Artificial Intelligence (AI)-Driven Data Protection Strategies in Banking Institutions in Uasin Gishu County, Kenya

In an era where traditional cybersecurity measures are increasingly inadequate against the growing sophistication and volume of digital threats, banks are compelled to adopt innovative technologies such as AI.The study explored the adoption and effectiveness of Artificial Intelligence (AI)-based strategies for data protection among banking institutions in Uasin-Gishu County, Kenya.The present study employed surveys and interviews to investigate the integration of AI tools, particularly machine learning algorithms for fraud detection, predictive analytics, and anomaly detection in selected banking institutions.The study revealed that all surveyed banks (100%) had adopted AI-based security systems, with 68.6% focusing on fraud prevention and 66.7% on anomaly detection.A statistically significant relationship (p < 0.001) was observed between strong data protection policies and firms' integration of AI in security frameworks.The adoption of AI was driven by its capacity to predict threats, enhance fraud detection, and improve operational efficiency.Despite these benefits, the study identified significant challenges, including a shortage of skilled professionals for AI system implementation and persistent concerns regarding data privacy.Additionally, existing regulatory frameworks were deemed insufficient to address emerging risks associated with AI-driven data security.Most respondents acknowledged that the advantages of AI outweighed its challenges, making it a preferred solution for enhancing data protection.The study concludes that AI enhances data security in the banking sector and recommends strengthened regulatory frameworks, increased investment in specialized AI training, and continuous stakeholder engagement to maximize AI's potential in the cybersecurity landscape.