AI and the Future of Work
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Item Artificial Intelligence in the Workplace a Paradox: Contributor to Loneliness and Enhancer of Organisational and Employee Health(2025-01-07) Patel, Roshni; Peko, Gabrielle; Sundaram, DavidThe utilization of artificial intelligence (AI) is on the rapid rise in organizations across the world. The perceived benefits of AI, such as enhanced operations, improved efficiency, and a driver of growth, are some reasons for its increased adoption. The side effects of leveraging AI on people are becoming apparent, and one of these is loneliness. Loneliness can be the cause of or exacerbate mental and physical health issues. This paper outlines the current state of loneliness contributed by AI usage in the workplace. This paper hopes to inform future research to ideate AI solutions that ameliorate said issues. The Job Demands–Resources model and Bright ICT Initiative taxonomy are drawn on to inform the study. Causal loop diagrams are utilized to understand the effect of AI on mental and physical health. We leverage systems thinking to understand the issues and identify appropriate solutions for ameliorating loneliness in the workplace.Item A Collaborative Creative Process in the Age of AI: A Comparative Analysis of Machine and Human Creativity(2025-01-07) Boo, Chaeeun; Kim, Yeongseo; Suh, AyoungSince the emergence of generative AI, there has been an ongoing debate about whether AI can engage in creative activities or possess creativity, yet questions persist about what machine creativity is and how it differs from human creativity. To address this gap, this study conducts a systematic literature analysis examining the evolving discourse on machine creativity and the conceptual distinctions and intersections between human and machine creativity. Our analysis of 52 selected studies reveals insights into how creativity is perceived and manifested differently by machines compared to humans, suggesting that while machine creativity is novel and original, it lacks the intentionality and authenticity of human creativity. Based on this literature analysis, we propose a theoretical framework where human and machine creativity coexist. It offers implications for effectively integrating AI into creative processes, providing both academic insights into the attributes of machine creativity and practical guidance on integrating AI into creative practices.Item Framing Patterns of Generative AI: An Exploratory Survey of Utilization, Benefits, and Challenges(2025-01-07) Von Brackel-Schmidt, Constantin; Leible, Stephan; Gücük, Gian-Luca; Simic, DejanOrganizations and individuals are still identifying new and value-adding utilizations for generative artificial intelligence (GenAI) that offer great potential. Simultaneously, the introduction in organizations and private spheres is at a momentum in which promises and fears are communicated via various (informal) networks. Both lead to different attitudes towards GenAI. Given the passage of time and the ongoing progress, it is to be expected that the experimentation phase will follow a broad and structured deployment. Consequently, organizations must pay attention to suitable utilization scenarios and the attitudes of those potentially affected by GenAI to enable a successful deployment. Therefore, we surveyed utilization scenarios and attitudes towards GenAI. Building on this, we derived a structured overview of GenAI utilizations and identified four attitude (frame) patterns towards GenAI ranging from negative to enthusiastic. Our results contribute to explorative knowledge and can aid research and practice when dealing with human-centered GenAI utilization and deployment.Item AI Identity Threats and Reinforcement in Organizations: A Theoretical Model of Professional Role Identity Implications(2025-01-07) Richter, Janek; Schaller, RenaThe ever-increasing dissemination of artificial intelligence (AI) and the increasing trend for natural interaction with humans holds significant potential to influence professionals’ identity. There is conflicting evidence in literature for the reinforcing as well as threatening effect of AI on identity. We investigate implications of AI on the identification process of professionals in organizations. Based on the extant literature, we develop a nuanced framework that clusters AI identity shaped by positive identification, anti-identification, dis-identification, and ambivalent identification. Based on these results, we formulate propositions on AI identity for future research.Item Generative AI across the Corporate Hierarchy: The Disparity of Emotions, Attitudes, Social Norms and Usage(2025-01-07) Hornstein, Patricia; Born, Nadja; Treffers, Theresa; Welpe, IsabellOrganizations can unlock numerous benefits by using generative artificial intelligence (AI). Thus, understanding the predictors driving its usage is crucial. Psychological factors such as emotions, attitudes, and norms play a key role. Research has examined these for employees and leaders separately; however, without comparing them across the hierarchy. This is important as research has discovered hierarchical differences in these factors regarding several organizational phenomena, such as digital readiness. Disparities may result in disregarded concerns, leading to a decline in trust and motivation. Building on identity theory, we examine differences in emotions, attitudes, and norms toward generative AI across the hierarchy. Our results show that high-level employees exhibit more excitement, less perceived threat, and stronger norms, yet this does not translate into higher usage. This study highlights the risk of leaders falling into impression management, given their low usage rates, and warns against disconnected levels based on discrepancies in psychological factors.Item Are Entrepreneurial Employees More Inclined to Accept Artificial Intelligence? An Extension of the UTAUT2(2025-01-07) Pomrehn, Larissa; Göttel, VincentAlbeit the increased use of artificial intelligence (AI) in organizations, the understanding of how employees perceive its introduction and which factors play a role in their usage intentions and behavior is still underdeveloped. This study draws on the UTAUT2 by Venkatesh et al. (2012) to investigate AI acceptance by employees in more detail. Structural equation modeling results of a survey with employees (N = 224) reveal that age, gender, experience, and attitude towards AI show partially moderating effects for the UTAUT2 measurements. We analyze how employees’ entrepreneurial mindset influences their usage intention, as we expect entrepreneurially-minded individuals to perceive AI introduction differently. We find ambiguous results regarding entrepreneurial mindset as creativity, propensity to risk, and the perceived entrepreneurial benefits as well as attitude show moderating effects, both strengthening and weakening UTAUT2 relationships. This study contributes theoretical implications towards extending the UTAUT2 with moderators as well as practical implications for organizations.Item Employee Affective Reactions to Algorithmic Management: How Does Context and Algorithm Transparency Matter?(2025-01-07) Pomrehn, Larissa; Wehner, MariusThe use of algorithmic management (AM) expands continuously, whereas knowledge about the influence of context and algorithm transparency on employee affective reactions to AM is still underdeveloped. To fill these voids, this study draws on the affective response model (Zhang, 2013) and examines the role of different contexts (i.e., work allocation, training allocation, performance evaluation) and levels of algorithm transparency (i.e., high vs. low) for the relationship between the decision-entity (human vs. algorithm) and employee reactions. Results of a vignette study with German employees (N = 354) showed that employees had more positive reactions to AM in training allocation compared to work allocation, whereas both levels of algorithm transparency had similar effects on reactions in the AM condition. Our results shed light into the intricacies of AM reactions, guiding future research directions. Practitioners can leverage these insights to determine contextual nuances of AM and refine consequent communication strategies.Item Human-AI Teams' Impact on Organizations - A Review(2025-01-07) Latto, Chloe; Richter, Alexander; Tate, MaryAs Generative Artificial Intelligence (AI) is encroaching further on our work and social environments, we examine the increasingly common situation where teams of white-collar workers include both humans and AI. We explore three key themes via a comprehensive (n=122) systematic literature review: key success factors, use cases for human-AI teams, and challenges faced when implementing human-AI teams. The key success factors identified discuss the need for clear roles and responsibilities by playing to human and AI strengths, skill development and system transparency. Use cases can be grouped into problem-solving, decision-making, routine tasks, and personal assistants. Finally, the identified challenges relate to system trustworthiness, biases, time and effort to adopt, AI using data, and job insecurity. We conclude by identifying avenues for future research based on the gaps identified throughout this review.Item Leveraging Generative Artificial Intelligence for Design Thinking in Creative Processes: A Literature Review(2025-01-07) Zemke, Hendrik; Stahmann, Philip; Janiesch, ChristianGenerative artificial intelligence (GenAI) is diffusing in various business contexts to support and complement human work. Its capabilities to generate information in different formats, such as texts, images or videos enable it to support creative processes in business. Creativity supports the adaptation to changing conditions and fosters innovative problem-solving. Our research aims to investigate concrete support potentials of GenAI in Design Thinking processes. To this end, we conducted a structured literature review and tailored the resulting GenAI potentials to Design Thinking phases. In terms of practical implications, our results provide usage potential of GenAI to foster organizational creativity in a structured manner. For theory, we derive implications on responsible use of GenAI with regards to creativity, where authorship, intellectual property, and the reduction of model-induced bias constitute major challenges.Item Consulting in the Age of AI: A Qualitative Study on the Impact of Generative AI on Management Consultancy Services(2025-01-07) Tronnier, Frederic; Bernet, Robin; Löbner, Sascha; Rannenberg, KaiThe business model of management consultancies (MCs) traditionally relies on human expertise to address complex challenges of clients. Generative artificial intelligence (GenAI) has the potential to enhance efficiency and optimize processes in traditionally personalized and knowledge-intensive domains. By employing qualitative content analysis on 15 interviews with consultants from various MCs, this qualitative study investigates the impact of GenAI on the business model (BM) of MCs. Various subcategories for value creation, value proposition and value capturing, impacted by GenAI, are derived. The findings suggest that GenAI enhances process efficiencies, automates routine tasks and optimizes knowledge management, allowing consultants to focus on higher-value, creative tasks. New opportunities to reduce cost and to create additional revenue streams are identified, that come with additional challenges. The continued need for human-driven insights and client relationships remains critical, indicating that generative AI is viewed more as a strategic complement, rather than a replacement for consultants.