AI-Powered Quality Assurance: Revolutionizing Software Development Through Intelligent Anomaly Detection and Automated Monitoring
Year: 2025
Type: article
Abstract: The integration of artificial intelligence into data management has fundamentally transformed enterpriseapproaches to quality assurance and anomaly detection. Through the orchestration of automated monitoringsystems, advanced pattern recognition algorithms, and contextual analytical frameworks, AI technologiesdeliver substantial enhancements to productivity, precision, and issue resolution across softwaredevelopment ecosystems. The deployment of AI-driven solutions redefines traditional data stewardshippractices by enabling sophisticated real-time processing capabilities and data-informed decision-making.These technological advancements yield measurable improvements in operational efficiency, costcontainment, and strategic resource optimization. As AI continues to evolve within enterpriseenvironments, it demonstrates increasing significance in preserving data integrity, streamliningdevelopment processes, and fostering innovation throughout the software industry.
Author: Viswakanth Ankireddi -
Institution: Intel (United States)
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409218694