Measuring Intellectual Capital in the Context of the Increased Use of Artificial Intelligence

This paper addresses the topic of measuring intellectual capital in a context where artificial intelligence and ESG factors are becoming essential. The literature provides extensive information on the limitations of traditional models for measuring intellectual capital, including the Value-Added Intellectual Capital Ratio, which does not explicitly highlight the positive implications of digital assets and sustainability. The study is based on 75 companies listed on the Bucharest Stock Exchange, and the data are processed using SPSS software, employing qualitative and quantitative methods, linear regression, Pearson’s correlation, and the ANOVA model. According to the results, the traditional model does not provide complete information and does not yield significant values for Tobin’s Q coefficient, unlike the modern model, which is based on four dimensions: human capital, relational capital, social capital, and ESG factors. The modern model provides information that can be used in the decision-making process and in the development of future strategies for investors, managers, and other information users. The paper lays the groundwork for the development of future multidimensional models for evaluating intellectual capital, adapted to current changes, providing a reliable source of information for stakeholders. Artificial intelligence is viewed as a method for analyzing complex data, not as an independent variable. Indirectly, it is reflected through components of structural capital such as digital infrastructure, as well as through corporate sustainability policies. In this way, we can assess the specific relevance of predictors to organizational outcomes.