Artificial Intelligence has emerged as a defining priority in higher education worldwide. Universities and colleges across the globe are modernizing their curricula by integrating AI into teaching and research to prepare graduates for an increasingly digital economy. Pakistan is moving in the same direction.
Recently, the Chairman of the Higher Education Commission (HEC) Pakistan announced in an official press release that HEC has made a three-credit-hour course on Artificial Intelligence mandatory for undergraduate programs across universities in Pakistan. This policy marks a timely step towards academic transformation and signals that AI is no longer an optional addition to university curricula. Yet, it also raises a critical question:
Who will teach AI?
This question has received remarkably little attention. Academic discussions and policy debates have largely focused on what students should learn, while overlooking the faculty members who are expected to deliver AI-integrated education. Curriculum reform is essential, but without adequately prepared instructors, even the most ambitious AI policies risk falling short in the classroom.
The challenge is not faculty willingness to embrace AI; it is providing them with the opportunity, training, and institutional support to do so.
The Faculty Generation Gap
Most university faculty members today belong to Generation X and Generation Y. They completed their undergraduate, graduate, and doctoral education during a period when deep disciplinary expertise defined academic excellence. Linguists specialised in language and communication, management scholars in organisational behaviour and business, educationists in pedagogy, and historians in historical inquiry. Their expertise was built around their respective disciplines—not Artificial Intelligence. This observation is not a criticism of today's academics. Rather, it reflects the historical evolution of higher education. For much of the 1990s and early 2000s, AI remained a specialized field within Computer Science, Information Technology, and advanced research laboratories. The rapid advances in deep learning during the early 2010s, followed by the emergence of generative AI tools such as ChatGPT in late 2022, transformed AI into a mainstream academic concern. Within only a few years, universities worldwide began integrating AI into disciplines beyond computer science—including law, medicine, education, management, arts, humanities, and the social sciences. The AI transition occurred remarkably quickly. Academic capacity, however, has not evolved at the same pace.
Using AI Is Not the Same as Teaching AI
Universities often assume that disciplinary competence automatically translates into expertise in Artificial Intelligence. It does not. Designing AI-integrated courses requires much more than knowing how to use ChatGPT or other AI tools. Faculty members must understand AI concepts, research methodologies, ethical considerations, assessment frameworks, disciplinary applications, and responsible classroom integration. Such expertise cannot be acquired through occasional webinars, brief online tutorials, or short-term workshops alone. It requires sustained academic engagement, structured professional development, institutional support, and interdisciplinary collaboration.
Nevertheless, universities across disciplines—from languages and literature to sociology, management, and education—are increasingly advertising faculty positions that expect applicants to demonstrate expertise in AI-assisted teaching, AI-supported research, and AI-oriented curriculum development. More importantly, it exposes a widening gap between policy ambitions and institutional preparedness.
The Real Challenge Is Opportunity, Not Willingness
This should not be interpreted as a criticism of current faculty members. Higher education institutions have spent decades encouraging academics to become specialists within their own disciplines because disciplinary depth remains the foundation of credible scholarship. Just as a computer scientist cannot become a philosopher after attending a single conference, a historian cannot become an AI curriculum designer overnight. Expertise develops through years of education, research, practice, and continuous scholarly engagement. The challenge, therefore, is not a lack of willingness. It is a lack of opportunity.
Preparing Faculty for the AI Era
The future of AI in higher education depends less on replacing existing faculty and more on equipping them for the AI era. Artificial Intelligence should complement disciplinary expertise rather than replace it. Every field—from management and education to humanities and the social sciences—can benefit from AI while preserving its intellectual foundations and analytical traditions. Successful integration requires more than revised course outlines or new degree titles. It requires qualified teachers.
Before expecting faculty members to redesign programmes around AI, universities and policymakers must invest in comprehensive faculty development through interdisciplinary collaboration, industry partnerships, structured AI certification programmes, funded research opportunities, and continuous professional learning. Only then can AI become a meaningful educational reform rather than merely another curriculum requirement.