AI vs. Human Documentation: Finding the Right Balance

"Should we use AI to write our documentation?" This question comes up in nearly every conversation I have with documentation teams. The answer isn't simple.

After working with dozens of teams implementing AI documentation tools, I've found that the best approach isn't choosing between AI or humans. It's finding the right balance between them.

The Current State of AI Documentation

Let's be clear about what AI can and can't do in 2025:

What AI Documentation Tools Do Well

• Generate first drafts quickly from minimal input
• Follow consistent structures across multiple documents
• Explain technical concepts in clear, accessible language
• Create variations for different audiences
• Maintain consistent terminology throughout documentation
• Generate code examples in multiple languages
• Create visualizations from text descriptions

Where AI Documentation Still Falls Short

• Deep domain expertise in specialized fields
• Understanding undocumented context within organizations
• Identifying what users will find confusing without explicit guidance
• Making judgment calls about what to include or exclude
• Verifying factual accuracy of generated content
• Creating truly innovative approaches to documentation challenges

These strengths and limitations shape where AI provides the most value in documentation workflows.

When to Use AI for Documentation

AI documentation tools excel in specific scenarios:

1. Standardized, Structured Content

When documentation follows consistent patterns, AI shines. Examples include:

• API reference documentation
• Product specifications
• Standard operating procedures
• Troubleshooting guides with common patterns

For these types of content, AI can generate accurate, well-structured documentation quickly, especially when provided with clear templates and examples.

2. First Drafts and Outlines

Starting with a blank page is hard. AI excels at creating initial drafts that humans can refine. This approach works well for:

• Project documentation
• Meeting notes and summaries
• Process documentation
• Basic tutorials and guides

The AI handles the structure and basic content, while humans add nuance, context, and expertise.

3. Content Transformation

AI efficiently transforms existing content into new formats:

• Converting technical specifications into user guides
• Adapting documentation for different technical levels
• Creating summaries of longer documents
• Translating documentation into multiple languages

This capability helps teams maintain consistent information across different documentation types without duplicating effort.

4. Repetitive Documentation Tasks

Some documentation tasks are necessary but tedious. AI handles these efficiently:

• Generating code samples in multiple languages
• Creating standard sections that appear in many documents
• Updating documentation when minor changes occur
• Formatting and structuring content consistently

Automating these tasks frees human writers to focus on higher-value work.

When Human Documentation Is Essential

Despite AI's capabilities, human expertise remains crucial in several areas:

1. Novel or Cutting-Edge Topics

AI models train on existing content. For truly new concepts or technologies, human expertise is irreplaceable:

• Documentation for innovative products with no direct precedent
• Emerging technologies not yet widely documented
• Proprietary systems with limited public information

In these cases, humans must create the foundational content that AI can later help maintain and expand.

2. Complex Decision-Making Guidance

Documentation that helps users make nuanced decisions benefits from human judgment:

• Architectural decision guides
• Best practices based on hard-won experience
• Security recommendations with risk trade-offs
• Implementation strategies for complex systems

These documents require deep expertise and judgment that AI currently lacks.

3. Content Requiring Empathy and User Perspective

Understanding user frustrations and needs often requires human empathy:

• Onboarding materials for complex products
• Troubleshooting guides for confusing errors
• Documentation for users with accessibility needs
• Content addressing sensitive topics or user pain points

Humans excel at anticipating confusion and addressing emotional aspects of user experiences.

4. Critical Review and Verification

AI can generate plausible-sounding content that contains subtle errors. Human review is essential for:

• Safety-critical documentation
• Security guidance
• Regulatory compliance documentation
• Content where errors could have significant consequences

Human experts provide the final verification that ensures documentation accuracy.

The Hybrid Approach: AI-Human Collaboration

The most effective documentation strategies combine AI and human strengths. Here's how successful teams are implementing this hybrid approach:

1. AI-Assisted Human Writing

In this workflow:

1. Humans define the documentation scope and objectives
2. AI generates initial drafts based on human guidance
3. Human writers review, edit, and enhance the content
4. AI helps with consistency checks and formatting
5. Humans perform final verification and approval

This approach combines AI efficiency with human judgment and expertise.

2. Human-Guided AI Generation

For more standardized content:

1. Humans create templates and examples
2. AI generates content following these patterns
3. Humans review for accuracy and edge cases
4. AI implements corrections across all similar content
5. Humans perform spot checks and final approval

This approach works well for large-scale documentation with consistent patterns.

3. Complementary Responsibilities

Some teams divide responsibilities:

• AI handles: Reference documentation, standard procedures, code examples, diagrams from descriptions
• Humans focus on: Conceptual explanations, best practices, decision guides, user-focused content

This division plays to the strengths of both AI and human writers.

Case Study: A Balanced Approach

A software company I worked with implemented a hybrid documentation strategy with these results:

The key wasn't replacing humans with AI, but redirecting human effort to where it adds the most value.

Implementation Guidelines

If you're integrating AI into your documentation workflow, follow these guidelines:

1. Start with a Clear Content Strategy

Before implementing AI tools:

• Define your documentation types and purposes
• Identify your audience and their needs
• Establish quality standards and success metrics
• Determine which content types are candidates for AI assistance

AI works best when guided by a clear strategy.

2. Implement Appropriate Review Processes

Different content needs different levels of review:

• High-risk content: Multiple expert reviewers
• Standard reference material: Spot checks and automated testing
• Conceptual content: Review for accuracy and clarity
• User-facing guides: User testing and feedback

Adjust your review process based on content importance and complexity.

3. Train Your AI on Your Documentation

Generic AI produces generic documentation. Improve results by:

• Providing examples of your best documentation
• Creating templates for common document types
• Building a company-specific style guide
• Using tools like resetDocs that can adapt to your documentation style

The more your AI understands your specific needs, the better its output will be.

4. Upskill Your Team

Documentation roles are evolving, not disappearing. Help your team adapt by developing:

• AI prompting skills
• Content strategy expertise
• Editorial judgment
• User experience design
• Technical accuracy verification

The most valuable documentation professionals will combine technical knowledge with AI guidance skills.

The Future of Documentation

As AI capabilities continue to advance, the balance will shift, but human expertise will remain essential. The future of documentation isn't AI or humans—it's AI and humans working together in increasingly sophisticated ways.

The most successful documentation teams will be those that thoughtfully integrate AI tools while preserving the human judgment, expertise, and empathy that truly great documentation requires.

How is your team balancing AI and human documentation efforts? Share your experiences in the comments.