Reimagining Education in the Coming Decade: What AI Reveals About What Really Matters

Samar A. Ahmed^1,2*

• ¹Ain Shams University, Cairo, Egypt
• ²Rabdan Academy, Abu Dhabi, United Arab Emirates

My central argument is that higher education's future lies not in defending what AI does better, but in cultivating what AI cannot replicate: epistemic judgment, belonging, creativity, and wonder. Universities must reimagine themselves as human commons-spaces where meaningmaking, ethical responsibility, and imagination thrive. Three pillars have long sustained higher education: information transmission through lectures, standardized assessments as proof of mastery, and degrees as the monopoly of credentialing. Each is now destabilized by AI.Higher education is undergoing structural disruption in three interlinked domains. First, information transmission through traditional lectures has been under scrutiny for decades (Mazur, 2009;Bruff, 2019), and with the rise of AI tutors and multimodal platforms, one-way teaching is rapidly becoming redundant. Regional studies reinforce this trajectory: in Saudi Arabia and the UAE, students increasingly report preferring AI-driven simulations and explanations over passive note-taking (Bugawa et al., 2025). Similarly, in curricular reviews I conducted at King Salman International University, lectures were often regarded as supplementary to AI-powered resources rather than as the primary mode of learning. Second, standardized assessment-historically anchored in predictable formats such as multiple-choice quizzes, short essays, and formulaic problem sets-is now vulnerable to automation (Luckin, 2022). Yet accreditation reviews in the UAE reveal that institutions remain heavily dependent on these formats, even as students openly exploit AI to bypass them (Tbaishat, 2025). My own compilation of external examiner reports confirms this disconnect, with reviewers consistently flagging the misalignment between AI-enabled student practices and static assessment methods. Third, credential monopolies, once tightly held by universities as gatekeepers of expertise, are being eroded by AI-enabled micro-credentials and blockchain-based verification systems (Siemens, 2020). Evidence from the Gulf illustrates the same shift: employers increasingly recognize modular certifications, while universities experiment cautiously with competencybased recognition (Plexal/UK-Gulf Fellowship, 2025). In program planning work I have undertaken, micro-credentials are already presented as legitimate supplements to degrees, signaling a transformation in how knowledge and expertise are validated. Collectively, these shifts do not signify the end of higher education but rather the collapse of outdated scaffoldingwhat will endure are the uniquely human practices that AI cannot replace. The enduring value of higher education lies in cultivating judgment, belonging, and creativitydimensions that AI cannot replicate. While AI produces outputs, it does not interpret meaning; thus, faculty must shift from delivering information to fostering epistemic judgment. Barnett (2009) frames this as the pursuit of "critical being." In my own teaching of medicine, for example, I have seen students use AI to generate differential diagnoses, yet the real learning occurs when they weigh ethical, cultural, and contextual factors-judgments that no algorithm can provide. Equally essential is the relational dimension of learning: education is not only cognitive but also social. Tinto (2017) emphasizes belonging as central to persistence, and regional surveys confirm that while students in the UAE appreciate AI's personalization, they remain uneasy about its lack of "human touch" (Plexal/UK-Gulf Fellowship, 2025). My students often affirm that mentorship and recognition from faculty sustain their motivation more than any digital tool. Finally, creativity and wonder remain uniquely human. As Biesta (2021) argues, curiosity and intellectual risk are central to education. Regional evidence supports this: entrepreneurship students in the Middle East found that AI simulations enhanced technical competence, but genuine creative breakthroughs emerged only in human-led discussions (Awad et al., 2024). In student projects I have supervised, the most profound insights consistently came not from polished AI outputs but from moments of play, improvisation, and exploration. If universities are to thrive, they must reframe their practices around what endures.• Curriculum: There needs to be a shift from content-heavy syllabi to inquiry-driven frameworks. In regional programs I have reviewed, inquiry-based designs that embed AI tools within authentic tasks-such as case-based simulations in medicine or scenariobased exercises in security-produced stronger engagement (Laurillard, 2012). • Pedagogy: Faculty should design learning ecologies rather than perform content delivery.Studies in GCC universities confirm that students prefer active, problem-oriented learning experiences supported by AI (Bugawa et al., 2025). Students thrive most when pedagogy emphasizes debate, co-creation, and simulation. • Assessment: Move to authentic tasks-simulations, reflective narratives, collaborative projects-that emphasize reasoning and adaptability (Boud & Falchikov, 2006). Regional surveys reveal faculty reluctance to abandon traditional exams despite evidence of AIenabled cheating (Tbaishat, 2025). I recommend shifting toward reflective and applied assessments.• Faculty roles: Professors must serve as stewards of meaning, not sages on the stage. Their authority derives from intellectual integrity, mentorship, and modeling judgment (Barnett, 2009). The Gulf-wide surveys (Plexal/UK-Gulf Fellowship, 2025) show that while students trust AI for content, they look to faculty for ethical guidance and mentorship. By the next decade, classrooms will look radically different. The following scenarios build not only on global scholarship but also on regional pilots and reforms:• Hybrid immersive environments: In Gulf universities, early adoption of AI-enhanced VR tools points to a future where students from different countries collaborate in shared immersive spaces (Bugawa et al., 2025). • AI companions: In UAE surveys, students already bring generative AI into tutorials (Anthology Survey, 2023). Within a decade, AI tutors may accompany every learner, while classroom sessions focus on critique, debate, and meaning-making. • Discipline-specific examples:In my own teaching of medicine, I have observed how anatomy education has already shifted from static dissection-based approaches toward 3D models and virtual reality. AI-driven, data-rich simulations are poised to extend this trend even further, which suggests that the true pedagogical focus of medical education must increasingly be on empathy and ethical decision-making rather than on technical recall. In law, research shows that mock trials are beginning to incorporate AI-curated precedents, serving as precursors to "living courts" where students can grapple not only with legal reasoning but also with questions of fairness and the unintended consequences of algorithmic judgments (Siemens, 2020;Tbaishat, 2025). Similarly, in engineering, evidence indicates that students already use AI to model sustainability trade-offs in their projects; here, the real challenge is not computational accuracy but navigating the cultural and ethical implications of design choices (Awad et al., 2024).• Knowledge commons: Universities in the GCC (Cooperation Council for the Arab States of the Gulf) are experimenting with modular, competency-based learning ecosystems (Plexal/UK-Gulf Fellowship, 2025), foreshadowing the rise of decentralized knowledge communities.• Ethical laboratories: UNESCO's Green Paper on Generative AI in UAE Education stresses the role of classrooms as civic spaces for ethical debate (UNESCO/IIEP, 2025). Role-play and scenario testing prepare students to live with technology responsibly. To thrive in this new landscape, institutions must act deliberately.Faculty development must be reoriented toward facilitation, mentorship, and interdisciplinary collaboration, while assessment practices should be redesigned to move beyond AI-vulnerable tasks and instead reward originality and ethical reflection. At the curricular level, ethics should be institutionalized in line with the UAE's Green Paper recommendations (UNESCO/IIEP, 2025), ensuring that values-based learning anchors innovation. Equally vital is the protection of spaces of belonging, which serve as foundations of trust within increasingly decentralized learning ecosystems. Finally, universities must champion lifelong adaptability, positioning themselves not as one-time credentialing providers but as continuous partners in lifelong learning. The real danger is not that AI will render education obsolete, but that universities will cling to outdated practices, mistaking tradition for substance. What must perish are the habits that reduce teaching to transmission and learning to credentialing. What must endure-and must be amplified-are the irreducibly human practices of judgment, belonging, and wonder.This conclusion does not arise from theory alone but from practice. Across more than a decade of designing and evaluating programs in medicine, pharmacy, and security education, I have seen students persist when they feel part of a community and thrive when invited into spaces of curiosity and ethical dialogue. Regional surveys and pilots confirm this: Gulf students want personalization but also mentorship; they embrace AI but still need human recognition (Plexal/UK-Gulf Fellowship, 2025). AI cannot replicate these experiences. Higher education must reclaim its role as a human commons-transforming the abundance unleashed by AI into an abundance of humanity.