APPLICATION AND EXPLORATION OF ARTIFICIAL INTELLIGENCE IN ENTERPRISE MANAGEMENT AND INDUSTRIAL UPGRADING
DOI:
https://doi.org/10.61841/r1y56f25Keywords:
Artificial intelligence (AI), Enterprise management, Application of AI, Automation, Innovation, Smart manufacturing.Abstract
The purpose of this study is to investigate the application of artificial intelligence (AI) in the domain of enterprise management and to assess the impact of this technology on the promotion of business modernisation, creativity, and productivity in China. AI is becoming more widely recognised as an influential force in contemporary corporations, allowing enterprises to streamlining processes, optimising utilisation of resources, and improve managerial decisions using data-driven conclusions. The purpose of this study is to evaluate the ways in which AI technology might enhance managerial procedures such as organising, management of supply chains, customer administration, controlling, and operational oversight. Employing survey questionnaires dispersed throughout Chinese firms, a method based on quantitative data is used. The statistical analysis techniques are employed to investigate the relationship between the results of enterprise management and applications of AI. The results demonstrate a substantial positive correlation, demonstrating that the implementation of AI leads to improvements in profitability, precision, and tactical versatility. AI decreases errors made by people, improves the reliability of forecasts, and promotes creativity by automated daily tasks and evaluating enormous data sets. By allowing for the customisation of products and services and by providing descriptive models of buyer behaviour, AI also helps to increase engagement with clients. In addition, issues such as the hazards to privacy of information, moral concerns, and the necessity for workforce adaptability are brought to light by the study. Despite these drawbacks, the findings emphasise that AI is a crucial facilitator of enterprise advancement, simplifying the transition from conventional management paradigms to smart, technological-driven systems.
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