Key Insights from the DEC Leadership Summit Americas 2026
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By Digital Education Council
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October 22, 2026
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Five Emerging Priorities
01
Build Visible Leadership Coalitions
57% of leaders named a visible champion or leadership coalition as the strongest driver of progress. Institutions moving fastest paired top-level sponsorship with structured faculty support, not either alone.
Five Emerging Priorities
02
Resource Authentic Assessment Properly
Oral assessment, portfolios, and unplugged practice guard against deskilling better than policy statements alone, yet they demand far more staff time. Funding and workload models must begin to reflect that cost.
Five Emerging Priorities
03
Build Cross-Sector Partnerships
AI and the future of work cannot be left to universities alone. Government, industry, and institutions must act together, especially in Latin America, where fewer institutions can invest in AI independently.
Five Emerging Priorities
04
Treat Curriculum and Operating Models as Continuously Adaptable
Periodic curriculum review cannot keep pace with how quickly technology and the workforce are changing. Institutions must move to continuous redesign so programmes can adapt while they are being delivered.
Five Emerging Priorities
05
Match the Lever to the Institution
Faculty readiness (28%), evidence of impact (28%), and dedicated resources (25%) ranked almost equally as accelerators. No single lever fits every context, so each institution must identify its own constraint.
Across the Americas, AI adoption is unfolding from sharply different starting points. Latin American institutions report high student enthusiasm alongside acute structural pressures, while those in the US and Canada describe more cautious campuses but greater capacity to invest.
What unites them is a shared bottleneck: 57% of leaders say coordinating fragmented initiatives now consumes most of their time.
This report captures the conversations from the DEC Leadership Summit Americas 2026, hosted at Columbia University in New York, where 37 senior leaders from 29 institutions examined what it takes to turn AI experimentation into institutional change.
It sets out ten signals for the sector, from the role of visible leadership coalitions to the case for bringing students into formal decision-making, and explores why progress depends as much on context as on any single lever.
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