This proposed research explores how artificial intelligence adoption may improve operational efficiency in manufacturing companies. It focuses on predictive maintenance, automated quality inspection, and production scheduling. Data collected from managers and technical personnel will be used to assess implementation readiness and potential performance improvements. The study will also examine infrastructure costs, employee skills, and organizational resistance, providing a framework for evaluating artificial intelligence investments in manufacturing.