International Journal of Science, Engineering and TechnologyAuthors: Chamath Perera
Abstract: The integration of Artificial Intelligence (AI) into enterprise IT support systems has initiated a paradigm shift from reactive problem-solving toward proactive and intelligent service delivery. Traditional IT support models, often constrained by manual interventions and linear workflows, are being transformed by AI-driven automation that enhances operational agility, responsiveness, and scalability. At the center of this transformation are AI-powered virtual assistants (AIVAs), which employ natural language processing (NLP), machine learning (ML), and contextual analytics to understand user intent, resolve incidents, and streamline workflow management. These assistants function not merely as automated responders but as intelligent collaborators capable of adaptive learning and decision-making based on historical data and real-time analytics. AIVAs automate a wide spectrum of IT support activities including ticket generation, categorization, resolution suggestion, and knowledge base retrieval—thereby reducing human workload and minimizing operational latency. Their ability to integrate across diverse enterprise platforms such as IT service management (ITSM) tools, cloud environments, and monitoring systems positions them as key enablers of digital transformation. Through a comprehensive synthesis of scholarly research, industrial frameworks, and real-world implementations, this review explores how AIVAs contribute to measurable improvements in service quality, mean time to resolution (MTTR), and overall cost efficiency. In addition to outlining architectural models and implementation strategies, the paper critically examines the underlying challenges associated with AIVA deployment particularly issues of contextual understanding, bias in NLP models, data privacy, and integration with legacy systems. The discussion extends to ethical and governance considerations that influence organizational adoption and user trust in AI-driven support ecosystems. Furthermore, the review identifies emerging trends such as the rise of generative AI, predictive maintenance analytics, and multimodal assistants that integrate voice, text, and visual inputs for enhanced interactivity.
DOI: https://doi.org/10.5281/zenodo.17875754
