Africa’s security crisis is worsening, with conflicts, terrorism, and forced displacements escalating. The Sahel Region has become a global epicenter of terrorism, while Sudan’s conflict created the largest displacement crisis in the world, with over 11 million people forced to flee. In the Democratic Republic of Congo (DRC), the M23 insurgency continues to destabilize the eastern part of the country.
Civilians are paying a heavy price with families torn apart, livelihoods destroyed, and access to essential services disrupted. Poor border control, slow intelligence responses, and ineffective crisis management have made matters worse. Artificial intelligence (AI) offers a path forward by enhancing intelligence gathering, strengthening border security, and improving humanitarian crisis response.
Terrorist groups are exploiting Africa’s weak intelligence-sharing networks and outdated security methods. About 4,794 people were killed in terrorist attacks in the Sahel in 2024, according to the Global Terrorism Index 2025. The human cost is devastating, with villages massacred and thousands forced to flee their homes. One of the most brutal village massacres occurred in Burkina Faso in August 2024, where jihadists killed at least 100 civilians. Survivors reported that armed militants stormed the village, executing residents and burning homes, forcing the remaining villagers to flee.
Traditional security strategies, including human intelligence and military intervention, have failed to curb these crises effectively. Governments should invest in digital infrastructure and integrate AI into national security strategies to combat insurgency and extremism. AI-powered surveillance systems can analyze large data sets to identify patterns in terrorist activity, predict potential attacks, and track extremist networks. This approach has proven effective in global counterterrorism efforts. For instance, in the United Arab Emirates, AI surveillance tools have been deployed to detect suspicious activities and prevent potential terrorist threats. African governments should collaborate with local AI experts to develop predictive models for threat detection. These models can analyse communication patterns, financial transactions, and online activities to flag potential risks. However, these tools should be deployed with strict oversight to prevent misuse against civilians.
Another security challenge that Africa is currently facing is porous borders. Weak border management is enabling illegal arms trade, human trafficking, and insurgent movements. This has fueled crises like the M23 rebellion in the DRC, where armed groups easily cross into Rwanda and Uganda to regroup. In West Africa, smuggling routes remain open, allowing terrorist groups to expand across borders undetected.
This chaos leaves civilians vulnerable, with many abducted for ransom or subjected to human trafficking networks. AI-powered border monitoring systems can track illegal crossings using drones, facial recognition, and automated alerts. Regional blocs must take the lead in deploying AI-based border security programs tailored to their unique security challenges. For example, thermal imaging AI systems can detect movement in dense forests, while satellite-based AI can track illegal maritime activities. Governments must also establish legal frameworks to regulate AI-driven border monitoring to ensure ethical use and prevent human rights violations.
Beyond armed conflicts, human security in Africa is under threat from displacement, food insecurity, and disease outbreaks. The crisis in Sudan has overwhelmed humanitarian agencies, with millions of people lacking access to food and healthcare. Similarly, the DRC is facing one of the world’s largest hunger crises, while severe droughts in the Horn of Africa have left over 45 million people facing food insecurity.
For affected communities, this means starvation, untreated diseases, and children growing up in extreme deprivation. AI can revolutionize crisis management by predicting humanitarian emergencies before they escalate. Governments and humanitarian agencies should deploy AI models to analyze climate patterns, population movements, and food supply chains to anticipate shortages. Machine learning can also enhance emergency response coordination, ensuring that aid reaches the most vulnerable populations faster. For instance, Rwanda and Tanzania are already making use of automated drone systems to deliver medical supplies in conflict zones and remote areas, demonstrating efficient crisis response. Additionally, governments must invest in AI training for disaster response teams to ensure they can interpret AI-generated insights and act accordingly.
Security challenges in Africa are evolving, and so must the continent’s approach to tackling them. AI provides an effective, data-driven approach to tackling terrorism, border security, and humanitarian crises. Governments must prioritise AI adoption by investing in modern technology, forming regional partnerships, and integrating AI into national security strategies.
Rabelani Mulaudzi is a Writing Fellow at African Liberty.
Article first appeared on Daily Trust.
Photo by Igor Omilaev via Unsplash.