What happens when increasingly powerful AI systems are built on top of poorly structured information?
Much of the conversation around AI focuses on better models, better prompts, and better interfaces. But according to information architect Jorge Arango, useful AI also depends on something less visible: the architecture underneath it.
In this episode of UX Spotlight by Userlytics, host Denis Cristea sits down with Jorge to explore how information architecture is evolving in the age of AI, why context matters more than simply feeding systems more data, and why chatbots should be treated as one interaction pattern rather than the inevitable future of every interface.
Drawing on nearly three decades of experience in digital design, Jorge connects today’s AI shift to earlier transitions from the early web to mobile computing. He explains why information architecture has always been about more than menus and navigation: at its core, it is about helping people understand their options, find useful information, and make better decisions.
What You’ll Learn
• Why information architecture is bigger than navigation. Jorge explains why the discipline extends beyond menus, site maps, and website structure, and how it can help people find their own paths to knowledge.
• How better information can increase agency. Clear structure helps people understand what they can do, what choices are available, and how to act on the information in front of them.
• Why AI still needs architecture underneath the interface. A simple chat box may hide a much more complex system of rules, boundaries, sources, and context that determines what the model can use and how it should respond.
• Why more data does not always produce better AI. Jorge shares how larger bodies of information can sometimes make model responses less relevant, while carefully structured context can lead to stronger results.
• Why chatbots are useful, but not always the right interface. Conversational systems give users flexibility, but they can also make it harder to understand what a product can actually do.
• How information architecture can support trust. Carefully selected and structured information can help keep AI responses relevant to the situation and reduce the risk of misleading users.
• Why interaction metaphors matter. The way we describe and present technology influences what people expect from it, whether we are talking about web pages, chatbots, or artificial intelligence itself.
Key Takeaway
“Better context can be more useful than simply giving an AI system more data.”
– Jorge Arango, Information Architect
One of the clearest ideas to emerge from the conversation is that powerful models do not remove the need for structure.
People still need to understand where they are, what they can do, what information matters, and whether they can trust what the system is telling them.
The interface may change. The need for good information architecture does not.
Listen to the Episode
Hear the full conversation with Jorge Arango on UX Spotlight by Userlytics.
Available on YouTube, Spotify, and Userlytics.
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About the Guest
Jorge Arango
Jorge Arango is an information architect, author, educator, consultant, and speaker who has spent nearly three decades applying architectural thinking to digital experiences and complex information environments. His recent work explores the relationship between information architecture, AI, and context engineering.
About the Host
Denis Cristea
Denis Cristea is the host of UX Spotlight by Userlytics, a podcast featuring conversations with UX researchers, designers, product leaders, and industry experts. With a background in media, content production, and UX-focused storytelling, Denis brings a conversational and practical perspective to discussions about research, insights, technology, and digital experiences.
About UX Spotlight by Userlytics
UX Spotlight by Userlytics features conversations with UX researchers, designers, product leaders, and industry experts exploring the ideas, practices, and technologies shaping modern user experience.
Each episode goes beyond surface level trends to examine how teams understand users, make better decisions, and create stronger digital products.
