Developing an Artificial Intelligence Capability: A Theoretical Framework for Business Value

Despite the claim that Artificial Intelligence (AI) can revolutionize the way private and public organizations do business, to date organizations still face a number of obstacles in leveraging such technologies and realizing performance gains. Past studies in other novel information technologies argue that organizations must develop a capability of effectively orchestrating and deploying necessary complementary resources. We contend that if organizations aim to realize any substantial performance gains from their AI investments, they must develop and promote an AI Capability. This paper theoretically develops the concept of an AI capability and presents the main dimensions that comprise it. To do so, we ground this concept in the resource-based view of the firm and by surveying the latest literature on AI, we identify the constituent components that jointly comprise it.

[1]  Jeffrey Heer,et al.  Agency plus automation: Designing artificial intelligence into interactive systems , 2019, Proceedings of the National Academy of Sciences.

[2]  Philip R. O. Payne,et al.  Questions for Artificial Intelligence in Health Care. , 2019, JAMA.

[3]  Paul A. Pavlou,et al.  Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities , 2020, Inf. Manag..

[4]  R. Grant The Resource-Based Theory of Competitive Advantage: Implications for Strategy Formulation , 1991 .

[5]  R. Duane Ireland,et al.  Resource Orchestration to Create Competitive Advantage , 2010 .

[6]  Jim Sterne,et al.  Artificial Intelligence for Marketing: Practical Applications , 2017 .

[7]  Patrick Mikalef,et al.  Big Data Analytics Capability: Antecedents and Business Value , 2017, PACIS.

[8]  Patrick Mikalef,et al.  Big Data Enabled Organizational Transformation: The Effect of Inertia in Adoption and Diffusion , 2018, BIS.

[9]  Jian-Yun Nie,et al.  Complexity Sciences and Artificial Intelligence for Improving Lives through Convergent Innovation , 2018 .

[10]  Patrick Mikalef,et al.  Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment , 2019, British Journal of Management.

[11]  Patrick Mikalef,et al.  Big data analytics and firm performance: Findings from a mixed-method approach , 2019, Journal of Business Research.

[12]  A. Lockett,et al.  The Development of the Resource-Based View of the Firm: A Critical Appraisal , 2009 .

[13]  E. Shortliffe,et al.  Clinical Decision Support in the Era of Artificial Intelligence. , 2018, JAMA.

[14]  Robert W. Palmatier,et al.  A Comparative Longitudinal Analysis of Theoretical Perspectives of Interorganizational Relationship Performance , 2007 .

[15]  Patrick Mikalef,et al.  Information technology-enabled dynamic capabilities and their indirect effect on competitive performance: Findings from PLS-SEM and fsQCA , 2017 .

[16]  Kenneth L. Kraemer,et al.  Review: Information Technology and Organizational Performance: An Integrative Model of IT Business Value , 2004, MIS Q..

[17]  刘 子熠,et al.  Hybrid-augmented intelligence: collaboration and cognition , 2017, Frontiers of Information Technology & Electronic Engineering.

[18]  Mohammad Hossein Jarrahi,et al.  Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making , 2018, Business Horizons.

[19]  Michail N. Giannakos,et al.  Big data analytics capabilities: a systematic literature review and research agenda , 2017, Information Systems and e-Business Management.

[20]  Anandhi S. Bharadwaj,et al.  A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation , 2000, MIS Q..

[21]  Chun-Wei Yang,et al.  Applications of artificial intelligence in intelligent manufacturing: a review , 2017, Frontiers of Information Technology & Electronic Engineering.

[22]  Peter Corcoran,et al.  Deep Learning for Consumer Devices and Services: Pushing the limits for machine learning, artificial intelligence, and computer vision. , 2017, IEEE Consumer Electronics Magazine.

[23]  Maria José Sousa,et al.  Skills for disruptive digital business , 2019, Journal of Business Research.

[24]  Erik Brynjolfsson,et al.  Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics , 2017 .

[25]  Joey F. George,et al.  Toward the development of a big data analytics capability , 2016, Inf. Manag..

[26]  M. Wade,et al.  Review: the resource-based view and information systems research: review, extension, and suggestions for future research , 2004 .

[27]  Hal R. Varian,et al.  Artificial Intelligence, Economics, and Industrial Organization , 2018 .

[28]  Brian P. Bloomfield The Culture of Artificial Intelligence , 2018 .

[29]  J. Barney Resource-based theories of competitive advantage: A ten-year retrospective on the resource-based view , 2001 .

[30]  Paul A. Pavlou,et al.  From IT Leveraging Competence to Competitive Advantage in Turbulent Environments: The Case of New Product Development , 2006, Inf. Syst. Res..