Dr Fazal Ali
Ivy League universities are asking themselves: what value will graduates bring to the workplace that AI cannot provide? Firms and bureaucracies are asking: What would a work environment saturated with frontier AI models require of the university graduate?
The university is in ruins. In its pursuit of bureaucratic “excellence”, the university shifted from a cultural institution that builds national identity to a profit-driven corporation.
“Excellence” replaced culture as the primary goal. Universities have not always been bureaucratic systems. Once, the idea of the University was accorded the kind of referential value that “excellence” lacks.
The appeal to excellence arose when the nation-state ceased to be capitalism’s elemental unit. In that moment, rather than states striving to exemplify capitalism, capitalism engulfed the nation-state. To understand this enigma, one need only reflect on the idea that FIFA has more member associations than the United Nations has sovereign member states.
Specifically, FIFA counts 211 national member associations, whereas the United Nations recognises 193 member states. Now, in a daze, we gaze at the spectre of AI cavorting like a Moko Jumbie among the ruins and in the cloud.
With great expectations, graduates set out to find a job. But work finds the skill it needs on its own. Moreover, unbeknownst to job-evaluation committees and HR departments, AI has already edited every job description. This invisible rewrite has caused an “authenticity gap”. This is precisely why highly selective institutions have set out to AI-proof their graduates.
Universities are in dialogue with management consulting firms and executives at mega caps about how to graduate workers who are essentially AI-proof. They are now focusing on two main areas:
(1) enabling all students to achieve AI fluency, and
(2) aligning academic offerings with the realities of AI-enabled roles.
They are recalibrating how they are preparing students from induction to graduation. A cloud now hangs over coursework and the use of AI. Universities must decide how to include AI chatbot outputs as appendices and how to vet bibliographies for hallucinated citations.
Can the use of Turnitin and Quetext to generate AI-content detection reports empower students to develop the AI-literacy, social skills, critical thinking, and cognitive capabilities that the AI-thick workplace expects?
Universities are already responding to the local context of Municipal Corporations by sourcing data that highlight the specific skills for SMEs and then mapping those needs against student skill sets. Local Economic Development Units (LEDs) can now identify emerging and existing market opportunities for SMEs to overcome trade barriers and expand their businesses across creative screen economies.
Institutions now pair students with SMEs that wish to get more value from their data sets. SMEs submit data-intensive projects to higher education institutions while committing to mentoring students. Students help solve real-world problems, and universities create a pipeline of data-fluent graduates with expertise.
SMEs lack the scale to invest in AI capabilities and training and are less likely to have structured internship programs. Universities now have a role to find frictionless ways to partner with LEDs and SMEs.
AI is accelerating, and that acceleration is accelerating. Universities need to make sure the partnerships they forge are developing equally fast. The scale of change required needs more than pilots.
Once, universities relied on traditions of intellectual self-formation and world-class faculty that allow students to develop intellectual independence, ethical reasoning, critical thinking, and a core curriculum requiring students to debate foundational texts in philosophy and society.
With the “AI-Bend in the River” ahead, they are now inserting guidelines on the curated use of tools and technologies that use AI.
Faculty are now allowed to create ideographic AI policy prescriptions for individual courses. Blanket policy prescriptions form an umbrella framework.
Some law schools now prohibit students from using AI to draft, frame arguments, and edit coursework. The expectation is that classroom time be used to engage students in sustained and rigorous dialogue that minimises distractions from screens.
Others are banning laptops, tablets and phones in the classroom for first-year law students as part of their broader strategy of graduating AI-proof workers. This prohibition aims to prevent generative AI from undermining the Socratic method.
Students reading courses in legal research and writing are expected to compose arguments without AI. Other students are permitted to use AI for research and preparing oral arguments, with faculty providing feedback. This approach allows learners to nurture their own writing skills independent of generative AI tools while also developing their ability to supervise AI and critique its output.
In July 2026, the creators of ChatGPT were engaged in a controlled test of the capabilities of its most advanced AI models. The agent escaped containment, reached the internet and broke into Hugging Face to fulfil its testing objective. This is a warning sign that confirms our worst fears.
Dr Fazal Ali completed his Master's in Philosophy at the University of the West Indies. He was a Commonwealth Scholar who attended the University of Cambridge, Hughes Hall; the Provost of the University of Trinidad and Tobago; the acting President of UTT; and the Chairman of the Teaching Service Commission. He is the President of NIHERST and an external services consultant with the IDB.
