Africa faces a growing risk of being left behind in the global artificial intelligence (AI) revolution as adoption surges in wealthier regions, according to the International AI Safety Report 2026, which paints a stark picture of widening digital and economic divides.
The report finds that general-purpose AI systems capable of performing a wide range of tasks such as writing, coding and data analysis is spreading faster than previous technologies like the personal computer and the internet. An estimated 700 million people worldwide now use leading AI systems every week, with some countries recording usage rates above 50% of their working-age populations.
Yet this rapid uptake is highly uneven. While parts of Europe, North America and selected Middle Eastern and Asian economies dominate adoption, much of Africa remains on the margins. The report estimates that across large parts of Africa, Asia and Latin America, AI usage likely remains below 10% of the population placing the continent among the lowest-adoption regions globally.
This gap matters. The report warns that countries with strong digital infrastructure and skilled workforces are positioned to capture AI’s productivity gains first, potentially accelerating their economic growth while low-income regions lag further behind. One study cited in the report suggests that AI’s impact on economic growth in advanced economies could be more than double that in low-income countries, raising concerns that AI may deepen income and wealth inequality both within and between nations.
For Africa, the challenge is not only access to technology but also readiness. The report highlights structural barriers that constrain adoption across the Global South, including limited computing infrastructure, shortages of specialised skills, and institutional capacity gaps. As a result, African economies risk becoming passive consumers of AI products developed elsewhere rather than active participants in shaping and benefiting from the technology.
At the same time, AI’s advance is bringing new security pressures. The report documents growing evidence that AI systems are already being used in real-world cyberattacks, with malicious actors and state-linked groups employing AI tools to support cyber operations. Against this backdrop, Africa also registers lower confidence in preparedness for major cyber incidents affecting critical infrastructure, compared with Europe and North America — a vulnerability that could become more pronounced as AI capabilities expand.
While AI promises productivity gains — studies show improvements of between 15% and 60% for certain tasks — the labour market effects are complex. Early evidence from higher-income countries suggests that junior and early-career workers are most exposed to disruption, as routine and easily substitutable tasks become automated. The report cautions that once adoption accelerates in emerging economies, countries without strong retraining systems may struggle to help workers adapt to rapidly changing skill demands.
Crucially, the authors note that data on AI deployment and impacts in Africa remains limited, making it harder for policymakers to design evidence-based responses. The report calls for more region-specific research, warning that gaps in knowledge are greatest in rapidly digitising regions such as Africa and Latin America.
Beyond economics and jobs, the report also flags rising global risks linked to advanced AI, including concerns about misuse in biological research and the growing difficulty of reliably testing models for dangerous capabilities before deployment. Although major AI companies have begun publishing voluntary safety frameworks, global risk-management systems are still described as immature, with significant evidence gaps and uneven governance.
For Africa, these trends underline a dual challenge: avoiding exclusion from AI-driven growth while strengthening safeguards against emerging digital threats.
The report stresses that for the Global South, AI safety is inseparable from inclusion. Fair access to computing resources and data, responsible openness of AI models, and stronger international cooperation are identified as essential if developing regions are to participate meaningfully in the AI economy rather than fall further behind it.
