Design: Information Architecture

“The practice of information architecture is the effort of organizing and relating information in a way that simplifies how people navigate and use information on the Web.”—DSIA Research Initiative

Over the past two decades, the volatile evolution of Web applications and services has resulted in organizational uncertainty that has kept our understanding and framing of the information architect in constant flux. In the meantime, the reality of getting things done has resulted in a professional environment where the information architect is less important than the practitioner of information architecture (IA). Read More

Throughout my career as a user experience designer, I have continually asked myself three questions:

• What should my deliverables be?
• Will my deliverables provide clarity to me and their audience?
• Where do my deliverables and other efforts fit within the spectrum of UX design?

I have found that, if I do not answer these questions prior to creating a deliverable, my churn rate increases and deadlines slip.

When attempting to answer the third question, I use a framework I discovered early in my career: The Five Competencies of User Experience Design.PDF This framework comprises the competencies a UX professional or team requires. The following sections describe these five competencies, outline some questions each competency must answer, and show the groundwork and deliverables for which each competency is responsible. Read More

Card sorting has been a cornerstone of information architecture for decades. This method works well because it lets real people show you what they think. You can hand participants a set of labeled cards representing pieces of content, ask them to group the cards in whatever way makes sense to them, then study the patterns that emerge. The result: a window into users’ mental models that no amount of internal brainstorming could replicate.

However, the conversation around card sorting is changing. Artificial intelligence (AI) tools can now generate category structures in seconds. Large language models (LLMs) such as ChatGPT and Claude can sort a list of 40 content items into plausible groupings without your needing to recruit a single participant. Some teams have started asking whether traditional card sorting is still worth the effort. Others have gone even further and entirely replaced participant research and information architecture with AI outputs.

Both reactions miss the mark. AI does not make card sorting obsolete, but it does change how smart teams should use it. In this first installment of my new column Structuring Success, I’ll share what AI can and cannot do for card sorting, illustrate the differences that AI can make with real product examples, and offer a practical framework for combining human insights with AI’s speed. Read More