In the fourth industrial revolution, the growing digitalization integrates new technologies, such as smart sensors, new communication standards, cyber-physical systems, big data analysis, and the Industrial Internet of Things (IIoT), into the manufacturing industry. In this new age of manufacturing, every component represents a potential data source enabling new methods for data-driven production systems. Prominent application fields in discrete manufacturing are identified by literature research from current developments and enriched with use-cases from projects at the Institute of Production Management, Technology and Machine Tools (PTW). A superior application field resulting from data-driven production is introduced with arising business models. While such applications demanded much effort in the past, artificial intelligence (AI) encountered a turning point which enables systems to learn complex tasks without being explicitly programmed. However, AI has not yet reached the same level of penetration in the manufacturing industry compared to other sectors, such as healthcare and finance. In this paper, the barriers and challenges are outlined and addressed with recommendations for an implementation approach. Another challenging change for future industrial companies is the accomplishment of appropriate IT-infrastructure, especially at the operational level of the production network. Conventional infrastructures such as the strictly hierarchically layered automation pyramid, which does not support skip-level function integration, won’t be longer feasible due to the increasing number of network participants in the future IoP. Central questions about IT-infrastructure and networking, such as platforms and services, communication networks, interoperability of distributed systems, security, and wireless technologies are discussed and assessed from the PTW point of view.