Artificial Intelligence in Economic and Financial Communication: Challenges, Practices, and Perspectives for More Transparent and Efficient Information

Abstract

This article examines whether, and under what conditions, artificial intelligence (AI) improves economic and financial communication through better information quality, transparency and decision-making efficiency. Drawing on agency theory, information asymmetry and information governance, it proposes a conceptual model in which AI affects information quality, information quality shapes transparency, and transparency improves decision-making performance. The model also includes a direct effect of AI on decision-making performance and a risk of algorithmic opacity. Three moderating variables are considered: information governance arrangements, data quality, and the complementarity between human expertise and AI systems. Together, these yield eight research hypotheses. An exploratory qualitative study based on semi-structured interviews with twenty-three professionals from the public, private and semi-public sectors in Morocco, analysed thematically, shows that AI is mainly perceived as a tool for automation, reliability and decision support, chiefly because it reduces human error and handles large volumes of data. These effects depend on the quality of input data, on governance arrangements and on continued human oversight. Respondents also report risks of algorithmic opacity, bias, hallucinations and breaches of confidentiality, and the public sector lags behind in adoption. The findings support a contingent, non-deterministic view of AI in economic and financial communication: its value depends on data quality, governance and human judgment more than on the technology itself.

Classification JEL: D82, M41, O33, G30

Paper type: Exploratory qualitative empirical research