Algorithmic isomorphism and the erosion of competitive advantage in the age of artificial intelligence: A review of emerging risks in strategic management
TL;DR
The article analyzes how the imperfections of artificial intelligence systems such as the lack of transparency, inherent database bias and their Western-centric nature can lead to the reproduction of identical market behaviour patterns and points to the necessity of balancing technological innovation with a human-centric approach to protect corporate identity.
Abstract
Artificial intelligence is gaining prominence not only as an operational optimization tool, but primarily as a key element shaping decision-making processes and strategic management within organizations. The public and academic debate is dominated by concerns regarding job losses, privacy violations, social manipulation and biases hidden in algorithms. The purpose of this review paper is to transpose these issues into the realm of corporate management and examine a significantly less obvious threat: algorithmic isomorphism. This entails the homogenization of business strategies resulting from widespread reliance on the same global machine learning models. The article analyzes how the imperfections of artificial intelligence systems such as the lack of transparency (the black box effect), inherent database bias and their Western-centric nature can lead to the reproduction of identical market behaviour patterns. Furthermore, the impact of these technologies on the risk of unique know-how leakage and the loss of tacit knowledge held by human managers, which is crucial for competitive advantage, is discussed. The comprehensive analysis also encompasses the transfer of market mechanisms, known from algorithmic financial crises, to the sphere of long-term business decision-making. The conclusions point to the necessity of balancing technological innovation with a human-centric approach to protect corporate identity.