Fuzzy Inspired Intelligent Interaction Model for Business Sector using Statistical Analysis

Technological breakthroughs in Artificial Intelligence (AI) have led to the growth of human-like computers that can work independently and replicate a cognitive activity. The progression and interest among managers, researchers, and the general public have aroused interest in many industries, and significant corporate sectors are spending massively to profit gain through technology with the development of business interaction models. As information technology (IT) platforms become more advanced, and business activities become more autonomous, there is an increasing demand for business managers to better impact company operations and how they correspond with organizational goals. Machine learning and fuzzy logic design have lately been highlighted as recent innovations. Machine learning is an artificial intelligence approach that may enable smarter and more intelligent decision-making outcomes. In comparison, Fuzzy Logic Design (FLD) is a procedure that provides inferences or solutions from an ambiguous situation. In this research article, a fuzzy-inspired intelligent interaction model for the business sector is proposed, which utilizes a fuzzy logic design approach while enabling users to understand functions from a business standpoint and organize them related to the business targets, identify key indicators and carry out the necessary intelligent analysis on them to recognize causal factors of unforeseen metric values and enhance efficiency to improve business leadership.