Abstract

Artificial intelligence (AI) offers organizations much potential. Considering the manifold application areas, AI’s inherent complexity, and new organizational necessities, companies encounter pitfalls when adopting AI. An informed decision regarding an organization’s readiness increases the probability of successful AI adoption and is important to successfully leverage AI’s business value. Thus, companies need to assess whether their assets, capabilities, and commitment are ready for the individual AI adoption purpose. Research on AI readiness and AI adoption is still in its infancy. Consequently, researchers and practitioners lack guidance on the adoption of AI. The paper presents five categories of AI readiness factors and their illustrative actionable indicators. The AI readiness factors are deduced from an in-depth interview study with 25 AI experts and triangulated with both scientific and practitioner literature. Thus, the paper provides a sound set of organizational AI readiness factors, derives corresponding indicators for AI readiness assessments, and discusses the general implications for AI adoption. This is a first step toward conceptualizing relevant organizational AI readiness factors and guiding purposeful decisions in the entire AI adoption process for both research and practice.

Details

Title
Ready or Not, AI Comes— An Interview Study of Organizational AI Readiness Factors
Author
Jöhnk Jan 1 ; Weißert Malte 2 ; Wyrtki Katrin 3 

 FIM Research Center, Project Group Business & Information Systems Engineering of the Fraunhofer FIT, Bayreuth, Germany 
 University of Bayreuth, FIM Research Center, Bayreuth, Germany (GRID:grid.7384.8) (ISNI:0000 0004 0467 6972) 
 FIM Research Center, Project Group Business & Information Systems Engineering of the Fraunhofer FIT, Bayreuth, Germany (GRID:grid.7384.8) 
Pages
5-20
Publication year
2021
Publication date
Feb 2021
Publisher
Springer Nature B.V.
ISSN
23637005
e-ISSN
18670202
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2479911128
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.