Dervin K. Cochrane

BEYOND THE ACCREDITATION WALL

Artificial Intelligence, Governance and the Future of Quality Assurance in the Global South

Dervin K. Cochrane¹

Can artificial intelligence transform accreditation in the Global South from a periodic, compliance-driven exercise into a more transparent, continuous and integrity-focused system of higher-education governance? This paper addresses this question by examining the emerging role of artificial intelligence (AI) and digital technologies in accreditation against the structural vulnerabilities that characterize quality-assurance systems in Jamaica, the Caribbean and the wider Global South. Drawing on my recent broader interdisciplinary book chapter on accreditation, governance and AI, the paper argues that accreditation should not be understood merely as a technical mechanism for verifying institutional quality. It also operates as a system of governance, legitimacy and power. Yet its dependence on periodic reviews, institutional self-reporting, documentary evidence and centralized decision-making can create opportunities for symbolic compliance, data manipulation, regulatory capture and other forms of institutional gaming. These vulnerabilities are conceptualized through the “Accreditation Wall”: the assumption that formal accreditation procedures constitute an effective barrier against institutional failure and misconduct, even when actors may circumvent the safeguards themselves. The paper argues that Artificial Intelligence (AI) creates an opportunity to reconceptualize this model. AI-assisted anomaly detection, continuous data analysis, digital credential verification and real-time monitoring could enable accreditation systems to move beyond episodic procedural compliance towards more dynamic forms of institutional accountability. For resource-constrained systems in the Global South, these technologies could potentially strengthen regulatory capacity while improving transparency and the early detection of irregularities. However, technological adoption does not automatically produce better governance. Artificial Intelligence (AI) may reproduce existing inequalities and introduce new problems involving algorithmic bias, data governance, technological dependency, institutional capacity and accountability for automated decisions. The paper therefore rejects both technological determinism and the assumption that Artificial Intelligence (AI) can substitute for professional judgement. It concludes that the central question for the Global South is not simply whether AI should be incorporated into accreditation, but how AI can be governed so that it strengthens rather than reproduces the weaknesses of existing accreditation systems? A future accreditation architecture should consequently combine technological innovation with human oversight, transparency, contextual relevance, institutional integrity and social justice.