Rethinking assessment when AI is always available
The case for rethinking university assessments in the age of AI is straightforward. If AI can produce a competent essay or solve a take-home problem, the final submission no longer provides sufficient evidence of learning. AI-assisted projects can be combined with oral defense, live problem-solving or staged drafts requiring students to explain what they accepted, rejected and verified. Academic integrity and generative AI are therefore better understood through intellectual ownership: students remain responsible for framing the problem, interpreting evidence and defending their conclusions, even when AI assists with the work.
Why access alone cannot close the gap
Students with strong foundations can use AI to challenge assumptions because they can judge its responses; those with weaker foundations may accept plausible but incorrect answers. Device access, connectivity, language proficiency and faculty support compound these differences. Preventing AI from widening educational inequality in India requires more than providing tools: equal access does not create equal educational opportunity.
What institutions need to put in place
Effective AI governance in higher education requires oversight of data, approved applications and consequential decisions. As AI enters tutoring, assessment and admissions, safeguards for brainstorming cannot be the same as those for grading or scholarship allocation. An AI governance framework for higher education institutions must distinguish levels of risk, establish clear accountability and retain human oversight where decisions affect students.
Moving from adoption to implementation
Students need to verify claims rather than outsource reasoning; faculty need incentives to redesign teaching; administrators need workable governance; and employers can contribute through applied assessments. At India’s scale, shared tools, governance templates and faculty-development resources could help less-resourced institutions build these capabilities.
The next stage of AI in higher education will be determined less by which institutions deploy the most tools than by which ones improve learning while preserving judgement, accountability and equitable access. India’s opportunity is not simply to create a handful of AI-leading universities, but to extend those benefits to the median student, faculty member and institution.
