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Why Africa can no longer ignore the Rise of AI Performance Risk

ARTICLE BY

  • Justin Naylor
  • CEO
  • iTOO Special Risks

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Artificial intelligence (AI) has moved far beyond the realm of experimentation. Across South Africa and the wider continent, AI is now embedded in financial systems, logistics networks, agricultural platforms, enterprise automation and customer‑facing services. It is making (or helping to make) decisions that carry real financial, operational and societal consequences. Yet as adoption accelerates, a new category of risk is emerging: that of AI itself failing.

This is not the familiar territory of cyberattacks, ransomware or data breaches, but something more subtle, more complex and arguably more consequential. AI systems can ‘hallucinate’, misclassify or generate inaccurate outputs, even when functioning as designed. These failures are not malicious. They are intrinsic to how machine‑learning models work. And they are becoming impossible for African businesses to ignore.

The rise of agentic AI and the risks it brings

The continent is experiencing a rapid shift towards autonomous and semi‑autonomous AI systems. Banks are deploying machine‑learning models to detect fraud and assess creditworthiness. Retailers are using AI to forecast demand and optimise supply chains.  Farmers are adopting AI‑driven tools to determine soil inputs, irrigation cycles and pest‑control strategies. Governments are exploring AI for service delivery, identity verification and  infrastructure planning.

These systems are powerful, but they are also probabilistic. They do not behave like traditional software, which produces the same output from the same input every time. AI is not like traditional software, and it does not always produce the same output from the same input. Even the most advanced models carry a measurable error rate.

When AI is used for low‑stakes tasks, these errors are manageable. But when AI is entrusted with high‑stakes, autonomous decision‑making — such as approving transactions, classifying risk and allocating resources — the consequences of an incorrect output can be severe.

Consider a fraud‑detection model that incorrectly approves a fraudulent transaction. Or a credit‑scoring engine that misclassifies a high‑risk customer as low‑risk. Or an agricultural AI system that recommends the wrong fertiliser mix, damaging crops and livelihoods. These are not cyber incidents. They are performance failures of the AI itself. And until recently, they were largely uninsurable.

Why traditional insurance models fall short

African organisations have long relied on cyber insurance, professional indemnity cover and operational risk policies to protect themselves. But these frameworks were built for a world in which humans, not algorithms, made the critical decisions. Cyber insurance responds to malicious attacks.

Professional indemnity responds when a human professional makes an error. Neither is designed for a scenario in which an autonomous AI system, acting without human oversight, makes a statistically incorrect decision that causes financial loss.

If a human is still reviewing or approving the AI’s output, then that falls under professional indemnity. But when an AI model is left to make critical decisions on its own, that is where this product becomes essential. This gap has become increasingly visible as African enterprises push deeper into automation. The continent’s regulatory frameworks are still evolving, and many organisations are deploying AI faster than governance structures can keep up. The result is a widening exposure that traditional insurance cannot absorb.

Why AI performance insurance is emerging now

The timing is not accidental. South Africa, in particular, is experiencing a surge in AI adoption across both enterprise and developer ecosystems. AI is the buzzword in every boardroom right now. Companies want to experiment, automate and innovate — but they also want assurance.

Three forces are driving the need for AI performance insurance:

  • The proliferation of agentic AI: Businesses are increasingly comfortable allowing AI to operate This shift from decision‑support to decision‑making fundamentally changes the risk landscape.
  • The rise of African AI developers: South Africa is home to a growing community of software developers and AI startups. Many are building models for banks, insurers, retailers and agricultural platforms. Yet proving performance upfront is difficult, and buyers are understandably cautious.
  • The regulatory lag: AI governance frameworks across Africa are still in development. Until they mature, organisations need alternative mechanisms to manage uncertainty.

A catalyst for Africa’s AI future

Insurance has historically enabled technological progress, from industrialisation to aviation to large‑scale infrastructure. AI is no different. Insurance has always enabled progress by absorbing risk.

Africa is entering a new era in which AI will increasingly operate without human oversight. This brings enormous opportunity but also new forms of risk. Thus, AI performance insurance is not a luxury; it is a foundational tool for a future in which algorithms play a central role in economic and social systems.

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