AMR Special Topic Forum - Artificial Intelligence in Management
Deadline: 1 October 2024
Editors: Sebastian Raisch, Robert W. Gregory, Keith Leavitt, Dana Minbaeva, Alex Murray, Jennifer D. Nahrgang, & Anastasiya Zavyalova
In a rapidly evolving business technology landscape, artificial intelligence (AI) has emerged as a transformative force in management. The predictive capabilities of AI have equipped managers with data-driven foresight, enabling them to monitor and anticipate market trends, business risks, customer preferences, and employee behaviors, thereby facilitating more evidence-based decisions. However, as we explore the future of management, we recognize that the potential of AI extends beyond prediction. The emerging generative capabilities of AI represent a leap forward, fostering creativity and enabling innovative ideas, designs, and solutions. With its user-friendly interface, generative AI makes it easier for a broader swath of the population to get involved in AI-enabled problem solving. The synergies between the predictive and generative capabilities of AI are undeniable. Predictive insights fuel generative processes, while generative outputs enhance predictive accuracy. This powerful extension of AI, from prediction machines to generative problem-solvers, presents the potential for AI to transform a host of conventional management practices, heralding an era where artificial agents complement and potentially replace managers and knowledge workers in a variety of organizational settings. These developments have the potential to fundamentally alter the nature of the firm, the future of work, and management theories.
The Academy of Management Review (AMR) invites scholars to contribute to a Special Topic Forum (STF) on AI’s multifaceted role in management and organization theory. Theoretical exploration is paramount to advance our understanding of how AI is reshaping the organizational landscape and redefining management as we know it. The STF seeks to tackle essential research questions at multiple levels of theorizing. At the micro level, researchers could delve into how predictive and generative AI applications alter key managerial tasks, such as communication, decision making, employee engagement, problem solving, and innovation. At the meso level, scholars might explore how organizations leverage predictive and generative AI for new strategies, structures, and capabilities. At the macro level, scholars could scrutinize the ethical, regulatory, and societal ramifications of integrating AI into organizations’ day-to-day management.
We welcome submissions that enrich our conceptual understanding of AI’s role in management and organizations within and across levels. Specifically, we encourage submissions from diverse and/or interdisciplinary teams.
Research questions in this STF could include but are not limited to the following:
- Decision making and problem solving: How does predictive AI augment managers’ cognitive processes and decision-making strategies? In what ways does generative AI alter the nature of problem solving in organizations? Can AI help identify and formulate problems? How does the presence of AI affect the biases and heuristics observed in human decision-making processes within organizations? To what extent does the generation of new data solve AI’s traditional challenges of data availability and quality in decision making?
- Work roles, employee skills, and managerial practices: How does the emergence of predictive and generative AI change the nature of work? What new work roles do organizations create and which employee skills gain or lose importance? In what ways can the use of AI enhance or hinder employee productivity, motivation, job satisfaction, and skill development? How can AI reduce barriers and contribute to more inclusive organizations? What managerial practices should be put in place to prevent potential negative consequences? How do these practices influence employees’ trust and reliance on AI systems?
- Creativity and innovation: What is predictive and generative AI’s impact on creativity and innovation? How do organizations manage the interplay between AI-generated ideas and the inherently unpredictable nature of breakthrough innovation? How can organizations foster an environment where generative AI enhances human creative thinking and entrepreneurial spirit?
- Teams, communication, and coordination: How does the inclusion of artificial agents change team structures, processes, and dynamics? What role does generative AI play in enabling communication and coordination within and across organizations? How does the increasing presence of chatbots in the managerial domain influence communication patterns and knowledge transfer? What is the role of AI in fostering or impeding interpersonal relationships at work?
- Management of social evaluations: How do predictive and generative AI affect the processes through which organizational reputations are built, damaged, and repaired? How has AI changed the ways through which organizations become stigmatized or destigmatized? What are the pathways through which AI allows organizations to gain celebrity (or become infamous) and how do these pathways differ from those in the pre-AI era? How has AI affected perceptions of third-party certifications’ credibility and rankings’ validity, and with what consequences for organizations’ social evaluations?
- Strategy, business models, and capabilities: In what ways do AI-based prediction and generation transform traditional business models and enable new ones? How do organizations strategically reposition themselves in response to AI-driven disruption in their markets? How can firms develop unique capabilities and create competitive advantages using predictive and generative AI? Does the joint deployment of predictive and generative AI help organizations balance the dual needs for efficiency gains and strategic innovation?
- Organizational structures, practices, and routines: What organizational designs facilitate the integration of AI into organizational practices and routines? How does the integration of predictive and/or generative AI technologies, in turn, influence the design and evolution of organizational structures, hierarchies, and reporting relationships? How could organizations effectively manage the transition from traditional practices and routines to AI-enabled ones?
- Societal implications: What theoretical perspectives can illuminate predictive and generative AI adoption’s ethical and social implications, such as equality, intellectual property, privacy, and security concerns? How do organizations navigate the ethical dilemmas related to AI technologies? How does AI support or hinder the ability of corporations, international organizations, and social movements to address grand challenges and other social problems? What are the positive and negative implications of AI adoption on the planet, such as, for example, its impacts on water consumption, carbon emissions, and deforestation?
- Governance, stakeholders, and institutions: How can organizations develop and implement AI governance frameworks that ensure transparency, fairness, and compliance with legal and ethical standards? In what ways do organizations establish effective mechanisms for stakeholder engagement in the development of AI governance policies, particularly in contexts where technology outpaces regulatory frameworks? How do institutional arrangements change through organizations’ increasingly widespread use of predictive and generative AI?
Timeline and Submission
The deadline for submissions is 1 October 2024 at 23:59 ET (DST+1,UTC-4). All submissions must be uploaded to the Manuscript Central website between 1 September and 1 October 2024. Guidelines for contributors and the AMR Style Guide for Authors must be followed. To answer questions from authors who are planning to submit to the STF, a team of guest editors will host online Q&A sessions in April 2024. Participation in the Q&A sessions and is not a prerequisite for submitting your paper to AMR and does not does affect the manuscript review process and outcome.
For questions about submissions, contact AMR’s Managing Editor. For questions about the content of this STF, contact Sebastian Raisch, Robert W. Gregory, Dana Minbaeva, Keith Leavitt, Alex Murray, Jennifer D. Nahrgang, or Anastasiya Zavyalova.
