Higher education institutions face persistent challenges with digital consistency. Decentralized structures, autonomous units, constant change, and one‑off projects often produce sprawling ecosystems filled with duplicated content, uneven quality, and fragmented user experiences. As AI becomes more deeply integrated into digital operations, this inconsistency doesn’t just frustrate users, it weakens governance, degrades data quality, and undermines the reliability of AI‑supported systems.

This talk will share a practical, people‑first approach to building digital consistency at scale. Drawing on McGill’s multi‑year effort to align a large-scale digital ecosystem, she explains how standards, governance structures, and communities of practice create the shared language and expectations that large institutions need to make meaningful, sustained progress.

This presentation explores:

• Why digital consistency is so difficult in large, decentralized environments.
• How McGill’s digital standards, governance model, and community of practice have reshaped institutional culture and improved collaboration.
• The structural challenges that remain, and why they matter even more in an AI‑accelerated landscape.
• How foundational work (content models, journey maps, governance monitoring, web registries) establishes the conditions for cohesive, AI‑ready digital ecosystems.
• Key lessons learned about alignment, trust, shared ownership, and the role of community in scaling consistent practices.

Attendees will come away with a clearer understanding of what it takes to operationalize digital consistency across complex organizations, and why investing in foundational structures is essential for delivering trustworthy, unified, and AI‑enabled digital experiences.