Kaplan and Haenlein define artificial intelligence as a “system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”. What do you think? In their article (Kaplan Andreas; Michael Haenlein (2018) Siri, Siri in my Hand, who’s the Fairest in the Land? On the Interpretations, Illustrations and Implications of Artificial Intelligence, Business Horizons), they furthermore analyze how AI is different from related concepts, such as the Internet of Things and big data, and suggest that AI is not one monolithic term but instead needs to be seen in a more nuanced way. This can either be achieved by looking at AI through the lens of evolutionary stages (artificial narrow intelligence, artificial general intelligence, and artificial super intelligence) or by focusing on different types of AI systems (analytical AI, human-inspired AI, and humanized AI). Based on this classification, they show the potential and risk of AI using a series of case studies regarding universities, corporations, and governments. Finally, they present a framework that helps organizations think about the internal and external implications of AI, which they label the Three C Model of Confidence, Change, and Control.