Artificial intelligence has grown significantly over time and has slowly reshaped various industries. Therefore, the perception of careers is also increasingly changing to match the needs of today’s world. With the integration of AI in most industries, higher education systems will need to change or improve to keep pace with current changes.
Previously, universities prepared students for the workforce. However, now, new career fields are gradually opening up due to the automation and efficiency of work using AI. Students need to prepare for the future. These days, employers are also looking for professionals who understand not only business principles but also how to apply AI to solve complex problems.
The demand for AI skills is rapidly increasing. These days, most job postings are looking for AI-related skills, as employers are looking for graduates who can work alongside AI technology, rather than competing with it. One can only imagine the pressure on universities to redesign their curricula to better prepare students for an AI-enabled workplace.
It is time for universities, colleges, and training institutes to teach AI concepts at their core, rather than adopting AI tools as finished products. Assignments must be redesigned so that AI serves as a starting point for analysis rather than a shortcut to a finished product. Continued investment in faculty development is also needed to ensure that AI implementation is done in the right way.
Changes to academic integrity policies are also needed. Because those policies were previously designed for a pre-AI world. Universities need guidance that is specific enough to use, yet flexible enough to revisit as tools change. Course-level AI statements must be set by the instructor to prevent violations. We need advance warning and policy implementation, rather than flagging it after completion.
Digital and AI literacy should be treated as a campus-wide competency, rather than a computer science-specific skill. All students, staff, and faculty in all disciplines need to understand how these systems work and where failures occur. AI literacy is something we build and distribute, not just discuss.
A good example is MIT, which has an open learning department that launched Universal AI. It is a free, modular program that takes learners from the basics of AI to industry-specific applications, with the help of more than 30 faculty across the Institute. There’s also MIT Sloan, which runs a dedicated resource hub that provides faculty with discipline-specific guidance rather than general rules. The RAISE initiative focuses on AI literacy for K-12 students and educators.
Another good example is Yale University, which combines large-scale investments with decentralized policies. For example, Yale University has committed more than $150 million over five years to computing infrastructure, secure AI tools, faculty hiring, and interdisciplinary research grants. On the policy side, classroom AI policy is left up to individual instructors rather than issuing one rule for the entire campus, which is very helpful. Instructors can adapt AI policies to their courses.
Arizona State University is another university that offers the most aggressive model of campus-wide implementation. For example, in 2024, we became the first university to form an institutional partnership with OpenAI. By late 2025, we expanded that agreement to provide all students, faculty, and staff with free access to ChatGPT Edu at no personal cost. Additionally, we invited faculty and staff to submit suggestions on how AI can support teaching, research, and daily work. This approach, combined with an ethics committee and ongoing training to manage the pace of change, generated project submissions from over 80% of schools and universities within weeks.
Other leading examples include Harvard University, which is expanding interdisciplinary AI research across medicine, business, engineering, and public policy. Meanwhile, Princeton University has established a dedicated AI research initiative to advance the responsible use of AI, ensuring that it is used in an appropriate manner with maximum compliance and that it keeps up with the pace. The University of Pennsylvania launched Penn AI to connect all 12 schools and increase research visibility through collaborative research and education. Cornell University also continues to expand its AI innovations through the Cornell Tech Campus.
Universities in Pakistan face greater opportunities since the approval of the National AI Policy in 2025. This National AI Policy was built around a National AI Fund, a network of AI Centers of Excellence, and ambitious human capital goals that include training 1 million learners and 10,000 new trainers by 2027. However, despite this, a policy vacuum exists where appropriate policies have not been put in place regarding the use of AI in educational institutions in everyday use. What is needed is guidance on its use so that instructors can ask if learners are violating the terms of use when working on assignments, projects, etc.
In Pakistan, a notification has been issued by the Higher Education Commission for a 3 credit hour AI course to be compulsory for all undergraduate and postgraduate degree programs in universities. Universities have the flexibility to offer it as an elective interdisciplinary course or as a supplementary subject integrated into an existing program. However, the content is stipulated.
Pakistan has steadily moved from policy consultations to actual curriculum mandates, testing the course-level flexibility model adopted by Yale University and leaving the definition of outcomes to individual institutions and instructors.
Additionally, thousands of instructors across the country are expected to teach AI-related content, but they have no formal training in this area. Universities therefore need to invest in developing the knowledge, confidence and teaching abilities of their faculty.
Despite the increasing use of AI by students and faculty in teaching, learning, and research, most universities have not established clear guidance on its use. This helps instructors deal with any kind of violations related to assignments, projects, and assessments.
To ensure successful adoption of AI, higher education institutions should focus on several strategic priorities. First, universities must develop comprehensive AI policies that define acceptable uses of AI in teaching, learning, research, and assessment.
Second, teachers need to be trained to have the relevant knowledge to teach students. You’ll also learn how to redesign curriculum, assessment, and classroom practices to fit your learning environment. Third, universities should establish AI innovation and education centers to support AI adoption. This is very important and will also help foster innovation.
Fortunately, Pakistani universities do not need to create a strategy from scratch. You can borrow university models from MIT, Yale, Harvard, Princeton, Cornell, the University of Pennsylvania, and ASU to fit your local constraints without requiring a huge budget. However, AI literacy training for teachers will likely be needed before making anything mandatory in the classroom. Universities are responding at an unprecedented pace. Over the past two years, hundreds of higher education institutions around the world have implemented AI policies, launched AI literacy initiatives, and developed new AI degree programs.
The author is the author of “Digital Pakistan” and holds the position of Chief Digital Officer and Director at the Center for Information and Communication Technology, IoBM. He tweets/posts @imranbatada and can be reached at: [email protected]
