HEC makes AI course mandatory from 2026: What educators need to do now
The Higher Education Commission of Pakistan (HEC) has mandated a three-credit AI course for all undergraduate and postgraduate programmes starting in 2026. The directive covers public and private universities and calls for immediate integration into curricula.
HEC's message is clear: AI literacy is no longer optional. Every student should leave with practical skills and a working grasp of how AI applies to their field.
What the directive requires
- Three-credit AI course required for all degree programmes (BS to PhD equivalent).
- May be offered as an elective, interdisciplinary, or supporting subject within each programme.
- Curricula must combine theory with hands-on application relevant to each discipline.
- Universities should begin implementation immediately and monitor quality standards.
HEC also flagged the need for faculty training and updated teaching resources to deliver effective instruction across departments.
Core outcomes to build into your course
- Practical problem-solving with AI tools and methods.
- Data literacy and basic analysis workflows used in research and industry.
- Ethical use of AI, including bias, privacy, transparency, and accountability.
- Field-specific applications (e.g., diagnosis support in healthcare, fraud detection in finance, decision support in engineering, learning analytics in education).
Integration strategies by programme
- Engineering and CS: Intro to machine learning concepts, Python-based labs, model evaluation, and deployment basics.
- Business and Finance: Forecasting, credit risk scoring basics, automation for reporting, and model risk awareness.
- Health Sciences: Clinical decision support use-cases, data quality, safety, and ethics in sensitive contexts.
- Social Sciences and Education: Qualitative + quantitative analysis with AI tools, survey augmentation, and policy implications.
- Arts and Media: Generative tools, authorship and copyright, and responsible production workflows.
Implementation checklist for deans, HoDs, and QA teams
- Define programme-level learning outcomes that map to AI competencies and your accreditation standards.
- Choose the course slot (elective/interdisciplinary/supporting) and confirm credit mapping.
- Co-develop syllabi with cross-department input to ensure relevance for each field.
- Adopt a common assessment framework: projects, case studies, labs, and an ethics component.
- Secure computing access (lab PCs or cloud credits) and a policy for tool usage.
- Set up a faculty upskilling plan and teaching resources hub.
- Establish monitoring: student feedback loops, course review each semester, and QA audits.
Faculty development and resources
Invest early in staff training. Most shortcomings in new courses come from uneven instructor readiness and lack of shared materials.
- Create a cross-campus teaching team and a shared repository of slides, labs, datasets, and rubrics.
- Run short bootcamps before semester start; pair new instructors with mentors for the first delivery.
- Align ethics teaching across departments to keep policies consistent.
For practical guidance on course design and classroom rollout, see the AI Learning Path for Teachers and programme-level ideas under AI for Education.
Quality assurance and student impact
HEC expects institutions to move fast and maintain standards. Track student outcomes across problem-solving, data work, and ethical decision-making, then adjust content each term.
Graduates who complete this course will be better prepared for research, internships, and roles that expect AI fluency. This directly supports employability and stronger academic performance across disciplines.
Why this matters
AI is now baked into work across healthcare, finance, engineering, and education. Treat this course as core infrastructure for your university: consistent, practical, and tied to real use-cases.
For official updates and guidance, visit the Higher Education Commission of Pakistan.
Next steps (start this week)
- Appoint a coordinator and assemble a cross-department taskforce.
- Approve a baseline syllabus and field-specific modules.
- Book faculty training dates and finalize computing access.
- Publish a one-page student brief explaining objectives, tools, and assessment.
Move now, iterate quickly, and keep the course anchored to real problems your students will face after graduation.
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