AI overview

When used thoughtfully, AI can enhance user experiences through personalized interactions, increased efficiency, and innovative designs. Regardless of the AI resources or workflows you use, it's important to ensure that you're aligned with the compliance rules, ethical considerations, and best practices on this page.

PatternFly AI resources

The following guides are intended to help you integrate AI into your workflows as you design and develop products with:

Design language: The foundational design decisions that guide the use of AI features in products.
Rapid prototyping: Guidance for generating and iterating AI features during early stages of design.
Marketplace: Plugins that give AI coding assistants knowledge and skills to generate more accurate, PatternFly-compliant code.
AI-assisted code migration: Guidance for using AI to speed up and simplify codebase migrations.
Conversational design principles: Guidance for designing effective and human-centered AI conversations.
Generative UIs: Proof-of-concept resources for creating UIs that can utilize AI to dynamically generate elements as needed.

What rules and best practices do I need to follow?

All AI systems built with PatternFly must adhere to Red Hat's legal and ethical framework.

Red Hat policies

When using PatternFly to design Red Hat products, you must adhere to AI-related policies that Red Hat has previously outlined. This means you must:

Gain approval before using AI technology for business related to Red Hat.
Gain approval before using certain information as input for AI technology.
Review, test, and validate generative AI model output.
Always consider data privacy when entering company or personal information into AI resources, and ensure compliance with all company data protection policies and rules around AI usage.

View policy details (requires Red Hat login)

PatternFly AI principles

These five core principles create our ethics-first framework, which should guide the use of AI related to PatternFly.

All people involved in any step of creating AI are accountable for considering its impact. Roles and processes are clearly defined and documented.

AI systems should be easy to explain and comprehend. Humans should be able to easily perceive, recognize, and understand their decision-making processes. Imperceptible AI is not ethical.

All processes, decisions, and practices involved in AI systems should be open and transparent—not hidden. Users should be able to understand who is making decisions and how these decisions are made.

AI systems that are fair should be intentionally designed to prioritize and promote inclusion. They should focus on accessibility for all humans and should minimize—not amplify—bias.

At their core, AI systems must prioritize a human-centered approach, focusing on addressing real needs and empowering humans. They should emphasize accessibility, transparency, user autonomy, and privacy. To build trust and promote understanding, these systems should provide users with intuitive interfaces and clear communication of intentions and capabilities.

How do I design AI features with best practices in mind?

When designing, developing, and using AI, consider the following ethical and best-practice guidelines.

Document your value proposition

Every AI product should begin with a documented user need and problem statement. Before choosing a technology, identify the specific gap in the current experience that AI is uniquely qualified to fill.

Determine if AI adds value

Not all uses of AI are good for your UX strategy. Conduct research to identify real user needs where AI provides a clear advantage over traditional UI patterns.

Do not add AI features simply because they are new or trendy. If the value proposition isn't documented and validated by research, stick to standard UI.

When to use AI

Improve productivity: Streamlining onboarding, data entry, or routine job tasks.
Offer better personalization: Tailoring search results or dashboard views to a user's unique history.
Support sustainability: Making design and development processes more repeatable.

Choosing the right AI technology

Some AI features are better suited for different types of AI, and they should align with the user's risk tolerance.

AI feature type	Usage	Risk tolerance
Generative AI	Summarization, creative brainstorming, and conversational support.	Lower: Best when a "human-in-the-loop" can verify and edit the output.
Predictive or structured AI	Data classification, trend forecasting, and risk scoring.	Higher: Best for tasks requiring high precision and repeatable, data-driven outcomes.

Ethical design and compliance checklist

When working on an AI system, you should consciously check that you're in alignment with the core principles and best practices of PatternFly and Red Hat.

To help teams navigate best practices and requirements, we offer a guiding checklist that covers accountability, transparency, and fairness standards. Note that this resource is open to change and is not exhaustive. Always ensure you're following the most up-to-date industry standards and Red Hat AI requirements.

Download Ethics and Compliance Checklist (PDF)

Core guidelines for AI

While the checklist handles the details, keep these three non-negotiables in mind:

Imperceptible AI is not ethical: Users must always be able to recognize when they are interacting with an AI system.
Communicate uncertainty: If a model has low confidence in a result, the UI must reflect that uncertainty to the user.
Human-in-the-loop: AI should augment human expertise. Always have a human review AI-generated output for accuracy and tone before it is finalized.

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