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International Journal of Research and Innovation in Social Science (IJRISS)

Kidnapping as an Evolving Security Threat in Africa: Drivers, Trends, and Resilience Options in The Artificial Intelligence Age

byDr Abiodun Akinola OLADITI; Dr John Olusola AKANNI; Dr Rasheed Aderemi RAJI; Dr Abubakar Soliu Idowu

Published July 28, 2026  •  Vol. 10, Issue 7, pp. 2798–2809Open Access
DOI: 10.47772/IJRISS.2026.100700192

Abstract

Kidnapping has emerged as one of Africa’s most complex and rapidly evolving security threats, transforming from isolated criminal activity into a structured security economy associated with terrorism financing, organised crime, governance fragility, and socioeconomic vulnerabilities. This study examines the drivers, regional trajectories, and resilience options associated with kidnapping in Africa, with particular attention to the emerging role of Artificial Intelligence (AI) in contemporary security governance. The study adopts a narrative review and policy-analysis design, drawing evidence from criminal justice statistics, conflict-event datasets, terrorism-impact indices, institutional reports, and recent scholarly literature on kidnapping, organised crime, terrorism financing, and AI-enabled security applications. Data sources were selected based on relevance, credibility, geographical representation, and recency, with emphasis on materials published between 2020 and 2026. Through thematic synthesis and comparative analysis, the study identifies poverty, unemployment, weak governance, porous borders, climate-related resource pressures, judicial limitations, and criminal-terrorist financing networks as major drivers sustaining kidnapping across African regions that calls for pragmatic advances rather than the usual rhetoric. The study further examines empirical applications of AI-enabled security interventions, including automated surveillance and crime analytics in South Africa, digital security initiatives in Kenya, citizen-reporting and predictive policing experiments in Ethiopia, and AI-supported financial intelligence mechanisms relevant to counter-terrorism financing. Findings indicate that AI offers significant opportunities for strengthening kidnapping prevention through predictive analytics, intelligence coordination, financial monitoring, and early-warning systems. However, the technology also introduces risks associated with surveillance abuse, algorithmic bias, data protection concerns, and potential exploitation by criminal and extremist actors. The study argues that AI should be understood as a security-enhancing instrument rather than a substitute for governance reform. Sustainable resilience against kidnapping in Africa requires integrating responsible AI deployment with institutional strengthening, socioeconomic development, regional intelligence cooperation, community participation, and human-rights-based security governance.

Keywords: Kidnapping for ransom; Terrorism financing; Artificial intelligence; Predictive policing; Security resilience

JournalInternational Journal of Research and Innovation in Social Science (IJRISS)
ISSN2454-6186
Volume / IssueVolume 10, Issue 7
Pages2798–2809
Publication dateJuly 28, 2026
DOI10.47772/IJRISS.2026.100700192
PublisherRSIS International
LicenseOpen Access

How to cite this article

Dr Abiodun Akinola OLADITI, Dr John Olusola AKANNI, Dr Rasheed Aderemi RAJI, & Dr Abubakar Soliu Idowu (2026). Kidnapping as an Evolving Security Threat in Africa: Drivers, Trends, and Resilience Options in The Artificial Intelligence Age. International Journal of Research and Innovation in Social Science (IJRISS), 10(7), 2798-2809. https://doi.org/10.47772/IJRISS.2026.100700192

BibTeX

@article{Dr2026,
  title   = {Kidnapping as an Evolving Security Threat in Africa: Drivers, Trends, and Resilience Options in The Artificial Intelligence Age},
  author  = {Dr Abiodun Akinola OLADITI and Dr John Olusola AKANNI and Dr Rasheed Aderemi RAJI and Dr Abubakar Soliu Idowu},
  journal = {International Journal of Research and Innovation in Social Science (IJRISS)},
  volume  = {10},
  number  = {7},
  pages   = {2798--2809},
  year    = {2026},
  doi     = {10.47772/IJRISS.2026.100700192},
  publisher = {RSIS International}
}