Joint SI Workshop

Call for Abstracts:

Artificial Intelligence in Organizations: Opportunities for Management and Implications for IS Research

Artificial Intelligence (AI) is emerging as a fundamental, pervasive economic and organizational phenomenon that holds many theoretical and practical opportunities and challenges for management and information systems scholars. Recent advances in AI have given rise to a diverse set of technologies able to perform human-like tasks such as complex decision-making, reasoning and learning, sophisticated analytics and pattern recognition, visual acuity, speech recognition and language translation as well as emotion detection [1]

Today, companies across industries increasingly rely on AI technologies to automate structured and repetitive work processes, gain insights through extensive analysis of large datasets and engage with customers and employees in new ways [2].

As the adoption of AI technologies across organizations is increasing, AI may alter working and organizing in significant ways.

The experiences of early adopters of AI technologies demonstrate that such technologies may produce no, unknown, or unexpected outcomes, raising new challenges and concerns about the long-term impact of investments in AI in organizations. Emerging challenges include addressing ethical concerns such as AI bias, trust, and transparency; altering how people and things are valued; and eroding expertise and occupational boundaries [3].

The conditions under which new human-machine configurations can or cannot have effects such as amplify human ability, perform key processes autonomously, contribute to innovativeness and affect both short-term and sustained competitive advantage remain to be explored [4].

It is therefore important to improve our understanding about the potential effects of AI technologies in organizations (such as transforming dynamics, patterns and structure of organizations, management), and the broader societal, legal, and ethical implications of AI. Advancing both practitioner and academic work in these areas is of key importance at this particular moment in time, as practitioners and academics are just beginning to understand the transformative potential of AI technologies.

This joint JAIS-MISQE special issue seeks original research on “Artificial Intelligence in Organizations: Opportunities for Management and Implications for IS Research.”

Some of the topics of interest of this joint special issue include:

  • Transformative effects of AI technologies
  • Emergence of new configurations of human-machine interactions and their impact on working and organizing
  • Failures and errors with AI technologies
  • Usage and consequences of different AI technologies (e.g., robotics, machine learning, chatbots, digital twins, etc.) across industries
  • Unintended consequences of AI implementation and use
  • Psychological, social and cultural aspects of human computer and robot interactions
  • Organizational, societal and ethical implications of AI
  • Challenges of AI for decision making
  • Impact of AI use on knowledge and expertise
  • Design approaches combining human-machine capabilities to elevate performance
  • Paradoxical effects of algorithmic technologies 
  • Embedding smart machines into products, services, strategies, cultures and behaviors

Workshop Date & Deadlines:

Sept. 1th, 2019: Submit an abstract of no more than 3 single-spaced pages of text and up to 2 figures (figures are not counted in 3 page limit) for your JAIS paper; and 3 pages for your MISQE paper in a single submission. The submission should include key phenomena and research question, methods and case material. For JAIS (e.g., theoretical and conceptual framing and expected contributions), for MISQE (e.g., conceptual framework, unique insights and lessons learned).

Oct. 26th, 2019: Notification of workshop acceptance with preliminary editorial feedback

Dec. 14th, 2019: Joint SI Workshop in Munich

Submissions should be sent to: benbya@gmail.com

You can contact Workshop and Special Issue Senior Editors:

Hind Benbya, Montpellier Business School, h.benbya@montpellier-bs.com

Sirkka Jarvenpaa, University of Texas, Sirkka.Jarvenpaa@mccombs.utexas.edu

Stella Pachidi, Cambridge University, s.pachidi@jbs.cam.ac.uk

Tom Davenport, Babson College, tdavenport@babson.edu


[1] Anderson, J, Rainie, L, and Luchsinger, A. 2018. “Artificial Intelligence and the Future of Humans” Pew Research Center, December.

[2] Davenport, T. 2018. The AI advantage: How to put the artificial intelligence revolution to work, MIT Press.

[3] Faraj, S, Pachidi, S. and Sayegh, K. 2018. “Working and Organizing in the age of the learning algorithm” Information and Organization, 28(2), pp. 62-70.

[4] Benbya, H. and Leidner, D. 2018. How Allianz UK used an Idea Management Platform to Drive Employee Innovation” MISQ Executive, 17(2), pp. 139-155; and Yan, K. Leidner, D. and Benbya, H. 2018. “Differential Innovativeness Outcomes of User and Employee Participation in Online User Innovation Communities”, Journal of Management Information Systems, 35(3), pp. 1-34.

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