IMPROVING ECONOMICAL MAINTAIN TACTICS FOR ARTIFICIAL INTELLIGENCE AND MACHINERY LEARNING DEPLOYMENTS IN INFORMATION TECHNOLOGY

Abstract

Artificial intelligence (AI) and machine learning (ML) have revolutionised business processes by improving data analytics and boosting operational efficiency via their incorporation into IT infrastructures. However, some distinct challenges must be surmounted in order to keep these AI and ML systems running smoothly and reliably, particularly with regard to keeping costs in check. The purpose of this research is to find the best ways to improve maintenance solutions for AI and ML installations in terms of cost-effectiveness. Due to their inherent complexity, AI and ML systems require ongoing monitoring, regular model updates, and retraining to maintain accuracy and stay up with ever changing data patterns. When these systems refuse to cooperate with standard maintenance procedures, costs may quickly spiral out of control and performance takes a nosedive. One of the novel approaches discussed in the piece is predictive maintenance, which employs ML algorithms to anticipate problems before they occur, therefore lowering repair costs and downtime. The potential for automated monitoring systems to reduce the need for human oversight by rapidly identifying anomalies is also discussed. One of the main goals of this research is to determine the best combination of initial investment in dependable infrastructure and continuing operational expenditures for maintenance. By being proactive and taking measures to avoid problems, organisations may extend the life of their AI and ML systems, make better use of their resources, and reduce risks. The findings provide a framework for decision-makers and IT professionals to follow when developing effective and economical maintenance plans, which might be very useful. The researcher’s research contributes to the ongoing discussion on sustainable AI and ML management by highlighting the need of strategic maintenance as a means to optimise the return on investment (ROI) in these ground-breaking technologies.