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The world is moving extremely fast towards creating a superintelligence that will go far beyond human capabilities. Proper use of this superintelligence in enterprises will result in developing conditions in which their potential is fully exploited. In the context of the above, research has been undertaken to recognize the level of knowledge maturity in the domain of IT tools based on the artificial intelligence algorithm. In other words, it is about recognizing whether the enterprise knows IT tools supporting management operating on the basis of the artificial intelligence algorithm. It was assumed that in the fourth generation industry era such tools should be implemented by Polish manufacturers operating in the agricultural machinery sector. To assess the level of business knowledge of IT tools based on AI algorithms maturity the self-evaluation questionnaire was developed and the research was conducted among manufacturers of parts, subassemblies and ready-made agricultural machines.

The role and importance of management staff is very important in the era of the Fourth Industrial Revolution. A high-quality production environment will require mature management staff with experience in working with new technologies, machines, and, especially, data and information. The undertaken research indicates that both in terms of theory and practice of management, there are many unresolved issues concerning the measurement of maturity of a manager. Given the above, it was recognized as justified in this chapter to contrive and implement an assessment method in practice. The fundamental purpose of the chapter is attempted assessment of maturity of managers in manufacturing companies operating in the agricultural machinery sector being an answer to the upcoming Fourth Industrial Revolution identified as a concept regarding the use of automation and processing and exchange of data as well as implementation of various new technologies enabling to create the so-called cyber-physical systems and change of the methods of manufacturing.

The paper is qualitative-quantitative research designed and conducted to analyze technical culture maturity in companies representing agricultural machinery sector. Authors believe that technical culture maturity proves that company implemented and is following lean management principles. The research conducted showed high level of technical maturity, proving that companies within the sector are mature in technical culture context, nevertheless there are some aspects that could be improved. The high level of maturity is on one hand consequence of lean management principles implementation, on the other it creates environment that supports and strengthens leaning the companies. The developed method can be used by companies for self-assessment and reference when improving their maturity and implementing lean.

The subject of interest of hereby article is the identification of features related to the leanness of production units. The study was conducted in the context of the above and the main purpose was to verify this hypothesis. Surveys were conducted among Lean Production experts. The research allowed the authors (to designate preferred features of leanness in production units) to determine the essence and significance of the characteristics with respect to the leanness of designed production units.