Industrial work is under restructuring due to digitalization and automation. Technological leaps have led to paradigm shifts, and today with increased digitalization many companies are facing Industry 4.0 through disruptive technologies (Lasi et al, 2014). Through smarter industrial solutions such as Internet of Things (IoT), interconnected machines enable continuous data production and interaction with their environment in new ways Kagerman et al., 2013). Not only through robots, but also through all types of digital devices - which require some form of information interpretation as well as human operation and interaction. The human role in such "technology-talking" work situation will affect the workers way of decision-making and business operations. New work situations include handling continuous information flows and use of various digital technologies as their main production tool. Information judgment, decision-making authority, work incentives and the provision of knowledge creation will form work-training models in the industry 4.0 companies' operations. Hence, increased digitalization push competence development of workers and employees, and to be organized as an integrated combination of engineering knowledge and practical skills (Billet, 2001; Illeris, 2003). New professional competences and skills are needed to master digitalized transformation, which put pressure on manufacturing companies to plan for future transformative professions (Susskind & Susskind, 2015).In what way will digitalization in general and IoT in particular change industrial work and its conditions for competence development and learning? This question is asked and contextualised in two industrial cases, which represent different instances of production lines that is now undergoing industry 4.0. The findings are based on empirical data collections through interviews, observations as well as field- and meeting notes. Early results show that the advancements of digital technologies need to go hand in hand with competence development approaches. The findings show how industry 4.0 initiatives are perceived and adopted by various stakeholder groups. Interviewed managers are stressing the increased need of digitalized data and immediate decision support. As new work conditions based on software-oriented and data-driven initiatives emerge, new learning logics are needed. From these various "pictures" of Industry 4.0 initiatives we contribute with a discussion about prerequisites and implications for competence and learning for industry 4.0 transformations.