Inko Amaeriworio, Mrs. Inko Ayebamieghayefa
The integration of Artificial Intelligence (AI) into Information Technology (IT) services is driving a significant shift toward automation, intelligent analysis, and predictive capabilities in IT operations. This paper systematically examines the role of AI in enhancing IT service delivery and operational efficiency, drawing from a review of 25 peer-reviewed articles, industry reports, and case studies published between 2020 and 2025. Key AI technologies—including Machine Learning (ML), Natural Language Processing (NLP), Robotic Process Automation (RPA), and AIOps (Artificial Intelligence for IT Operations)—are analyzed for their impact on incident management, cybersecurity, resource optimization, and user support. The study identifies significant benefits, such as up to 50% reduction in mean time to resolution (MTTR), 30–45% improvement in operational efficiency, and enhanced proactive threat detection. However, critical barriers to adoption persist, including high implementation costs, skill shortages, data privacy concerns, and integration complexities, particularly in developing regions and SMEs. In response, this paper proposes a structured, five-phase strategic framework for AI adoption in IT, emphasizing phased implementation, workforce development, ethical governance, and scalable cloud-based integration. The findings underscore AI's pivotal role in the future of IT service management and provide actionable recommendations for organizations seeking to harness AI for sustainable digital transformation.
@article{ca5e8f6b-dace-400b-af92-67a773284854,
title={The Role of Artificial Intelligence in Enhancing Information Technology Services and Operations: A Systematic Review and Strategic Adoption Framework Engr. INKO, },
author={Inko Amaeriworio and Mrs. Inko Ayebamieghayefa},
year={2026},
language={en}
}TY - JOUR TI - The Role of Artificial Intelligence in Enhancing Information Technology Services and Operations: A Systematic Review and Strategic Adoption Framework Engr. INKO, AU - Inko Amaeriworio AU - Mrs. Inko Ayebamieghayefa PY - 2026 LA - en ER -
Rajesh Jha, Bimal Kumar Jha
This book describes the application of artificial intelligence (AI) and machine learning (ML) concepts to develop predictive models that can be used t
Introduction Concerns over air pollution and the environmental problem of acid rain have made governments all over the world tighten their regulations
Roger Rumbu check
Huan Li, Elsayed Oraby, Jacques Eksteen
Waste printed circuit boards (WPCBs) are a complicated and valuable fraction of electric and electronic waste. The recycling of them is critical to av
Roger Rumbu
PNAS Nexus
This article reports the design and characterization of a high-performance, truly solid polymer electrolyte for lithium-based batteries, addressing lo