Opinion
24-03-2026 | 14:56
AI in Lebanese Universities: Tech Investments Surge, But Faculty Readiness Lags
Lebanese universities are investing heavily in AI tools, but real educational transformation hinges on preparing instructors—whose training boosts readiness by 45%—rather than technology alone.
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Lebanese universities are racing to integrate artificial intelligence into teaching, as if the mere presence of technology can fix a system already under pressure. Millions are spent on platforms, tools are introduced, and policies are drafted. Yet one critical question remains largely unaddressed:
Are instructors ready?
The current discourse around AI in higher education remains overwhelmingly tool-driven. Institutions compete to showcase innovation, often equating digital adoption with educational progress. This assumption, however, is deeply misleading. Technology, no matter how advanced, does not transform education on its own.
Instructors do.
This creates a fundamental mismatch between institutional investment and actual outcomes. Universities are investing heavily in software and platforms while underinvesting in the human capacity required to use them effectively. In Lebanon, this gap is particularly visible. Professional development is often treated as a one-time intervention rather than a sustained process, leaving AI underutilized not because it lacks potential, but because it lacks ownership at the instructional level.
To understand this gap, it is important to distinguish between two concepts that are often conflated: systematic and systemic change.
A systematic approach focuses on process. It involves structured, step-by-step implementation, such as rolling out AI platforms or scheduling training sessions. While necessary, this alone is insufficient.
A systemic approach, by contrast, addresses the broader ecosystem. It recognizes that meaningful change requires alignment across institutional culture, incentives, governance, and support structures. Without this alignment, even the most well-planned initiatives fail to produce lasting impact.
Evidence from recent research conducted across Lebanese higher education reinforces this point. Drawing on a large-scale quantitative study involving 390 participants across multiple faculties and academic roles, a structured three-week professional development program was implemented to support AI integration in teaching.
The findings were clear and statistically significant.
Following the training, instructors’ self-efficacy increased by 45 percent. This substantial improvement reflects a stronger belief in their ability to effectively use AI in their teaching practices. More importantly, it demonstrates that when instructors receive targeted and sustained professional development, their confidence and readiness to engage with AI increase meaningfully.
This 45 percent surge in self-efficacy is not a marginal outcome. It is a decisive indicator of where real transformation begins.
The implication is clear: access to technology alone does not drive change. Human capacity does.
However, self-efficacy represents only one dimension of a more comprehensive framework. A deeper understanding of AI adoption in higher education reveals the interaction of three interconnected factors: instructors’ orientation toward AI-supported teaching, their self-efficacy, and their instructional initiative.
Orientation shapes perception. Instructors who view AI as an opportunity are more likely to engage with it, while those who perceive it as a threat tend to resist, regardless of institutional pressure.
Self-efficacy shapes capability. Confidence determines whether instructors feel able to translate knowledge into practice.
Instructional initiative shapes action. It reflects the willingness to experiment, redesign teaching strategies, and move beyond traditional approaches.
These dimensions form a coherent progression. Orientation influences self-efficacy, which in turn drives instructional initiative. Without alignment across these elements, adoption remains superficial.
For policymakers and university leaders, the implications are both strategic and urgent.
Lebanon’s higher education sector possesses a significant strength: its human capital. The willingness of instructors to learn and adapt is evident when the right conditions are provided. Yet this strength remains underleveraged due to systemic weaknesses, including fragmented professional development and limited alignment between institutional incentives and pedagogical innovation.
At the same time, there is a clear opportunity to reposition Lebanese universities as leaders in human-centered AI integration. This requires a shift in priorities, from investing primarily in tools to investing in people.
The path forward is not about abandoning technology, but about rebalancing the strategy behind it. Sustained professional development, supportive institutional cultures, and leadership committed to long-term capacity building must become central to any meaningful AI initiative.
Artificial intelligence will continue to evolve, regardless of institutional readiness. The real question is whether educators will be empowered to evolve alongside it.
Because in the end, the future of education will not be shaped by artificial intelligence alone, but by educators who are confident enough to use it, critical enough to question it, and proactive enough to transform it into meaningful learning.
Disclaimer: The opinions expressed by the writers are their own and do not necessarily represent the views of Annahar.