International Journal of Advanced Research in Artificial Intelligence and Machine Learning Reviews

AI-Driven IT Management: A Framework for Strategic Implementation and Risk Mitigation

2026-03-10T10:05:38+00:00

Artificial Intelligence (AI) has become a significant influence in IT management, altering strategic decision-making, automation, and risk management processes. The incorporation of AI into IT operations equips organisations with sophisticated tools to enhance efficiency, optimise resources, anticipate threats, and improve service delivery. This research examined the viewpoints of 230 participants, comprising IT professionals, managers, and decision-makers, to investigate the adoption, challenges, and risk mitigation strategies related to AI-driven IT management. The research employed demographic profiling in conjunction with four key dimensions of quantitative data analysis: (1) strategic implementation, (2) operational efficiency, (3) risk mitigation, and (4) organisational impact. The findings indicated that a structured framework that includes employee training, governance mechanisms, and scalable AI infrastructure is essential for effective implementation.

The Global Ethics of Foundation Models Trends, Challenges, and Governance Across Disciplines

2026-03-10T10:48:12+00:00

The rapid adoption of foundation models (FMs) such as large language models, multimodal AI systems, and generative AI has raised critical ethical concerns across multiple disciplines. These models, which can execute a variety of tasks with limited oversight, have presented significant risks such as bias amplification, privacy violations, accountability deficiencies, and disparities in access. This paper examines global patterns of ethical application of core models, identifies SIGNIFICANT challenges, and evaluates approaches to governance across academia, industry, and government. A survey was conducted with 185 participants, including AI practitioners, policymakers, academics, and users, to evaluate their awareness, perspectives, and practices concerning the ethics of foundation models. The results indicate a shared agreement on the need for uniform governance structures, improved transparency, and increased interdisciplinary cooperation to support the ethical deployment of AI technology.