Reimagining higher education for AI

Artificial intelligence has grown tremendously over time, slowly reshaping various industries. Therefore, even the perception of careers is increasingly changing to meet the current world’s needs. With the integration of AI in most industries, there is a need to change or improve the higher education system to comply with the current changes.

Previously, colleges and universities prepared students for the workforce; however, now, with AI automating tasks and streamlining operations, it is slowly opening new career fields. Students should be made future-ready. Nowadays, even employers are seeking professionals who not only understand business principles but also how to apply AI to solve complex problems.

The demand for AI skills is growing rapidly. These days, most job postings require AI-related skills as employers seek graduates who can work alongside AI technologies rather than compete with them. You can only imagine the pressure on universities to redesign curricula so that students are well equipped for AI-enabled workplaces.

It is high time universities, colleges and training institutions teach the concepts of AI at the core rather than just adopting AI tools as finished products. There is a need to redesign assignments so that AI serves as a starting point for analysis rather than a shortcut to a finished product. There is also a need for sustained investment in faculty development to ensure AI adoption is done in the right way.

A shift in academic integrity policies is necessary, too, since they were previously designed for a pre-AI world, and universities need guidance that is specific enough to be usable yet flexible enough to be revisited as tools change. Course-level AI statements need to be set by the instructors to ensure that no violation occurs. Rather than flagging it once it is done, prior warning or policy implementation needs to be there.

Digital and AI literacy needs to be treated as a campus-wide competency, not a specialised skill for computer science; all students, staff and faculty across every discipline need to understand how these systems function and where they fail. AI literacy is something to build and distribute rather than just discuss.

A good example is MIT, which has an Open Learning division that launched Universal AI, which is a free modular programme that takes learners from AI basics to industry-specific applications with contributions from more than 30 faculty members across the institute. There is also MIT Sloan, which runs a dedicated resource hub that provides faculty with discipline-specific guidance rather than generic rules. The RAISE initiative then focuses on AI literacy for K-12 students & educators.

Another good example is Yale, which is pairing major investment with decentralised policy. For instance, Yale University committed more than $150 million over five years towards compute infrastructure, secure AI tools, faculty hires and interdisciplinary research grants. On the policy side, the classroom AI policy is left for the individual instructors rather than issuing one campuswide rule, which is really helpful. Instructors can adapt the AI policy to their own courses.

Arizona State University is another one that offers the most aggressive model of campus-wide adoption. For instance, in 2024, it became the first university to strike an institutional partnership with OpenAI. By late 2025, it had expanded that deal to give every student, faculty member, and staff member free access to ChatGPT Edu at no individual cost. Additionally, they invited the faculty and staff to submit proposals on how AI could support teaching, research, or daily operations, an approach that generated project submissions from more than 80 per cent of its schools and colleges within weeks, paired with an ethics committee and ongoing training to manage the pace of change.

Other key examples include Harvard University, which has expanded interdisciplinary AI research across medicine, business, engineering, and public policy. On the other hand, Princeton University has established dedicated AI research initiatives to advance responsible AI use to ensure it is used in the right way with utmost compliance, plus keep up with the pace. The University of Pennsylvania has launched Penn AI to connect all 12 schools through collaborative research and education and to enhance the visibility of research, and Cornell University continues to expand AI innovation through its Cornell Tech campus.

Universities in Pakistan face a bigger opportunity, since in 2025, the National AI policy was approved, which was built around a national AI fund, a network of AI centres of excellence and ambitious human capital targets, including training a million learners and ten thousand new trainers by 2027. However, even with that, there is a policy vacuum in which the right policies haven’t been put in place regarding the use of AI in institutions, which is used daily. What is needed is guidance on its use so that instructors can question learners if they violate the usage terms while working on assignments, projects, and more.

In Pakistan, a notification was issued by the Higher Education Commission regarding the three-credit-hour AI course, which is mandatory in all undergraduate and postgraduate degree programmes in universities. Universities have the flexibility to deliver it as an elective interdisciplinary course or as a supporting subject embedded within existing programmes. However, the content is prescribed.

Pakistan is surely moving from policy talk to an actual curriculum mandate, and it validated the course-level flexibility model that Yale uses, prescribing outcomes while leaving delivery to individual institutions and instructors.

Also, thousands of instructors across the country are expected to teach AI-related content, yet they haven’t gotten the formal training in the subject. Therefore, universities need to invest in developing knowledge, confidence and teaching capabilities in the faculty.

Even with how AI is increasingly being used by students and faculty in teaching, learning and research, most universities are yet to establish clear guidance pertaining its use. This will help instructors to address all types of violations related to assignments, projects and assessments.

To ensure proper AI adoption, higher education institutions should focus on a few strategic priorities. First, each university should develop a comprehensive AI policy that defines the acceptable use of AI in teaching, learning, research and assessment.

Second, the faculty need to be trained so they have relevant knowledge to teach students. Also, they will know how to redesign the curricula, assessments and classroom practices for the learning environment. Third, universities should establish AI innovation and teaching centres that will support AI adoption. In a huge way, this will also help to boost innovations.

Luckily, Pakistani universities don’t need to invent the playbook from scratch. They can borrow from MIT, Yale, Harvard, Princeton, Cornell, Pennsylvania and ASU university models that fit their local constraints without needing huge budgets. However, there will be a need for AI literacy training for faculty before mandating anything in the classroom. Universities are responding at an unprecedented pace. Hundreds of higher education institutions worldwide have introduced AI policies, launched AI literacy initiatives, or developed new AI degree programmes over the last two years.