AI is changing how teams create and deliver documentation. In this section, we look at how teams are using AI today, what they expect in the future, and how AI is changing the way people interact with docs.
are currently using generative AI as part of their docs workflows
THINk ai will let us build docs that intelligently adapt to user needs
AI’s impact docs workflows and consumption
AI adoption is growing fast — but not everywhere
60% of companies said they’re already using generative AI in their documentation workflows, at least sometimes. About 31% use it often. But 25% said they don’t use AI at all.
Do you use generative AI in your documentation workflow?
AI isn’t just for big enterprises or tiny startups — usage is pretty even across company sizes. Interestingly, the percentage of mid-sized teams using AI is a little higher than small or large teams.
Size of companies that use generative AI in documentation workflows at least occasionally
How teams are using AI in their docs processes
When we asked how teams are using AI, most said it’s for writing and editing content. But 30% still aren’t using any AI tools in their docs process.
AI tools integrated into documentation processes
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So while AI is making a difference for many teams, it’s clear that human oversight is still essential to keep docs accurate, clear, and useful.
Teams expect AI to completely change how docs are made and used
Nearly half of the people we surveyed think AI will have a huge impact on documentation. 87% said it will be at least somewhat impactful.
How big do you think the impact of AI will be on the future of user-facing documentation?
When asked how they expect documentation to change, 42% said docs will start adapting automatically to what users need. Another 25% believe docs will be written mainly for AI and large language models (LLMs) to read and process.
How do you think AI will change the way we approach and format documentation in the future?
How docs show up when and where users need them
We’re already seeing this shift — with docs becoming smarter and showing up exactly when users need help. Tooltips, embedded guides, onboarding flows, and live chat are common now, and they’re just the start.
How do you currently provide documentation at point of need within your product?
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Looking ahead, teams expect more AI-powered assistants, chat interfaces, personalized help, and interactive guides. But no matter how advanced AI gets, it works best when paired with human oversight.
What new contextual formats do you think will play a larger role in documentation in the future?
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The companies seeing the best results with AI are the ones that set clear rules — knowing when to use AI, and when humans need to step in for quality and strategy.
Strategic implications
AI is transforming docs — but writers’ roles are expanding, not disappearing
AI isn’t replacing documentation teams — it’s changing what they focus on. AI can speed up documentation work, but it still needs human guidance to get things right. The best teams use AI to handle repetitive tasks, while writers focus on strategy, quality, and complex content.
Instead of spending time on repetitive writing tasks, writers are now:
– Reviewing and editing AI-generated content
– Organizing and structuring information
– Making sure docs stay accurate and useful
– Thinking strategically about how users find and use content
As Larry Ullman, Stripe’s first Technical Writer, explains:
The companies seeing real success with AI are the ones that:
– Set clear rules for when to use AI
– Keep writers in charge of final reviews
– Use AI to assist, not to replace
AI is a powerful tool, but without human input, it can’t deliver the clarity, accuracy, and user focus that great documentation needs.
Docs must shift from static pages to dynamic conversations
AI is pushing documentation beyond static pages. More companies are starting to think of docs as conversations — where users ask questions and get answers, instead of digging through long manuals.
This shift is already happening with AI-powered chatbots, smart search, and tools that guide users based on what they’re trying to do.
But for this to work well, teams need a strong base of clear, structured content. AI can only deliver good answers if it has high-quality docs to pull from.
The future of docs isn’t just about writing pages — it’s about creating systems where users can interact, explore, and get exactly the help they need, when they need it.
Clear, well-structured docs are the foundation for successful AI
AI is only as good as the content it works with. If your documentation is messy, outdated, or unclear, AI will just spread that confusion faster.
That’s why teams need to focus on getting the basics right — clear writing, good structure, and up-to-date content — before leaning too hard on AI tools.
AI can help scale your docs and deliver answers quickly, but it relies on strong human-created content to do that well. Skipping this step leads to bad user experiences — faster.
The takeaway? Fix your content first, then add AI.
As AI handles more of the routine work, writers are becoming content architects, strategists, and editors — making sure the overall documentation experience actually helps users succeed.
Users expect help exactly when and where they need it
People don’t want to search through long docs when they run into a problem — they expect answers to appear right when they need them. That’s why more teams are focusing on point-of-need documentation, where help is built directly into the product experience.
AI can help deliver that content at the right moment, but it can’t do much if the underlying documentation isn’t well-written and well-organized. Teams that succeed here are the ones that think beyond traditional docs pages and design for when, where, and how users actually need support.
The future of documentation is less about expecting users to come find answers — and more about making sure the answers find them.
New metrics are needed to track docs’ real impact
Traditional metrics like page views and ticket deflection don’t tell the whole story anymore. As documentation becomes more integrated into products — and as AI starts delivering content in new ways — teams need better ways to measure success.
Future-focused teams are starting to track things like:
– How docs improve user onboarding and activation
– How often docs help close deals or drive product adoption
– How documentation supports customer retention and long-term success
These kinds of metrics connect documentation directly to business outcomes, not just support efficiency. To keep up with how documentation is evolving, teams will need to rethink what they measure, and focus on how docs drive real impact across the entire customer journey.
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