Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Artificial Intelligence for Peace: Enhancing Nigeria’s National Conflict Early Warning and Response System (NCEWERS)

Domaine:

peace and security

Type de record:

paper
Créateur:
Osi
Éditeur:
Ane
Éditeur:
Cen
Hôte:avatar
The growing complexity of violent conflict in Africa calls for innovative approaches to early warning and early response (EWER). Nigeria’s National Conflict Early Warning and Response System (NCEWERS) has advanced conflict prevention through community-based data gathering, situation room analysis, and multi-stakeholder collaboration. Nonetheless, persistent challenges such as delayed responses, data overload, and limited predictive capacity have hindered its success. This paper examines how Artificial Intelligence (AI) can improve NCEWERS and similar systems across Africa by improving the accuracy, timeliness, and scale of conflict detection. As Wambua argues in a Kenyan context, "AI can effectively analyse vast amounts of historical, current and emerging data to systematically identify conflict triggers and patterns for effective conflict prevention". Furthermore, it submits that AI has an unmatched capacity to sustain real-time sharing of information among the relevant actors in conflict prevention infrastructure. This guarantees timely responses to check the escalation of conflicts. Using secondary data from institutional reports, academic studies, and lessons learned from projects, the study examines AI tools like Machine Learning (ML) for trend analysis, natural language processing for social media monitoring, and predictive modelling for hotspot identification. While AI offers faster processing and improved forecasting, some concerns remain around algorithmic bias, data privacy, ethical use, and the risk of sidelining local knowledge. The paper advocates for a hybrid model that combines AI-enabled analytics with human judgment and community insights, embedded within robust institutional response mechanisms. It further proposes recommendations, including investing in tailored AI research, fostering regional cooperation, developing ethical frameworks, strengthening capacity building, and prioritising community involvement. This approach positions Nigeria to lead in AI-enhanced peacebuilding on the continent, bridging the warning–response gap and ensuring that early alerts translate into timely, meaningful actions toward sustainable peace. International Journal of Migration and Global Studies (IJMGS), 5(2), 143-158

Visit

doi.orgijmgs.nou.edu.ng

Tags

Artificial IntelligenceConflict PreventionEarly Warning SystemsHybrid ModelPeacebuilding

Similaires

Enhancing Kenya’s National Security: Optimizing Early Warning and Response Surveillance SystemsBhuvanachandhiran/conflict-early-warning-systemtripplemagencies28-cmyk/AI-Powered-Threat-Intelligence-and-Early-Warning-System-for-National-Security-in-Kenya-AITIEWS-Leveraging artificial intelligence for predictive disease surveillance and early warning systems in NigeriaGOVERNANCE-EMBEDDED ARTIFICIAL INTELLIGENCE FOR CLIMATE-DRIVEN TRANSBOUNDARY PEST EARLY WARNING SYSTEMSAssessing the Early Warning-Response Gap in Ecowas Conflict Prevention, 2010-2025

Enhancing Kenya’s National Security: Optimizing Early Warning and Response Surveillance Systems

National security is a foundational priority for states, particularly in volatile global environment

Bhuvanachandhiran/conflict-early-warning-system

Random Forest model that predicted Tigray War, Sudan 2023 civil war & forecasts 2025 African conflic

tripplemagencies28-cmyk/AI-Powered-Threat-Intelligence-and-Early-Warning-System-for-National-Security-in-Kenya-AITIEWS-

Develop an AI-powered threat intelligence and early warning system to enhance Kenya’s capacity for p

Leveraging artificial intelligence for predictive disease surveillance and early warning systems in Nigeria

The study focused on a systematic review of the application of artificial intelligence in predicting

GOVERNANCE-EMBEDDED ARTIFICIAL INTELLIGENCE FOR CLIMATE-DRIVEN TRANSBOUNDARY PEST EARLY WARNING SYSTEMS

This proposal introduces Governance-by-Design Theory and its

Assessing the Early Warning-Response Gap in Ecowas Conflict Prevention, 2010-2025

This article interrogates the persistent disconnect between early warning capacity and timely confl