Artificial intelligence and machine learning

TLDR

Artificial intelligence and machine learning have become widely used across disciplines, yet their terminology remains inconsistent between academia and industry. This study aims to clarify the relationship between artificial intelligence and machine learning. The authors review literature, develop a conceptual framework for machine learning’s role in intelligent agents, and propose a consistent typology for AI‑based information systems. The work deepens understanding of AI and machine learning, providing terminological clarity and a foundation for interdisciplinary discussion and future research.

Abstract

Abstract Within the last decade, the application of “artificial intelligence” and “machine learning” has become popular across multiple disciplines, especially in information systems. The two terms are still used inconsistently in academia and industry—sometimes as synonyms, sometimes with different meanings. With this work, we try to clarify the relationship between these concepts. We review the relevant literature and develop a conceptual framework to specify the role of machine learning in building (artificial) intelligent agents. Additionally, we propose a consistent typology for AI-based information systems. We contribute to a deeper understanding of the nature of both concepts and to more terminological clarity and guidance—as a starting point for interdisciplinary discussions and future research.