Systems Approach for the Adoption of New Technologies in Enterprises

Abstract

There is a great challenge in the business sector to adopt new technologies that boost companies to break into Industry 4.0, especially to obtain the capacity to adopt and develop complex systems based on: artificial intelligence, Big Data, Data Mining, and Cyber Physical Systems. However, efforts tend to be more of an empirical process, rather than a prior analysis, that allows companies to identify the complexity of the situation and trigger a viable implementation. For this reason, this research carried out a systematic review to identify and analyze, from the Systems Science approach, the proposed and most used models to face these organizational problems. In total, 42 of the 3800 documents were filtered for discussion using a systems approach. In addition, one of the models was tested by interviews with Mexican managers to understand how it promotes the abstraction of complexity necessary for a viable system change. The findings at the end of the work were to determine the lack of systemic properties in the current proposals, especially in the efforts to adopt artificial intelligence and the need to have a suitable model for the context of technology.

Risk Analysis of Artificial Intelligence in Medicine with a Multilayer Concept of System Order

“…24 Intentional or Unintentional Changes During Training e.Pi. 25 Cyber Attacks e.Pi.i Others ✓ ✓ e.Pi. 25 ✓…”

“…The NIST framework provides guidance for addressing risks in the design, development, use, and evaluation of AI systems [25] to ensure their trustworthiness. However, this paper identifies the need for further risk analysis to facilitate the widespread adoption of the NIST framework by organizations.…”

Navigating Gender Nuances: Assessing the Impact of AI on Employee Engagement in Slovenian Entrepreneurship

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