Who Gets Left Behind When Institutions Move Too Fast on AI?

Only 6% of faculty fully agree their institution has provided sufficient resources for AI training, yet 86% see themselves using AI in teaching in the future.¹ Faculty are preparing for an AI-enabled classroom before many have been given the support to do so.

AI is changing how faculty think about teaching and assessment. Without structured support, AI adoption depends on individual confidence and willingness to experiment. As a result, students experience the consequences through uneven guidance and assessments that may no longer capture what they truly understand.

The institutions closing that gap have treated faculty development as infrastructure, not an afterthought.

Short-Cycle Programmes Kept Pace Where Fixed Curricula Could Not

The University of British Columbia (UBC) built short-cycle teaching courses designed to be updated and redeployed as faculty needs shift. Rather than a fixed programme, each cycle prioritises areas of greatest uncertainty among faculty, with a focus on where timely support can have a direct effect on practice.

The model is deliberately iterative. UBC’s approach, as Lucas Wright, Senior Education Consultant for Learning Technology at the institution, describes it, rests on a small set of core pedagogical principles applied consistently across cycles so that what faculty produce is reusable rather than reactive. 

Concentrating on a few areas done well, rather than covering the full range of AI applications at once, is what makes the quality of teaching and learning gains sustainable. 

As AI detection remains unreliable and assessment practices come under pressure, UBC has identified assessment redesign as the area where faculty next need structured support. According to Wright, oral examinations are one example of where structured practice and concrete examples can build faculty confidence in approaches that make student reasoning visible regardless of the tools used.

Assessment Redesign Is Faculty Development by Another Name

At ESCP Business School, the challenge was reframed entirely. Rather than asking how to restrict AI use, the institution asked how to redesign assessment so that student reasoning remained visible regardless of what tools were used. That reframing changed how faculty engaged with the question.

To make student reasoning more visible, ESCP diversified its assessment formats. Oral exams, in-class and timed tasks, and process-based evaluation — including drafts, logs, and reflections — moved assessment away from static outputs toward observable reasoning and understanding.

"When assessment redesign was framed not as a constraint but as a way to better capture authentic learning, faculty engagement increased significantly," said Sonia Ben Slimane, Learning and Research Quality Assurance Manager at ESCP Business School.

Changes are introduced progressively, with faculty encouraged to experiment within their own teaching contexts rather than adopt standardised solutions. What the institution provides is the structure: coordinated governance and shared resources, supported by a school-wide review of course syllabi to ensure consistency across programmes.

Making Development Mandatory Drives Consistent Adoption

Abu Dhabi University (ADU) took a more direct approach. Professional AI development was made mandatory, grounded in annual faculty surveys that had consistently shown demand for it. The programme was therefore received as a direct response to what faculty had asked for, not as a top-down requirement.

The AI-Enhanced Teaching and Learning Certificate moves faculty from foundational AI concepts through to direct application in their own courses. The capstone requires each faculty member to redesign one of their courses using AI-driven approaches, assessed against learning outcomes, student engagement, and assessment effectiveness. Practical assignments are also embedded throughout, allowing faculty to develop AI-supported teaching materials and assessment strategies before they reach the capstone.

"Making the programme mandatory ensured consistent capability development across all faculty, avoiding uneven adoption," said Dr. Hamad Odhabi, Vice Chancellor for AI and Operational Excellence at Abu Dhabi University.

The pre- and post-programme assessments showed a clear shift. Faculty members entered with general awareness of AI but limited confidence in applying it. By the end, they demonstrated stronger AI literacy and the ability to move from conceptual understanding to active implementation.

"Faculty moved from viewing AI as an external tool or source of uncertainty to treating it as a strategic enabler of their teaching," Dr Odhabi remarked.

The Bottleneck Is Institutional, Not Individual

The bottleneck is not whether faculty are willing to engage with AI. It is whether institutions have built the structures that make good engagement possible. UBC, ESCP, and ADU each arrived at that conclusion through different means; all three point in the same direction.

For a deeper look at how institutions can build faculty capability for AI integration, explore DEC's Faculty Support and Resource Basket, a collection of over 50 practical strategies and case studies from institutions navigating similar challenges.

^{¹ DEC Global AI Faculty Survey 2025}

This article draws on insights from the DEC Best Practices Collection, available exclusively to DEC Members.