The rapid entry of artificial intelligence into higher education is reshaping how knowledge is produced, how teaching and assessment are carried out, and what academic expertise means. For first-generation students, minority students, young people from the periphery and students with disabilities, the technology offers real opportunity. It can personalize learning, make content accessible in the student’s own language and at their own pace, and provide on-demand support to those without access to private tutoring or professional networks. Without institutional guidance, however, it may deepen existing gaps.
The paper presents an overview of AI adoption in Israel’s economy and academia. It analyzes five types of barriers: economic and infrastructural, linguistic and cultural, algorithmic bias, literacy gaps, and institutional and psychological barriers. It also points to two central risks: an “AI literacy divide” and “cognitive debt.”
Experimental findings from around the world show that pedagogical design, not the technology itself, determines whether a tool advances learning or undermines it. Responsibility for proper implementation therefore lies with the institution, not with the individual student.
Drawing on this analysis and on international examples, the paper recommends seven steps:
– Free institutional access to advanced, pedagogically designed tools.
– Inclusivity impact assessments before adopting AI systems.
– Mandatory AI literacy from the first year of study.
– A shift to process-based assessment and transparency declarations instead of AI-detection tools.
– Mandatory training for teaching faculty.
– Involvement of diversity and inclusion coordinators in shaping policy.
– Partnerships with philanthropic foundations to help close gaps.
