Ready or Not, AI Comes- An Interview Study of Organizational AI Readiness Factors

被引:224
作者
Joehnk, Jan [1 ]
Weissert, Malte [2 ]
Wyrtki, Katrin [1 ]
机构
[1] FIM Res Ctr, Project Grp Business & Informat Syst Engn Fraunho, Wittelsbacherring 10, D-95444 Bayreuth, Germany
[2] Univ Bayreuth, FIM Res Ctr, Univ Str 30, D-95447 Bayreuth, Germany
关键词
Artificial intelligence; AI adoption; AI readiness; Organizational readiness assessment; Interview study; ARTIFICIAL-INTELLIGENCE; INNOVATION ADOPTION; CONCEPTUAL-MODEL; FUTURE; DETERMINANTS;
D O I
10.1007/s12599-020-00676-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:5 / 20
页数:16
相关论文
共 79 条
[11]  
Bawack R, 2019, AMCIS 2019 P CANC
[12]  
Bhattacherjee A., 2012, SOCIAL SCI RES PRINC
[13]   Best Practices for Developing and Validating Scales for Health,Social, and Behavioral Research:A Primer [J].
Boateng, Godfred O. ;
Neilands, Torsten B. ;
Frongillo, Edward A. ;
Melgar-Quinonez, Hugo R. ;
Young, Sera L. .
FRONTIERS IN PUBLIC HEALTH, 2018, 6
[14]   GENERAL-PURPOSE TECHNOLOGIES - ENGINES OF GROWTH [J].
BRESNAHAN, TF ;
TRAJTENBERG, M .
JOURNAL OF ECONOMETRICS, 1995, 65 (01) :83-108
[15]  
Bresnahan T, 2010, HBK ECON, V2, P761, DOI 10.1016/S0169-7218(10)02002-2
[16]   Siri, Alexa, and other digital assistants: a study of customer satisfaction with artificial intelligence applications [J].
Brill, Thomas M. ;
Munoz, Laura ;
Miller, Richard J. .
JOURNAL OF MARKETING MANAGEMENT, 2019, 35 (15-16) :1401-1436
[17]  
Brynjolfsson E., 2017, CIODIVE
[18]   Profound change is coming, but roles for humans remain [J].
Brynjolfsson, Erik ;
Mitchell, Tom .
SCIENCE, 2017, 358 (6370) :1530-1534
[19]   From Use to Effective Use: A Representation Theory Perspective [J].
Burton-Jones, Andrew ;
Grange, Camille .
INFORMATION SYSTEMS RESEARCH, 2013, 24 (03) :632-658
[20]  
Catalyst Fund, 2020, GET START READ AI RE