Training
Information Architecture
When content grows, people stop browsing - they search. And increasingly, they ask a question directly, through search or a conversational assistant. This training teaches you how to build a user-centred information architecture and make it usable for AI systems.
Who is this module for?
This course is designed for teams managing content and digital products where “finding” has become a problem: digital leads, PMs/POs, UX/UI designers, content designers, SEO, communications teams, business teams, and anyone responsible for internal search or conversational assistants. Ideal if your website or intranet is growing, labels are a constant debate, search isn’t delivering, or you want to prepare your content for AI-driven use cases (augmented search, chat, dynamic FAQs).
What you'll get from it
You’ll get a practical approach to improving findability across every entry point: navigation, search, and natural-language questions via an assistant. You’ll learn how to diagnose the causes of poor findability, build a lightweight inventory and a minimal content model, then design a clear structure with labels people actually understand. Most importantly, you’ll leave with a testable version (tree testing + a simple “answer testing” checklist for the assistant) and guardrails for using AI as an accelerator without sacrificing quality.
What you'll actually learn
- Structure a content system (types, relationships, minimal metadata) adapted to your context
- Write consistent labels and naming conventions (rules + synonyms)
- Design a usable card-sorting protocol (items, instructions, participants)
- Turn findings into structural decisions (categories, levels, trade-offs)
- Define tasks and validation criteria for findability (tree testing)
- Evaluate AI-assisted access with a simple checklist (answer, source, clarity)
Key takeaways
Everything you need to know to organize this day for your team.
1 day, from 9:00 AM to 5:30 PM with breaks and lunch
6 to 12 people from the same organization
Online or on-site
In French or English
Practical examples & scenarios
Reusable tools & templates
No prerequisites
The agenda
An intensive day, structured to alternate between theoretical input and immediate practical application in workshops.
Foundations: findability and new entry points
Understand what breaks findability today and what AI truly changes, without the hype.
Lightweight inventory + content model + questions and tasks
Structure the essentials: content types, minimal metadata, intents, questions, and tasks to support.
Card sorting: categorise and label
Group content around users’ mental models, then test categories and labels that people actually understand.
Sitemap v1 + labelling rules + synonyms
Build a first sitemap in natural language and set shared rules for naming and managing synonyms.
Validation: tree testing + lightweight answer testing for the assistant
Validate findability first, then test the assistant layer with a simple checklist focused on the answer, the source, and clarity.
Wrap-up and governance: updates, quality, versioning
Define how the structure, assistant, and content stay healthy over time: ownership, rituals, quality standards, and an update cadence.
Take away some practical tools
