A Framework for Understanding AI-Induced Field Change: How AI Technologies are Legitimized and Institutionalized

TL;DR

This paper presents a conceptual framework combining institutional and information systems theories to analyze how AI technologies become legitimized and integrated into various fields, affecting organizations and institutions.

Contribution

It introduces a novel framework for understanding AI-induced field change by linking institutional infrastructure with AI adoption and institutionalization processes.

Findings

AI systems influence organizations and institutions as they are introduced into new fields.

The development of institutional infrastructure affects the speed and acceptance of AI integration.

Limited institutional infrastructure can hinder the broader institutionalization of AI.

Abstract

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.