Artificial intelligence (AI) - Application for evaluating the enterprise's digital transformation capacity

Authors

  • Nguyen Thi Thanh Huong
  • Tran Quang Huy

Keywords:

Machine learning, Digital transformation capabilities, Enterprises

Abstract

We are living in a period of digital transformation, in the 4.0 industrial revolution, the age of information is developing rapidly, so corporations and businesses can no longer exploit sustainably the competitive advantages if they only rely on the tangible assets of technology and the exploitation and mobilization of the intangible assets of technology are becoming increasingly more decisive factors. Digital transformation is an inevitable trend, contributing to promoting economic growth, improving labor productivity, competitiveness, production, and business efficiency, and lowering product costs, reducing administrative procedures, time, and costs. To evaluate the digital transformation capacity of businesses, traditional measures that are based on financial indicators are no longer strong enough and are not suitable to control and accurately control the performance of businesses in the new circumstances. Businesses need a new tool that can use artificial intelligence (AI) to provide a balanced view of all qualitative influencing factors and identify decisive capacity parameters in a more relevant and smarter manner. This article provides an overview of digital transformation perspectives and enterprise digital transformation capabilities, factors affecting digital transformation capabilities, and the application of language-based machine learning algorithms: ontology and fuzzy logic to evaluate the digital transformation capacity of enterprises.

Code: 24020101

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References

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Published

02-12-2024

How to Cite

Nguyen Thi Thanh Huong, & Tran Quang Huy. (2024). Artificial intelligence (AI) - Application for evaluating the enterprise’s digital transformation capacity. Journal SCIENCE AND TECHNOLOGY POLICIES AND MANAGEMENT, 13(1), 34–45. Retrieved from https://vietnamstijournal.net/index.php/JSTPM/article/view/526

Issue

Section

STUDIES OF STRATEGIES AND MANAGEMENT