpreted and reused by AI. Follow these principles when writing and maintaining your content:

• Use a style guide to ensure consistency in your writing decisions.
• Be intentional – use phrasing that directly answers the questions users may ask.
• Avoid ambiguity.
• Write short sentences.
• Add context.
• Use synonyms and related terms. This reinforces meaning and helps AI connect concepts.

Bonus step – Visuals

Visuals are not a priority in AI processing by default – plain text comes first. Written content is less expensive to process and easier to retrieve. If you have to use visuals, make sure you add enough context around them: HTML alt attributes, figure titles, and descriptive text that reflects the ideas expressed in the image.

Where possible, avoid using visuals that contain important semantic information, such as diagrams and infographics, unless the same information is also conveyed in plain text. Otherwise, you risk important details being lost between AI ingestion and retrieval.

The final step – Don’t panic

We know that getting your technical documentation AI-ready can be daunting. The rapid growth of AI tools makes it increasingly difficult to understand how your content is ranked, cited, and surfaced in AI-generated answers. If you want your end users to see your most accurate and up-to-date information, it’s essential that you adapt quickly to the new landscape.

At 3di, we’ve invested heavily in our own AI capabilities, from putting together a team of content tool developers to creating our own bespoke AI-powered solutions. We’ve built the expertise and tools to help our customers make the most of AI while avoiding many of the common pitfalls. If you would like to discuss how we can make your documentation AI-ready, contact us to find out more.