A Framework for Understanding AI-Induced Field Change: How AI Technologies are Legitimized and Institutionalized
This work addresses the challenge of AI integration into society for researchers and policymakers, offering a theoretical foundation to analyze field changes, but it is incremental as it builds on existing institutional and information systems theories.
The paper tackles the problem of understanding how AI technologies become legitimized and institutionalized across different fields, presenting a conceptual framework that analyzes the dynamic interplay between AI agents and existing institutional infrastructures.
Artificial intelligence (AI) systems operate in increasingly diverse areas, from healthcare to facial recognition, the stock market, autonomous vehicles, and so on. While the underlying digital infrastructure of AI systems is developing rapidly, each area of implementation is subject to different degrees and processes of legitimization. By combining elements from institutional theory and information systems-theory, this paper presents a conceptual framework to analyze and understand AI-induced field-change. The introduction of novel AI-agents into new or existing fields creates a dynamic in which algorithms (re)shape organizations and institutions while existing institutional infrastructures determine the scope and speed at which organizational change is allowed to occur. Where institutional infrastructure and governance arrangements, such as standards, rules, and regulations, still are unelaborate, the field can move fast but is also more likely to be contested. The institutional infrastructure surrounding AI-induced fields is generally little elaborated, which could be an obstacle to the broader institutionalization of AI-systems going forward.