Author
Abstract
Artificial intelligence technology has enabled computer information technology to be developed to new and unprecedented depths, significantly expanding the volume and complexity of information that can be processed, analyzed, and leveraged through the integration of AI-powered systems with traditional information technology infrastructures. Among the most notable innovations are the emergence of novel application models within the information technology industry and the development of advanced paradigms for providing network security. Despite these remarkable strides, the continued development of artificial intelligence technology remains constrained by several critical factors, including the inherent limitations of existing algorithmic frameworks, pressing ethical considerations surrounding the deployment of computer systems, and the growing scarcity of surplus computing resources necessary to sustain large-scale model training and inference. This review systematically investigates innovative pathways that promise to deliver meaningful technological advances, enhanced security protocols, and responsible environmental stewardship, all of which are essential for unlocking the full potential that artificial intelligence can offer to the broader information technology landscape. By examining current trends, identifying key challenges, and proposing forward-looking strategies, this paper highlights the transformative role that artificial intelligence is expected to play in driving the evolution of information technology. The emerging implementations, methodologies, and application ecosystems discussed herein warrant sustained scholarly attention, as they collectively shape the trajectory of future research and industrial practice in this rapidly evolving domain.
Suggested Citation
Fu, Zhengkang, 2026.
"Development Directions and Applications of Artificial Intelligence- Based Computer Information Technology,"
GBP Proceedings Series, Scientific Open Access Publishing, vol. 30, pages 83-90.
Handle:
RePEc:axf:gbppsa:v:30:y:2026:i::p:83-90
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