When the Regulator Becomes the Case Study
South Africa’s first binding artificial intelligence policy framework was withdrawn just 16 days after its official gazetting on 10 April 2025, after journalists discovered that its reference list contained fabricated academic sources — non-existent journals and real publications that never carried the cited research. The communications minister confirmed the cause: generative AI had been used in the document’s production without adequate human verification.
The episode is not primarily a story about embarrassment. It is a governance failure with direct implications for how African states build the institutional credibility required to regulate transformative technologies — and for how the continent positions itself within multilateral AI governance frameworks, including the African Union’s emerging digital architecture.
South Africa is a benchmark jurisdiction for the continent. When its Department of Communications and Digital Technologies produces a policy document that violates the accountability, transparency, and explainability standards it proposes to impose on others, the credibility deficit extends beyond Pretoria.
Two Integrity Failures at the Core of the Collapse
The hallucinated citations in the draft policy represent two distinct and compounding failures, according to Tanya de Villiers-Botha, a senior lecturer in cyber law at Stellenbosch University who specializes in AI regulation.
The first is epistemic integrity — the assurance that research underpinning a policy document has been conducted through reliable, ethical, and independently verifiable methods. The second is information integrity — the public’s reasonable expectation that an authoritative state document is grounded in real evidence.
The fabricated sources did not simply invent citations. They manufactured African scholarly authority, attaching respected researchers’ names to work they never produced, and attributed false evidence to institutions recognized as credible academic publishers. This is not a minor citation error. It is a structural compromise of the document’s evidentiary foundation.
AI hallucination — the tendency of generative AI systems to produce content that sounds authoritative but is factually fabricated — is a documented and growing problem. Lawyers in South Africa and internationally have submitted non-existent case law in court pleadings. Academics have published papers listing AI-generated phantom sources. The South African policy failure is the highest-profile instance yet of the problem penetrating executive policymaking.
The Policy’s Own Standards Condemn Its Production Process
The draft framework drew on the OECD AI Principles and the Smart Africa AI Blueprint, both of which establish accountability, transparency, and explainability as non-negotiable governance conditions — not just for AI system designers, but for any institution deploying AI in consequential processes.
On all three counts, the Department of Communications and Digital Technologies has not met the standards its own document would have required of others.
On accountability, the department has yet to provide a comprehensive account of which sections of the policy were materially shaped by fabricated sources, or the full extent to which the document’s analytical foundation is compromised.
On transparency, critical questions remain unanswered: which generative AI tool was used, by whom, at which stage of drafting, and whether AI was deployed to generate the literature review, the foundational values section, the synthesis of public submissions, or all of the above.
On explainability, the public cannot currently trace which policy positions were built on hallucinated evidence. Without a section-by-section disclosure, the normative framework of the revised policy will carry an unresolved credibility gap — one the department created and only the department can close.
Proceeding to revision without meeting these disclosure requirements would replicate the original failure at a deeper institutional level.
Continental Stakes: AI Governance Credibility in a Competitive Regulatory Environment
South Africa’s policy collapse arrives at a moment of intensifying competition among African jurisdictions to establish credible AI governance frameworks. Rwanda and Ghana have both advanced national AI strategies in recent years. The African Union’s Continental AI Strategy, adopted in 2024, establishes a framework that member states are expected to operationalize through domestic legislation and regulatory institutions.
For investors and technology partners evaluating regulatory environments across the continent, institutional credibility is a core variable. A jurisdiction that cannot verify the evidentiary basis of its own policy documents faces a harder task demonstrating the regulatory predictability that long-term technology investment requires.
The Smart Africa Alliance, which coordinates digital transformation policy across 40 member states, has positioned responsible AI as a continental competitiveness issue. The South African episode tests whether that positioning is matched by the institutional discipline required to produce credible governance instruments.
Nigeria, as West Africa’s dominant economy and a major AI investment destination, faces analogous pressures. The National Information Technology Development Agency has moved toward AI governance guidelines, but without the legislative anchoring that would give them binding force. The South African case illustrates what happens when policy ambition outpaces institutional verification capacity — a risk that applies across the region.
Synthetic Media and Information Integrity: The Structural Gap the Revised Policy Must Close
The hallucinated citations are one manifestation of a broader challenge the revised policy must address as a structural priority, not a sectoral afterthought. Generative AI’s capacity to produce fake text is the same underlying capability that produces deepfakes, synthetic voices, fabricated images, and the weaponization of individuals’ likenesses.
These are not problems to be delegated to sector-level regulation at a later stage. They are cross-cutting public trust challenges that require a dedicated regulatory logic — one built on clear definitions, designated mandate holders, agreed remedies, and cross-institutional coordination mechanisms.
South Africa already has regulatory bodies with overlapping jurisdiction over digital content, identity harms, and information distribution. What is absent is an agreed framework that coordinates their mandates specifically around synthetic media and AI-generated misinformation. Establishing that framework does not require new institutions. It requires political will and deliberate policy design — both of which the department has an opportunity to demonstrate through the revision process.
The revised policy should designate a specific institutional mandate holder for synthetic media and information integrity, with defined powers, accountability mechanisms, and cross-sectoral coordination obligations. Treating this as a subcategory of innovation governance would reproduce the structural gap the current failure has exposed.
What the Revision Process Must Deliver
The Department of Communications and Digital Technologies has described the draft as a “point of departure.” That framing is appropriate, but the departure point must be reset on verifiable ground.
Before the revision proceeds, the department should publish a section-by-section account of which parts of the withdrawn policy were affected by hallucinated sources, which AI tool was used and at what stage, and how the evidentiary foundation of the revised document will be independently verified before gazetting.
The institutional credibility of South Africa’s AI governance framework — and its utility as a model for other African jurisdictions navigating the same regulatory terrain — depends on whether the revision process is conducted to a higher standard than the document it replaces.
A state that uses AI to govern AI without adequate oversight has not demonstrated a technical failure. It has demonstrated a governance failure. The distinction matters, because only one of those can be fixed by better prompting.
