Essay

Advocates of compulsory generative AI argue that universities must prepare students for workplaces where AI-assisted drafting, coding and data analysis are routine. Requiring its use would also reduce inequality: some students already benefit from private tools and coaching, while others avoid AI through uncertainty or fear of penalties. If everyone must document prompts and edits, assessment can shift from the final product to decision-making, verification and reflection. Supporters claim this approach promotes academic integrity by making AI use transparent rather than hidden, and helps staff teach critical evaluation of outputs, including bias and factual errors.

Critics warn that making generative AI compulsory confuses employability with education. Universities should develop independent thinking, not outsource it. Mandating AI may encourage superficial engagement, as students accept plausible-sounding text instead of wrestling with difficult concepts. There are also practical obstacles: tools vary in quality, cost and privacy standards, and some disciplines rely on personal voice or creative risk-taking. Policing ‘responsible’ use could become bureaucratic, with students producing performative prompt logs. Rather than forcing AI into every assignment, the better strategy is to design assessments where its value is limited and to teach optional, carefully framed use.