LAU President Chaouki T. Abdallah opened the university's first Pulse Exchange on September 11, 2026, with a direct challenge: the institution's task is not to adopt or resist artificial intelligence, but to orchestrate it. The event, organized by LAU Internal Consulting and Project Management at the Beirut campus, brought together deans, administrators, and faculty to debate how AI should reshape teaching, operations, and graduate readiness.
"Our challenge at LAU is not simply to adopt AI, nor is it to resist it. It's to orchestrate it," Dr. Abdallah said. He argued that as intelligent systems absorb more routine work, universities must shift from training students to complete tasks toward forming the judgment that tells "a good answer from a vaguely flawed one."
Redesigning the classroom around AI
Provost and Executive Vice President for Academic Affairs Gregory Heileman addressed faculty directly on assessment and literacy. "The genie is out of the bottle," he said, calling efforts to punish students for using AI "a waste of time." The better response, he argued, is to redesign assignments that account for the technology rather than try to ban it.
Heileman said LAU must build foundational AI literacy into every discipline, "so that [faculty] are prepared to critically evaluate, ethically govern, and apply AI within their own specific disciplines." He cautioned against opaque "black box" systems and pushed for open-source tools the university can audit. For educators building these skills, structured pathways like AI for Education courses and certifications offer practical frameworks for integrating AI into curriculum design and assessment strategy.
The disappearing entry-level rung
AI Security Policy Expert at Cisco Tiffany Saade examined what happens when the first rung of the professional ladder vanishes. Entry-level roles are increasingly automated, and she warned that organizations can become more efficient each quarter while becoming less capable each decade. "If you hollow out the bottom of the pyramid, eventually you have to ask who will occupy the top," she said.
Saade argued that AI's greatest risk to graduates is not job loss but a shortcut around the struggle that builds real skill. "A university's most important product is human capability," she said, noting that employers cannot keep automating entry-level work while expecting graduates to arrive with years of judgment already formed.
Operations and the builder's advantage
Vice President for Administration Roy Majdalani turned the discussion to university operations, noting that most institutions now use AI daily but few have designed how people and systems should work together. He called for leaders to "orchestrate intelligence, not just manage people," identifying data literacy, judgment, governance, workflow redesign, and emotional intelligence as priorities.
LAU Engine Director Evan Fakhoury closed the lightning talks by describing how AI has erased the barrier between having an idea and launching a company. "That gap between thinking about something and building something is gone with the help of AI," he said, pointing to LAU-linked founders who used AI tools to build branding, dashboards, and platforms without outside teams. He said the university's job is to give students that same advantage: "We need to give the students the tools to validate the idea, do the deep research, build the prototype, talk to the people, build the company, test it, get the first customer, all with the help of AI."
For faculty looking to equip students with these capabilities, AI for Teachers training offers concrete methods for embedding AI tools into project-based learning and student work, from prototyping to research validation.
Why this matters for educators
The Pulse Exchange surfaced a tension that every institution faces but few name clearly: AI is not a policy problem to solve once. It is a design problem that touches curriculum, assessment, operations, and career readiness simultaneously. For faculty and academic leaders, the immediate takeaway is that banning AI in coursework is already obsolete. The harder work - redesigning assignments, building AI literacy across disciplines, and ensuring students still develop judgment through struggle - is what will determine whether graduates arrive in the workforce with genuine capability or just polished shortcuts.
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