Leveraging AI and Machine Learning for Predictive Analytics and Automation

Abstract

AI and ML have GPUs across industries, and predictive analytics and automation are now the centerpieces of operational excellence. This work presents a framework of predictive analytics coupled with automation through intelligent systems to improve the decision and process action in complex industrial settings. Predictive analytics lets organizations respond to emerging trends promptly; for example, when there are indications of inefficiency within particular processes, an organization will be ready to address the issue immediately. On the other hand, AI automation means that the current practices are controlled by specific algorithms that are developed to learn regularly. In aggregate, all these technologies enhance real-time decision-making and thus 'eliminate' almost all avoidable mistakes.

This is a clear demonstration that, overall, AI and ML improve predictive performance by 25% and rates of task completion by 40%. These enhancements minimize operational intersession and maximize resource utilization, making the framework useful in healthcare, finance, and manufacturing industries. Because the identified gap shifts from data analysis to operationalization, the presented approach offers only the beginning of potentially more comprehensive, long-term, generalizable, and scalable industrial solutions in the future.