Modern warfare and security operations increasingly rely on advanced technologies to maintain an edge over adversaries, and artificial intelligence stands out as a transformative force in this domain.
Across Africa, where diverse threats ranging from insurgencies and terrorism to border disputes and resource conflicts persist, the adoption of AI offers a pathway to bolster defence capabilities without solely depending on traditional manpower or imported hardware. This integration involves leveraging algorithms for data analysis, autonomous systems for surveillance, and predictive models for strategic planning, all tailored to the continent’s unique geopolitical and environmental challenges. As African nations grapple with limited resources and evolving threats, AI emerges as a tool to enhance operational efficiency, though its deployment requires careful navigation of technical and ethical hurdles.
The push for AI in African defence begins with the development of structured policies at both national and continental levels. The African Union has taken a leading role by formulating a Continental AI Strategy set for implementation from 2025 to 2030, aiming to guide member states in harnessing AI for inclusive growth while addressing security implications. This framework emphasises ethical use, data governance, and collaboration to prevent misuse, such as by terrorist groups employing AI for propaganda or disinformation campaigns. At the national level, countries like Kenya have unveiled comprehensive strategies, with its National Artificial Intelligence Strategy for 2025-2030 outlining visions for government-led AI adoption in sectors including security. Similarly, at least eight African nations, including Egypt, Mauritius, and Rwanda, have adopted formal AI policies, while others like Nigeria and South Africa are in advanced drafting stages. ECOWAS is also considering integrating AI to improve regional security. These initiatives reflect a recognition that AI can shift defence paradigms from reactive to proactive measures, enabling forces to anticipate threats through data-driven insights.
In practical terms, AI integration is most prominent in surveillance and intelligence gathering, areas where African militaries often face vast terrains and porous borders. For instance, AI-powered drones equipped with computer vision algorithms can monitor expansive regions in real time, identifying anomalies such as unauthorised movements or poaching activities. In Cameroon, Gabon, and Nigeria, security forces have deployed cameras and motion sensors integrated with AI models to combat wildlife trafficking, such as the poaching of pangolins, by analysing patterns and alerting rangers to potential incursions. This application extends to broader military contexts; South African forces utilise similar drone systems to track environmental threats like invasive weeds, which indirectly supports logistical operations by maintaining clear supply routes. Beyond aerial platforms, ground-based AI systems process satellite imagery and social media feeds to detect insurgent activities, a capability that proved vital in countering Boko Haram in Nigeria’s northeast, where predictive analytics helped forecast attack patterns based on historical data and environmental variables.
Another key area involves predictive maintenance and logistics optimisation, where AI algorithms analyse equipment data to foresee failures and streamline supply chains. African defence forces often operate with ageing fleets acquired through second-hand deals, making downtime a critical vulnerability. By employing machine learning models, militaries can extend the lifespan of assets like armoured vehicles or aircraft; for example, Egypt’s air force has begun incorporating AI tools to monitor engine performance in its fighter jets, reducing unscheduled repairs by up to 30 per cent in pilot programs. This not only conserves budgets strained by foreign exchange constraints but also ensures higher readiness levels during operations. In Algeria, similar systems are being tested for tank fleets, where AI predicts wear on tracks and turrets based on usage data from desert manoeuvres, allowing for preemptive interventions that minimise operational disruptions.
Counter-terrorism represents perhaps the most urgent application, given the prevalence of groups like Al-Shabaab in East Africa and ISIS affiliates in the Sahel. AI excels in sifting through vast datasets to identify threats, such as analysing communication patterns or financial transactions to preempt attacks. The African Union’s strategy specifically addresses this by guiding counter-terrorism efforts against AI misuse by extremists, who have started generating propaganda videos with deepfake technology to sow discord. A real-world instance comes from Morocco, where AI-integrated systems enhance border security through facial recognition and anomaly detection at checkpoints, thwarting smuggling networks linked to terrorist financing. In Libya, during recent conflicts, autonomous drones reportedly engaged targets with minimal human oversight, marking an early foray into lethal autonomous weapons systems on the continent, though this raised concerns about accountability. Such deployments illustrate AI’s potential to amplify force multipliers in asymmetric warfare, where outnumbered troops can leverage technology for superior situational awareness.
The benefits of this integration extend beyond tactical gains to strategic advantages that align with Africa’s broader development goals. By reducing reliance on human-intensive operations, AI allows defence budgets to stretch further, freeing resources for training or infrastructure. In resource-rich nations like the Democratic Republic of Congo, AI-driven geospatial analysis helps secure mining sites from rebel incursions by predicting raid probabilities based on seasonal patterns and intelligence reports. Moreover, AI fosters intra-African collaboration; shared platforms for threat intelligence could enable joint operations under frameworks like the African Standby Force, where real-time data sharing enhances collective response times. Economically, local AI development creates jobs in the tech sector, as seen in Rwanda’s investments in AI hubs that support both military and civilian applications, thereby building a skilled workforce that contributes to national resilience.
Yet, the path to effective AI integration is fraught with obstacles that demand proactive mitigation. Infrastructure deficits pose a primary barrier; many African countries lack reliable electricity, high-speed internet, or data centres needed for AI training and deployment. In rural conflict zones, such as those in the Sahel, inconsistent power supplies can render AI systems inoperable, forcing a fallback to manual methods. Skills shortages compound this issue, with a dearth of trained personnel in machine learning and cybersecurity; estimates suggest Africa needs millions more digital experts to fully capitalise on AI. Ethical dilemmas also loom large, particularly around autonomous weapons that might make life-or-death decisions without human input, risking violations of international humanitarian law. The potential for AI to exacerbate inequalities arises if wealthier nations like South Africa dominate the technology, leaving poorer states vulnerable to cyber exploits or biased algorithms trained on unrepresentative data.
Geopolitical risks further complicate adoption, as reliance on foreign AI providers—often from China, the United States, or Europe—could introduce backdoors or data sovereignty issues. Terrorist groups adapting AI for their purposes, such as using chatbots for recruitment or drones for attacks, adds another layer of urgency to developing robust defences. To address these, African leaders advocate for regional capacity building, including AI safety hubs to train experts and standardise regulations. The African Union’s Peace and Security Council has emphasised incorporating AI into governance strategies to promote sustainable development, urging member states to prioritise human oversight in military applications.
Looking ahead, the future of AI in African defence hinges on balanced innovation that prioritises inclusivity and oversight. Projections indicate that by 2030, AI could contribute substantially to peacekeeping missions, with early warning systems analysing social media and satellite data to prevent escalations in hotspots like Somalia or Mali. Hybrid models combining AI with human judgment will likely dominate, as seen in emerging projects where algorithms assist in scenario simulations for officer training. For instance, in Kenya, future strategies envision AI optimising resource allocation during humanitarian crises intertwined with security operations, such as flood responses in volatile regions. To realise this potential, investments in education and partnerships with global tech firms must accelerate, ensuring AI serves as a force for stability rather than division. As the continent advances, a unified approach will not only strengthen individual militaries but also position Africa as a proactive player in global security dialogues.
