What is the objective of this joint-special issue?

The joint special issue on “AI in organizations” has a dual objective:

  1. To open up the AI black box and focus on specific AI technologies and their business, organizational and socio-technical implications.
  2. To make both a theoretical contribution (targeted to JAIS) and a practice contribution (targeted to MISQE)

We seek papers that advance knowledge on:

  1. the potential effects of AI in organizations (e.g., individuals, teams, organization or multilevel) including transforming dynamics, patterns and structure of organizations and management; b) the conditions under which new human-machine configurations form and have specific effects; c) management of AI-related challenges  (e.g., AI bias, trust and transparency).
  2. Papers that do not differentiate AI from IS technologies or other emerging digital technologies, or are marginally related to AI are not a good fit with the SI.

Please refer to the call for papers for a definition of AI as well as a list of potential topics.

Can I submit to only one journal and not the other?

Submission to only one journal is not an option for this joint-special issue.

To be considered for the joint SI, authors are invited to develop two papers: a theoretical contribution for JAIS and a practical contribution for MISQE

Prospective authors may:

  • Focus on the same phenomenon
  • Use the same or different data sets
  • Use the same framing and theory in both papers but vary the emphasis and depth (different framing and research question are fine as well)
  • Not be the lead authors in both papers
  • Provide much more detail about the methodology and analysis in the JAIS version
  • Focus on how the JAIS paper either develops, extends, or otherwise improves a theory
  •  Focus on how the MISQE paper provides new insights for practice that are neither obvious nor inactionable

Where should I submit my papers and which guidelines should I follow?

Which process will be used in handling dual submissions?

The guest editors will screen initial submissions. Only the projects (dual submissions) that are aligned with the objectives of the joint SI and that have enough maturity and fit with both journals (JAIS and MISQE) will enter the review process.

Manuscripts that do not proceed to a peer review process will not get a full SE and AE report but can be submitted to the regular issues of the journal with an explanation that the initial submission was considered for the special issue. 

After the first round, if one of the papers is rejected, the project will be pulled out from the joint SI and the authors can proceed with a normal single submission.

Can I make nominations from the editorial board to handle my submissions?

As with other special issues in IS journals, nominations for Senior or Associate editors are not possible for the joint SI. Members of the editorial board of the joint SI will handle the submissions after an initial screening from the guest editors. Prospective authors are welcome to suggest reviewers.

Can you share examples of projects that resulted in both an academic and a practitioner paper?

During the workshop the EICs of JAIS and MISQE offered examples of academic pairs (papers on the same phenomenon published in an academic journal and MISQE), see some examples below:

  • Kane, G.C., Alavi, M., Labianca, G.J. and Borgatti, S., 2014. What’s different about social media networks? A framework and research agenda. MIS Quarterly, 38, 274-304.
  • Kane, G. C. (2015). Enterprise social media: Current capabilities and future possibilities. MIS Quarterly Executive, 14(1).
  • Koch, H., Gonzalez, E., and Leidner, D. (2012). Bridging the Work/Social Divide: the Emotional Response to Organizational Social Networking Systems. European Journal of Information Systems, April, 1-19.
  • Leidner, D., Koch, H., and Gonzalez, E., (2010). The Role of an Enterprise 2.0 System in Integrating Generation Y IT New Hires into the Workforce. MIS Quarterly Executive ,9(4), 229-242.
  • Preston, D., Chen, D and Leidner D., (2008). Examining the Antecedents and Consequences of CIO Decision Making Authority. Decision Sciences, 39(4), 605-642.
  • Preston, D., Leidner, D., and Chen, D., (2008). CIO Leadership Profiles: Implications of Matching CIO Authority and Leadership Capability on IT Impact. MIS Quarterly Executive, 7(2), 57-69.

Can you share exemplars from MISQE?

  • Lacity, Mary (2018) “Addressing Key Challenges to Making Enterprise Blockchain Applications a Reality,” MIS Quarterly Executive: Vol. 17 : Iss. 3, Article 3.
    Available at: https://aisel.aisnet.org/misqe/vol17/iss3/3
  • Sebastian, Ina M.; Ross, Jeanne W.; Beath, Cynthia; Mocker, Martin; Moloney, Kate G.; and Fonstad, Nils O. (2017) “How Big Old Companies Navigate Digital Transformation,” MIS Quarterly Executive: Vol. 16 : Iss. 3, Article 6.
    Available at: https://aisel.aisnet.org/misqe/vol16/iss3/6

JAIS-MISQE Workshop on AI

JAIS-MISQE Joint Special Issue workshop: “Artificial Intelligence in Organizations”

Goal:  Developmental feedback in preparation for the joint Journal of the Association of Information Systems and MIS Quarterly Executive Special Issue on:  Artificial Intelligence in Organizations

Pre-ICIS Workshop in collaboration with SIM
Saturday, December 14, 9:00 am-5 pm

Location: H4 Hotel München Messe, Munich

9:00 am Registration and coffee, breakfast on your own

9:30 am Welcome and Workshop kick off- Hind Benbya, Montpellier Business School

9:40-10:25 Workshop Keynote: Dr. Shivaji Dasgupta, Head of Artificial Intelligence and Smart Data, Deutsche Bank

10:25-10:50 Panel: Making Theoretical and Practical Contributions: Similarities & Differences Dorothy Leidner, Editor-In-Chief JAIS, Gabe Piccoli, Editor-In-Chief MISQE Moderator: Sirkka Jarvenpaa, University of Texas at Austin


Slam Presentations (5mn per presentation)  
1) Development of an Artificial Intelligence Ecosystem: Case study of iFlytek, Cheuk Hang Au, Barney Tan, Xuetao Wang, Yuan Sun

2) Decision delegation behaviors to algorithms in strategic decision contexts: A mixed method study, Michael Leyer, Sabrina Shneider

3)  Design of customer-facing chatbot applications, Mark Grimes, Ryan Schuetzler, Justin Giboney

4) Humanistic Deployment of AI through Harnessing the Fast & Flow Phenomenon      Omar Elsawy, Pernille Rydén

5) Chatbot Resistance in the Health Care Sector: An Empirical Examination from the Physicians’ Perspective, Lea Müller; Jens Mattke; Dr. Christian Maier

6) Inter-linkage between the material and the virtual in AI Sven-V. Rehm, Iris Junglas, Lakshmi Goel, Niall Connolly, Giovanni Maccani, Shane  McLoughlin, Abhinay Puvvala

7) The Role of Human Cognition and Mental Capabilities in Setting Up, Konstantin Hopf, Nora Fteimi, Thorsten Staake, Franz Lehner

8) Unpacking the Journey Toward Artificial Intelligence in an Organization, Abayomi Baiyere, Copenhagen business school

9) Anthropomorphization of AI is Changing the Human- Algorithmic Relationship, Tim Crone, Jonas Valbjørn Andersen, Mahmood Shafeie Zargar, Bart van den Hoof

10) The pursuit of data driven value creation in organizations, Oliver Müller, Arisa Shollo, Konstantin Hopf, Tiemo Thiess

12:00-13:00 Lunch

13:00-13:15 Break

13:15 Introduction to afternoon session, Stella Pachidi, University of Cambridge

13:25-14:55 1st Table Discussions

Table 1, Theme: Issues of ethics and effectiveness in Conversational AI
Facilitators:  Jason-Bennet Thatcher and Gabe Piccoli

When better is not better: Designing conversational AI for consumer-facing applications Mark Grimes, Ryan Schuetzler, Justin Giboney  

Usability of Voice-based Conversational Recommendation Agents in Online Shopping. Why Type When I Can Talk? Ransome Epie Bawack, Samuel Fosso Wamba, Kevin Carillo

“Raffi”, an Adaptive Conversational Agent Based on User’s Personality Rangina Ahmad, Dominik Siemon  

Table 2, Theme: Organizing for AI
Facilitators:  Stella Pachidi & Dorothy Leidner

The Development of an Artificial Intelligence Ecosystem: An Actor-Network Perspective Cheuk Hang Au, Barney Tan, Xuetao Wang, Yuan Sun  

Humanistic Deployment of AI through Harnessing the Fast & Flow Phenomenon Omar El Sawy, Pernille Rydén  

Managing Conflicting Requirements for Explainable AI in Organizations Aleksandre Asatiani, Pekka Malo, Esko Penttinen, Tapani Rinta-Kahila, Per Rådberg Nagbol, Antti Salovaara  

Table 3, Theme: AI implementation
Facilitators:  Ivo Blohm & Iris Junglas

Will We Be Replaced? Exploring Employees’ Resistance Towards AI Implementation Yu-Qian Zhu, Yi-Te Chiu, Jacqueline Corbett  

Learning to tango with productivity analytics – the emerging co-regulation of work practice with AI, Jocelyn Cranefield, Cathal Doyle, Alexander Richter, Michael Winikoff  

Does AI Matter?Resistance to AI-Driven Change in Organizations, Stefan Stieglitz  

Table 4, Theme: Materiality of AI
Facilitators:  Ulrike Schultze & Yolande Chan

How do you know what I need? Defining requirements in developing artificial intelligence for litigation Jochem T. Hummel, Lauren Waardenburg, Zhewei Zhang, Joe Nandhakumar

Developing a Structural Theory of Virtual Materiality Sven-V. Rehm, Iris Junglas, Lakshmi Goel, Niall Connolly, Giovanni Maccani, Shane McLoughlin, Abhinay Puvvala  

Medical Decision Making with Artificial Intelligence: a Sociomaterial Perspective | An Exploration of Ethical Issues in Advanced Analytics Cristina Trocin  

Table 5 Theme: AI Systems Design
Facilitators:  Aron Lindberg & Hope Koch

Designing Chatbot-based Learning Systems for Long-Term Use in Formal Educational Setting Florian Berens and Sebastian Hobert

Are Two Better Than One? Hybrid Intelligence as a New Design Approach for Complex Decision Making Philipp Ebel, Engel Christian  

Unpacking the Journey Toward Artificial Intelligence in an Organization, Abayomi Baiyere  

Summary of paper discussions

15:15-17:00 2nd Table Discussions

Table 1, Theme: Human-AI interaction
Facilitators:  Monideepa Tarafdar & Nils Urbach  

Collaboration of human and artificial intelligence in decision-making: The implications of machine agency on managerial job design, Michael Leyer, Sabrina Shneider  

Let the Machine Evaluate Your Idea – Evaluation Apprehension in Human- Machine Interaction, Dominik Siemon  

Trust Me I am Human: How the Anthropomorphization of AI is Changing the Human- Algorithmic Relationship, Tim Crone, Jonas Valbjørn Andersen, Mahmood Shafeie Zargar, Bart van den Hoof  

Effects of AI on Decision Making, Peter G. Roetzel, Ralf J. Ostendorf, Mario Smeets

Table 2, Theme: Impact of AI on work 1
Facilitators:  Ivo Blohm & Iris Junglas
AI identity, its antecedents and implications for job performance
Mamta Bhatt, Azadeh Savoli
Combinatoric reorganization in management occupations as
machines take on cognitive tasks
Shiyan Zhang, Michael zur Muehlen, Jeffrey V. Nickerson
Α Theoretical Framework for a Successful Design and Implementation of a Visual Analytics Tool to Enhance Clinical Decisions at the Point of Care
Tsipi Heart, Ofir Ben-Assuli, Robert Klempner, Rema Padman

Table 3, Theme: Strategic perspectives on AI
Facilitators:  Mikko Siponen & Hind Benbya
Identifying the New AI and Data Driven Value Chain in Insurance: Evaluating 10 Case Studies from 5 Continents, Alex Zarifis, Ian Herbert, Chris Holland
How to sense opportunities through AI-enabled systems: Insights from three predictive maintenance cases, Keller Robert, Ollig Philipp, Rieger Alexander, Stohr Alexander
The pursuit of data driven value creation in organizations:
A typology of data science projects and facilitators in the value creation, Oliver Müller, Arisa Shollo, Konstantin Hopf, Tiemo Thiess

Table 4, Theme: Impact of AI on work 2
Facilitators:  Aron Lindberg & Hope Koch
Artificial Intelligence Impacts on Organizations and Work: A Delphi Study with AI Experts, Sergi Pauli, Cesar Alexandre de Souza, Crispin Coombs
The role of the learning algorithm in the practice of routine:
The strategy of Human-AI hybrid, Anson CH Huang, Tzu-Chuan Chou, Sheng-Hsiung Wu
Affordance Actualization of Artificial Intelligence: What makes the difference? Anne Sophie Mayer
Table 5, knowledge management and decision making in the era of AI
Facilitators:  Sirkka Jarvenpaa & Yolande Chan
Typology of Chatbot Resistance in the Health Care Sector: An Empirical Examination from the Physicians’ Perspective
Lea Müller; Jens Mattke; Dr. Christian Maier
The Role of Human Cognition and Mental Capabilities in Setting Up Artificial Intelligence
Konstantin Hopf, Nora Fteimi, Thorsten Staake, Franz Lehner
The Interplay of People, Technology, and Organizational Practices in Algorithmic Decision Making: An Experimental Study with Reviewing Loan Application
Anh Luong, Nanda Kumar, Karl R. Lang

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.