Based on the findings, it is recommended that banks in Edo State implement continuous cybersecurity aware- ness programs to enhance staff knowledge and vigilance. Management should ensure full deploym

The gap

Consensus across the literature

Supporting evidence — 3 representative gaps

• Emerging Trends and Future Directions in Artificial Intelligence-Driven Cybersecuritya Strategic and Governance Perspective on AI-Enabled Digital Security Systems in India (2026) · doi

  Although this research was conducted in a very broad scope, there are various limitations that should be noted. First, the research is based purely on the secondary sources of data, which restricts its capacity to obtain real-time operational information about cybersecurity leaders and companies. Experts interviews, field surveys, and case studies were not possible as the primary data collection techniques because the nature of confidentiality and lack of access to sensitive data associated with cybersecurity. These kinds of limitations have been pointed out in past studies of AI and cybersecurity reviews, where the limited access to data has frequently precluded empirical verification of any of the limits in actual operational settings [46]. Second, the fast-changing environment of the Artificial Intelligence technologies and cyber threats imply that not all the new aspects are already seen in scholarly literature. The current technological advancements in AI-based cyber defense and mechanisms of attacks usually surpass the speed of academic publication, leaving a time delay between the innovation and the research results on the same paper [49]. Third, the differences between the studies in terms of the research methods can result in discrepancies in assessing the performance of the Artificial Intelligence and the effectiveness of cybersecurity. Disagreements in datasets, experimental situations, and metrics of evaluation can restrict comparability between research results. These limitations were however addressed by using multiple reliable data sources, methodological triangulation and systematic thematic analysis which is highly recommendable in enhancing reliability in secondary research studies [48]. 10.5.5

  Keywords: cybersecurity limitations based secondary sources time operational access artificial intelligence cyber conducted broad scope there
• CYBERSECURITY IN ACCOUNTING INFORMATION SYSTEMS IN THE BANKING SECTOR IN EDO STATE, NIGERIA (2026) · doi

  Based on the findings, it is recommended that banks in Edo State implement continuous cybersecurity aware- ness programs to enhance staff knowledge and vigilance. Management should ensure full deployment and regular updating of technological controls such as firewalls, encryption, and security software. Compliance monitoring should be strengthened, with clear policies and accountability mechanisms to reduce lapses. Finally, banks should integrate regular risk assessments and staff training to proactively address emerging cyber threats, thereby safeguarding financial data and promoting trust in banking operations. 157 doi: 10.5281/zenodo.19857508

  Keywords: banks staff regular based recommended state implement continuous cybersecurity aware ness programs enhance knowledge vigilance
• AI in Cybersecurity: A Case Study of Network Protection in Uganda’s Financial Institutions (2026) · doi

  The future of AI-driven cybersecurity in Uganda’s financial sector promises a transformative shift in how institutions protect sensitive data and ensure the integrity of financial transactions. One key direction is the integration of artificial intelligence with blockchain technology, which can create tamper-proof financial records and enable secure, transparent transactions across the banking and fintech landscape. This integration not only strengthens transaction security but also fosters trust among clients and regulators by providing immutable audit trails [18]. Another critical development is the use of AI-powered threat intelligence sharing, where financial institutions collaborate to detect, analyze, and respond to emerging cyber threats in real time. By pooling insights across networks, these institutions can anticipate attacks, minimize risks, and enhance resilience against sophisticated cybercrime. Hybrid security models are also expected to become more prevalent, combining AI’s predictive and adaptive capabilities with traditional cybersecurity measures such as firewalls, encryption, and multi- factor authentication, creating a multi-layered defense strategy that is more difficult for attackers to breach [19]. 3 Equally important is capacity building, as Uganda’s financial sector will require a growing cadre of skilled professionals trained in AI cybersecurity techniques, ensuring that the human element complements technological advances and supports long-term sustainability and resilience in the face of evolving cyber threats. CONCLUSION In conclusion, Artificial Intelligence (AI) holds transformative potential for strengthening cybersecurity in Uganda’s financial sector. The review demonstrates that AI applications, including machine learning, anomaly detection, and automated threat response, have significantly improved network protection, fraud detection, and operational resilience within banks and mobile money platforms. Case studies from leading institutions illustrate tangible benefits, such as faster identification of suspicious activities, reduced risk of data breaches, and enhanced overall system security. However, the successful adoption of AI-driven cybersecurity depends on overcoming several critical challenges, including high implementation costs, insufficient IT infrastructure, limited availability of skilled professionals, and gaps in regulatory frameworks. Addressing these constraints through targeted investment, capacity-building initiatives, and robust policy guidance will be crucial. As digital financial services continue to expand in Uganda, integrating AI technologies into cybersecurity strategies will not only safeguard sensitive financial data but also foster trust, ensure regulatory compliance, and strengthen the long-term resilience of the country’s financial ecosystem against increasingly sophisticated cyber threats. 1.Beyond payments: Expanding digital finance in Uganda for an inclusive and thriving financial future, https://www.uncdf.org/article/8893/beyond-payments-expanding-digital-finance-in-uganda-for-an- inclusive-and-thriving-financial-future REFERENCES 2.Echegu D. A., Aleke J. U., Alum B. N. Mobile Money Adoption in Uganda. 2024: 9(2) 10-16. IDOSR SCIENCES APPLIED AND JOURNAL COMPUTER OF https://doi.org/10.59298/JCAS/2024/92.1016 3.Asmar, M., Tuqan, A.: Integrating machine learning for sustaining cybersecurity in digital banks. Heliyon. 10, e37571 (2024). https://doi.org/10.1016/j.heliyon.2024.e37571 4.Adekoya, O.A., Atlam, H.F., Lallie, H.S.: Quantifying the Multidimensional Impact of Cyber Attacks in Digital (2025). Literature Review.

  Keywords: financial cybersecurity uganda digital institutions cyber resilience future sector intelligence security threats https driven transformative