The Internet of Things (IoT) and Artificial Intelligence (AI) is changing the conventional meaning of manufacturing to new smart, connected, and responsive manufacturing. Such integration will be possible to have live data provided by sensors, machines, production lines, and AI-based analytics as an instrument of predictive, prescriptive, and autonomous decision-making. The IoT-AI systems cater to the needs of a layered system design, industrial internet platform, and digital twin systems in order to improve the operational efficiency, scale and interoperability. Predictive maintenance, intelligent quality control, fault detection, process control, energy control, and supply chain control are the most common uses of it. Other facilitating technologies that can be used to revitalize responsiveness and smarts of systems include intelligent sensing, edge-cloud computing, big data analytics, next-generation networking (5G/TSN) and immersive technologies (AR/VR). These advantages notwithstanding, the system integration, cybersecurity, data governance, standardization, and workforce readiness issues are also a challenge. These problems are to be taken into account to realize the full potential of the IoT-AI convergence and allow building resilient, sustainable, and data-oriented manufacturing ecosystems as part of the goals of Industry 4.0.