How Artificial Intelligence affords digital innovation: A cross-case analysis of Scandinavian companies

Abstract Artificial Intelligence (AI) is fuelling a new breed of digital innovation in Human Resource Management by creating new opportunities for complying with General Data Protection Regulation during data collection and analysis, decreasing biases, and offering targeted recommendations. However, AI is also posing challenges to organisations and key assumptions about digital innovation processes and outcomes, making it unclear how to combine AI affordances with actors, goals, and tasks. We conducted a qualitative multiple-case study in Scandinavian organisations offering HR services. Grounded theory guided our data collection and analysis. Input-Process-Output framework and affordance theory supported the analysis of specific information processing constraints and enablers. We developed a framework to explain how AI affordances enable digital innovation and address the calls about definitional boundaries between innovation processes and outcomes. We showed how AI affordances are actualised and how this leads to reontologising decision-making and providing data driven legitimisation. Our study contributes to digital innovation research by elucidating AI affordances and their actualisation in organisations. We conclude with the implications to theory and practice, limitations, and suggestions for future research.

[1]  Shan Ling Pan,et al.  Affordances, experimentation and actualization of FinTech: A blockchain implementation study , 2019, J. Strateg. Inf. Syst..

[2]  Alessandro Margherita,et al.  Human resources analytics: A systematization of research topics and directions for future research , 2021, Human Resource Management Review.

[3]  Louis Rosenberg,et al.  Keeping Humans in the Loop: Pooling Knowledge through Artificial Swarm Intelligence to Improve Business Decision Making: , 2019 .

[4]  Patrick Mikalef,et al.  Big Data Analytics as an Enabler of Process Innovation Capabilities: A Configurational Approach , 2018, BPM.

[5]  Patrick Mikalef,et al.  Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance , 2021, Inf. Manag..

[6]  R. Yin.  Case Study Research: Design and Methods , 1984 .

[7]  Mingtao Xu,et al.  Substituting Human Decision-Making with Machine Learning: Implications for Organizational Learning , 2020 .

[8]  R. G. Fichman,et al.  Digital Innovation as a Fundamental and Powerful Concept in the Information Systems Curriculum , 2014, MIS Q..

[9]  Vinit Parida,et al.  Artificial intelligence and innovation management: A review, framework, and research agenda✰ , 2021, Technological Forecasting and Social Change.

[10]  Ann Majchrzak,et al.  Methods for Policy Research: Taking Socially Responsible Action , 2013 .

[11]  D. Norman.  The Design of Everyday Things: Revised and Expanded Edition , 2013 .

[12]  C. Collins,et al.  STRATEGIC HUMAN RESOURCE PRACTICES, TOP MANAGEMENT TEAM SOCIAL NETWORKS, AND FIRM PERFORMANCE: THE ROLE OF HUMAN RESOURCE PRACTICES IN CREATING ORGANIZATIONAL COMPETITIVE ADVANTAGE , 2003 .

[13]  Patrick Mikalef,et al.  Responsible AI for Digital Health: a Synthesis and a Research Agenda , 2021, Information Systems Frontiers.

[14]  Diane M. Strong,et al.  Critical Realism and Affordances: Theorizing IT-Associated Organizational Change Processes , 2013, MIS Q..

[15]  Daniel Robey,et al.  Affordance potency: Explaining the actualization of technology affordances , 2017, Inf. Organ..

[16]  Gerald C. Kane,et al.  The Contradictory Influence of Social Media Affordances on Online Communal Knowledge Sharing , 2013, J. Comput. Mediat. Commun..

[17]  Kathleen M. Eisenhardt,et al.  Theory Building From Cases: Opportunities And Challenges , 2007 .

[18]  Kalle Lyytinen,et al.  Digital Innovation Management: Reinventing Innovation Management Research in a Digital World , 2017, MIS Q..

[19]  K. Eisenhardt.  Building theories from case study research , 1989, STUDI ORGANIZZATIVI.

[20]  J. Forrest,et al.  Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors , 2020, Technological Forecasting and Social Change.

[21]  Kathleen M. Eisenhardt,et al.  Finding Theory–Method Fit: A Comparison of Three Qualitative Approaches to Theory Building , 2017 .

[22]  William J. Kettinger,et al.  Transformative rare events: Leveraging digital affordance actualisation , 2021, European Journal of Information Systems.

[23]  William H. DeLone,et al.  Global boundaries, task processes and IS project success: a field study , 2006, Inf. Technol. People.

[24]  D. Wright,et al.  Artificial intelligence for human flourishing – Beyond principles for machine learning , 2020, Journal of Business Research.

[25]  Yenni Tim,et al.  Actualizing big data analytics for smart cities: A cascading affordance study , 2020, Int. J. Inf. Manag..

[26]  Dhruv Grewal,et al.  How artificial intelligence will change the future of marketing , 2019, Journal of the Academy of Marketing Science.

[27]  Kalle Lyytinen,et al.  Research Commentary - The New Organizing Logic of Digital Innovation: An Agenda for Information Systems Research , 2010, Inf. Syst. Res..

[28]  Amy Van Looy.  A quantitative and qualitative study of the link between business process management and digital innovation , 2021, Inf. Manag..

[29]  F. Tschang,et al.  Artificial Intelligence as Augmenting Automation: Implications for Employment , 2020, Academy of Management Perspectives.

[30]  Hind Benbya,et al.  Special Issue Editorial: Artificial Intelligence in Organizations: Implications for Information Systems Research , 2021, J. Assoc. Inf. Syst..

[31]  Franz Strich,et al.  What Do I Do in a World of Artificial Intelligence? Investigating the Impact of Substitutive Decision-Making AI Systems on Employees' Professional Role Identity , 2021, J. Assoc. Inf. Syst..

[32]  G. Krogh.  Artificial Intelligence in Organizations: New Opportunities for Phenomenon-Based Theorizing , 2018, Academy of Management Discoveries.

[33]  G. Kasper,et al.  The Challenges of Algorithm-Based HR Decision-Making for Personal Integrity , 2019, Journal of Business Ethics.

[34]  P. Fleming.  Robots and Organization Studies: Why Robots Might Not Want to Steal Your Job , 2019 .

[35]  Arun Rai,et al.  Explainable AI: from black box to glass box , 2019, Journal of the Academy of Marketing Science.

[36]  Stella Pachidi,et al.  Working and organizing in the age of the learning algorithm , 2018, Inf. Organ..

[37]  Paul M. Leonardi,et al.  When Flexible Routines Meet Flexible Technologies: Affordance, Constraint, and the Imbrication of Human and Material Agencies , 2011, MIS Q..

[38]  L. Floridi.  Artificial Intelligence as a Public Service: Learning from Amsterdam and Helsinki , 2020, Philosophy & Technology.

[39]  Oliver Krancher,et al.  Key Affordances of Platform-as-a-Service: Self-Organization and Continuous Feedback , 2018, J. Manag. Inf. Syst..

[40]  A. Strauss,et al.  Basics of Qualitative Research , 1992 .

[41]  Panos Constantinides,et al.  Artificial intelligence in cardiology : applications, benefits and challenges , 2018 .

[42]  Sangmi Kim,et al.  Designing fair AI for managing employees in organizations: a review, critique, and design agenda , 2020, Hum. Comput. Interact..

[43]  Jan vom Brocke,et al.  Virtually in this together – how web-conferencing systems enabled a new virtual togetherness during the COVID-19 crisis , 2020, Eur. J. Inf. Syst..

[44]  C. Urquhart.  Grounded Theory's Best Kept Secret: The Ability to Build Theory , 2019, The SAGE Handbook of Current Developments in Grounded Theory.

[45]  Kalle Lyytinen,et al.  Organizing for Innovation in the Digitized World , 2012, Organ. Sci..

[46]  Cathy Urquhart,et al.  Putting the ‘theory’ back into grounded theory: guidelines for grounded theory studies in information systems , 2009, Inf. Syst. J..

[47]  Mayuram S. Krishnan,et al.  Leveraging Customer Involvement for Fueling Innovation: The Role of Relational and Analytical Information Processing Capabilities , 2017, MIS Q..

[48]  Sven Laumer,et al.  On the Untapped Value of e-HRM: A Literature Review , 2016, Commun. Assoc. Inf. Syst..

[49]  Robert F. Lusch,et al.  Service Innovation: A Service-Dominant Logic Perspective , 2015, MIS Q..

[50]  D. Strong,et al.  Affordance theory and how to use it in IS research , 2017 .

[51]  Brad McKenna,et al.  An affordance perspective of team collaboration and enforced working from home during COVID-19 , 2020, Eur. J. Inf. Syst..

[52]  Harry Scarbrough,et al.  Recombination in the open-ended value landscape of digital innovation , 2018, Inf. Organ..

[53]  Jan vom Brocke,et al.  How Big Data Analytics Enables Service Innovation: Materiality, Affordance, and the Individualization of Service , 2018, J. Manag. Inf. Syst..

[54]  Mike Wright,et al.  The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes , 2019, Research Policy.

[55]  Stefan Strohmeier,et al.  Artificial Intelligence Techniques in Human Resource Management - A Conceptual Exploration , 2015, Intelligent Techniques in Engineering Management.

[56]  Walter Fernandez,et al.  What Grounded Theory Is…A Critically Reflective Conversation Among Scholars , 2015 .

[57]  Jochen Wulf,et al.  Actualizing big data analytics affordances: A revelatory case study , 2020, Inf. Manag..

[58]  Omar A. Baakeel,et al.  The Association between the Effectiveness of Human Resource Management Functions and the Use of Artificial Intelligence , 2020, International Journal of Advanced Trends in Computer Science and Engineering.

[59]  Bengisu Tulu,et al.  A Theory of Organization-EHR Affordance Actualization , 2014, J. Assoc. Inf. Syst..

[60]  Andrew Burton-Jones,et al.  How Can We Develop Contextualized Theories of Effective Use? A Demonstration in the Context of Community-Care Electronic Health Records , 2017, Inf. Syst. Res..

[61]  Pär J. Ågerfalk.  Artificial intelligence as digital agency , 2020, Eur. J. Inf. Syst..

[62]  Rajiv Kohli,et al.  Digital innovation: A review and synthesis , 2019, Inf. Syst. J..

[63]  Patrick Mikalef,et al.  Examining the interplay between big data analytics and contextual factors in driving process innovation capabilities , 2020, Eur. J. Inf. Syst..

[64]  Robert K. Yin,et al.  Case Study Research and Applications: Design and Methods , 2017 .

[65]  Ashwani Kumar Upadhyay,et al.  Applying artificial intelligence: implications for recruitment , 2018, Strategic HR Review.

[66]  Andrew M. Hardin,et al.  Information Technology and organizational innovation: Harmonious information technology affordance and courage-based actualization , 2020, J. Strateg. Inf. Syst..