Saad S. Alani

Background: Enabling Edge Artificial Intelligence (Edge AI) to be implemented in autonomous systems and telecommunications can offer for improved real-time data, non-recurring latency, enhanced operational proficiency. Some empirical research suggests that Edge AI minimizes latency by 70%, enhances computing speed by 50%, and cuts bandwidth consumption by 30% in the most demanding cases. Objective: The purpose of this article is to investigate how Edge AI can serve as an enabling technology for the future of self-sustaining environments such as autonomous mobility and telecommunications in terms of measured utility and differentiation. Methods: Screening 120 refereed articles and 25 case studies connected to Edge AI application in telecoms and self-governing systems, this systematic looked-for patterns in the proximal research and promising agendas. The review encompassed research works concerned with latency minimization, bandwidth enhancement and enhancement in the processing capacity. Focus was made on application areas like self-driving cars, industrial IoT, and smart city platforms and performance analysis was made in these areas. Results: The current study prove that when employed in autonomous systems, Edge AI enhances decision making reaction time by 40-60%, while enhancing data traffic throughput within telecommunications networks by 35%. Further, Edge AI makes the overall energy consumption lower in IoT-based applications by cutting down the average usage by a quarter thus creating a sustainable network. Conclusion: Edge AI becomes a central tool in the development of self-driving cars and telecommunications, increased performance and ability to handle mass amount of data at a low latency. These developments place Edge AI at the base of the evolution of future intelligent systems as the basis for smarter and more responsive technological landscapes.

Background : As digital transformation accelerates globally, effective IT governance has become critical for organizational success. With global spending on IT governance and risk management projected to reach $16 billion by 2025, emerging technologies such as artificial intelligence (AI), blockchain, and cloud computing are introducing new governance complexities that demand adaptive strategies. Objective : The article explores the key factors and anticipated trends in IT governance that are expected to shape organizational management by 2025. The aim is to understand how evolving technological landscapes influence governance models and risk management practices. Method : A qualitative methodology was adopted, involving a systematic review of 100 scholarly and industry articles focused on recent trends and future directions in IT governance. The analysis highlights issues related to risk management, regulatory compliance, cybersecurity, and technology integration. Results : The review revealed that 83% of organizations reported significant governance challenges due to technological disruption, while 68% indicated a transition toward decentralized governance models, particularly within blockchain-based systems. Additionally, AI-powered decision-making tools are projected to be adopted by over 70% of large enterprises for IT governance functions by 2025. Conclusion : The findings underscore the growing need for flexible and adaptive IT governance frameworks that align with both agile and traditional business objectives. By anticipating and addressing future risks and compliance demands, organizations can enhance their current governance strategies to remain resilient and competitive in the digital era.