McGill University runs a thousand sites on its central platform, 500 more custom builds, and tracks 6,000 to 8,000 content edits a week. Joyce Peralta, Manager of Digital Communications at McGill, joins Chris Bryce to talk about the content model project addressing all of it.

The number that anchors this conversation: 61 different terms used across the university for the exact same program component. Joyce's central point is that AI does not cause content inconsistency, it amplifies inconsistency that already exists. The inaccuracy people see in AI answers comes from information presented differently across websites, not from information that is wrong.

McGill looked at building a separate content repository just for AI and turned it down, because a second repository means a second governance and synchronization problem. Joyce points to Dries Buytaert's markdown experiment, which found AI bots still hit the website itself the majority of the time.

The content model work is federated across about 50 subject matter experts from departments across the university. Rollout runs concept by concept, with a timeline Joyce estimates at five years or more. Her real point on success: this cannot be a Communications project or an IT project alone, it has to be both working as one team, with alignment across the whole institution.

Also in this one: the student usability panel that tracks how AI use among students changes year over year, why Drupal and the Drupal EDU Slack group are a real source of leverage, and what a taxonomy problem looks like at university scale.

Chapters

0:00 Welcome to Episode 48
1:05 Meet Joyce Peralta, McGill University
1:38 The velocity of change since Beyond the CMS launched
2:35 Inside McGill's web services team: comms and IT as one team
4:12 Who owns the university's content model
5:56 The vision behind McGill's content transformation
9:34 Taxonomy at scale: a thousand sites, 500 custom builds, 6,000 to 8,000 edits a week
14:33 Federated with 50 subject matter experts: the 61-term problem
16:19 AI amplifies inconsistency, it does not cause it
17:19 Why McGill rejected a separate AI-only content repository
19:10 How McGill actually uses AI in the content model project
21:35 Concept by concept: a rollout Joyce estimates at five years or more
24:02 Open source, Drupal, and the Drupal EDU Slack group
26:49 Three feedback groups, including the student usability panel
29:50 The human side of technology as AI reshapes expectations
31:32 Lessons for higher ed teams just starting this work
33:38 Where to find higher ed thought leadership
34:52 Wrap-up

Click here to watch a video of this episode.

Links
Joyce Peralta on LinkedIn
Dotfusion headless CMS services
Chris Bryce on LinkedIn

Click here to view the episode transcript.