Newly published article explores the tension between augmentation and automation through AI
In the 1950s, the discussion of the use of Artificial Intelligence (AI) in management was effectively halted due to unsatisfactory technological progress, AI research was largely ceded to computer science. As a result, management scholars have provided little insight into AI during the last two decades despite AI becoming increasingly pervasive in complex, managerial contexts.
New research, conducted in part at the House of Innovation, strives to reposition AI at the crux of the management debate. This research takes three recent business books on AI as a starting point and explores the automation and augmentation concepts in the management domain. Whereas automation implies that machines take over a human task, augmentation means that humans collaborate closely with machines to perform a task. The three books advise organizations to prioritize augmentation, which they relate to superior performance.
In reflecting on this advice, this newly published research argues that, in the management domain, augmentation cannot be neatly separated from automation. These dual AI applications are interdependent across time and space, creating a paradoxical tension. Overemphasizing either augmentation or automation fuels reinforcing cycles with adverse organizational and societal outcomes.
Drawing on these insights, the research concludes that management scholars need to be involved in research on the use of AI in organizations. It also argues that a substantial change is required in how AI research is currently conducted to develop meaningful theory and provide practice with sound advice.
Geneva School of Economics and Management, University of Geneva, Switzerland
House of Innovation, Stockholm School of Economics, Stockholm, Sweden