5 leisurely minutes
I am currently in Philadelphia to attend the 2026 Information Architecture Conference. I attended my first IA Summit two decades ago. Given this milestone, I started thinking about where Information Architecture (IA) is today. Though no longer a popular job title and many of its loudest voices have moved on to talk about other things, IA is still relevant. In some ways, information architecture is more important than ever. Technology continues to evolve at an ever quickening pace (understatement of the year), but the core challenges of the Information Age remain: finding, understanding, using, and trusting information. IA helps address these issues through holistic, human-centric thinking about information and its use. Here are three areas where information architecture can help teams deliver better experiences to their users.
Human Centricity
As AI automates more and more of the design and development process, institutional practices that keep humans central to the work get weaker. Information architecture has a rich, multi-disciplinary foundation with a strong focus on the user coupled with a deep understanding of information. IAs have practiced their craft in the technologies that have driven economic, political, and cultural change over the past three decades: digital cataloging systems, multimedia (like CD-ROMs), websites, mobile apps, social media, voice, and virtual reality to name a few. And IAs have worked with adjacent practices that are focused on the human side of technology, such as usability, user research, and content strategy. This long history in different technologies and human-centric practices has a lot to offer, especially to those working with AI.
Organizational Alignment
The second area where information architecture is invaluable is organizational alignment around language. The popularity of agile and lean techniques for design and development is unquestionable. But something is getting lost in the midst of all those two-pizza teams. Agreement around the definition, labeling, and categorization of things becomes increasingly difficult as the number of independent teams grows. Alignment requires a dedicated effort to sync teams around language, coordinate information systems for interoperability, and govern the processes that create and deliver information. If you have ever worked in a large organization and sat in a meeting to discuss the navigation of your website, you know what I am talking about. Information architecture has an extensive toolkit for creating conversations around information governance, helping everyone get on the same page.
Clarity for AI
The third area where IA is more important than ever is AI, particularly around structured data or semantics. There are different names for this depending on who you talk to, such as taxonomy and ontology, the semantic layer, or knowledge graphs. But what they all share in practice is their role in clarifying the language that is employed by users or enterprises in relation to AI systems. Consider gen AI. LLMs are by their very nature large semantic models. And unless they have been trained on the specific domain in question, they will have issues with context and disambiguation of language, leading to less than optimal outputs. Anyone who has worked with a RAG AI system has seen this at work. It takes more than just uploading a bunch of PDFs and Word documents into a RAG platform with a set of instructions to the responses your organization needs. An architectural approach can help a team to structure and clarify document inputs. This work can help a team identify areas where context of language can be clarified through the assistance of a taxonomy or semantic model, resulting in better outputs. It also has the added benefit of improving the source documents, making them easier to understand for the humans who use them.
IA Now
As the current hype of AI promises to completely change the way we build experiences, information architecture can help ground teams in reality by giving them ways to be more human-centric, align around organizational information and its use, and produce better outcomes with AI. To be clear, I am not saying that every organization needs an information architect. But every organization does need people who can think architecturally about information (and not just about data). IA requires dedicated focus and time. It is one thing to say we all do IA, but it is another thing to actually do it. So prepare to spend time on the information architecture of what you are building. It will be well worth it.
So keep calm, and IA on.
Berries to Pick
IA Thinkers
Here is a short list of folks writing about the importance of IA for today. Let me know who you follow.
Jorge Arango — One of the authors of the canonical polar bear book, Jorge is a prolific writer on information architecture and has spent the past few years discussing how IA is good for AI.
Austin Govella — Austin, the co-author of one of the most practical books on information architecture, has recently started blogging on IA skills and approaches that are still relevant.
Factor — A consulting firm dedicated to helping organizations leverage their information, Factor frequently writes about information architecture, taxonomy, and ontology.
Free IA Knowledge
A short list of free, online sources for learning about IA outside of books.
Boxes and Arrows — A design magazine started in 2002, Boxes and Arrows featured many articles on IA. It was put on hiatus in 2023, but remains an archive on IA and design topics freely available to everyone.
Page Laubheimer at Nielsen Norman Group: “Information Architecture: Study Guide” — A collection of articles and videos on IA principles, research methods, and navigation design.
World IA Day — A globally distributed one-day conference on all things information architecture.
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