Track description
n°15

Artificial Intelligence (AI) is the defining technology of our times. It has already impacted the way we do daily chores, run our businesses, or design work (Seymour et al., 2024; Zhang et al., 2023). AI has become much more ubiquitous in our daily lives thanks to the emergence of Generative AI tools (Alavi et al., 2024; Wang et al., 2025). Firms and researchers across the world are engaged in attempts to make AI tools more human to enable more engagement between humans and these AI tools (Seymour et al., 2024). Anthropomorphism refers to the users’ (humans) perception of the AI tools as human-like (Epley et al. 2007).

Literature in Information Systems and Marketing has analyzed the role of Anthropomorphism of technological elements like robots and its impact on users’ behavior (Bahmani et al., 2022; Blut et al., 2021; Li et al., 2021). The recent advances in AI technology have made the AI-enabled human augmentation very likely and the distinction between AI and human thin (Jain et al. 2021). This leads us to the questions about AI Anthropomorphism and its role in enabling these augmentations and higher user acceptance of these technologies.

ECIS 2026 theme focuses on Reimagining Digital Technology for Business, Management and Society. We feel that understanding AI’s anthropomorphism and the role such a human like characterization has on the way people perceive these pervasive technologies will be central in designing future systems for businesses. Studies that will analyze the extent of AI Anthropomorphism, its utility, impact, and role for digital future will be interdisciplinary. It would likely draw from literature in Information Systems, Psychology, Marketing and Systems Engineering.

Creating Anthropomorphic AI tools has ethical implications as well when the ability of a user to distinguish between human and AI agents disappear. Also, the ability to generate compelling content could be exploited for malicious purposes, making it necessary to establish stricter security measures and regulations to prevent abuse. Those aspects need to be accounted for in any digital future perspective. An important aspect of AI tools’ Anthropomorphism is the cognitive and psychometric state of those tools. Pellert et al. (2023) have established that Gen AI tools can have unique psychological profiles.

This provides the basis that mass personalization of AI tools is possible where personality profiles of Anthropomorphic AI tools closely resemble users’ personality profiles for higher productivity and better augmentation. Such issues are central to Information Systems’ study of digital futures as our field can leverage interdisciplinary studies, theories, and study designs to analyze the various aspects of such Anthropomorphic AI.

AI Anthropomorphism has been a successful track at ECIS 2025 as well attracting interesting papers on the way AI technology is becoming anthropomorphic and impacting businesses and society. There has been emerging trend on research in this topic as explained by the rise of special issues on this topic as well as papers in IS (Hasan et al., 2025), management (Bas et al., 2024) and philosophy (Floridi, 2025) disciplines and hence ECIS 2026 is well placed to continue Information Systems’ perspective on this emerging research topic.

In this track, we look forward to research using diverse methodologies and theories on a variety of topics that include (but not limited to) the following:

• Does AI have personality- AI personality profiles and its impact on AI-Human interaction?
• Impact of increasing Anthropomorphism of AI tools on human psychological space
• Interaction encounters between humans and AI
• Human cognitive abilities and AI cognitive abilities matching for better productivity in AI-Human collaboration
• Technologies and designs that enable better anthropomorphic design of AI tools
• AI Anthropomorphism and Pervasiveness- Are they linked?
• Changing nature of work, productivity and human behaviour in an AI-centric world
• Changing nature of marketing and customer care with blurring of boundaries between human and Anthropomorphic AI agents
• Business process redesign to accommodate higher human AI collaboration
• Making AI more accessible to marginalized communities by creating mass personalized Anthropomorphic AI tools
• Anthropomorphism of AI and societal care role evolution
• Management and regulation of Anthropomorphic AI tools
• Ethical implications of making AI Anthropomorphic
• Novel theoretical frameworks for studying and managing Anthropomorphism of AI technologies

• Alavi, M., Leidner, D. E., & Mousavi, R. (2024). A Knowledge Management Perspective of Generative Artificial Intelligence. Journal of the Association for Information Systems, 25(1), 1-12.
• Bahmani, N., Bhatnagar, A., & Gauri, D. (2022). Hey, Alexa! What attributes of Skills affect firm value?. Journal of the Academy of Marketing Science, 50(6), 1219-1235.
• Bas, A., & Dörfler, V. (2024, August). Can AI have intuition?. In 84th Annual Meeting of the Academy of Management.
• Blut, M., Wang, C., Wünderlich, N. V., & Brock, C. (2021). Understanding anthropomorphism in service provision: a meta-analysis of physical robots, chatbots, and other AI. Journal of the Academy of Marketing Science, 49, 632-658.
• Epley, N., Waytz, A., & Cacioppo, J. T. (2007). On seeing human: a three-factor theory of anthropomorphism. Psychological review, 114(4), 864.
• Floridi, L. (2025). AI as Agency without Intelligence: On Artificial Intelligence as a New Form of Artificial Agency and the Multiple Realisability of Agency Thesis. Philosophy & Technology, 38(1), 30.
• Hasan, R., Ojala, A., Quach, S., Thaichon, P., & Weaven, S. (2025). The dark side of AI anthropomorphism: A case of misplaced trustworthiness in service provisions. In 58th Hawaii International Conference on System Sciences (HICSS 2025) (pp 5695-5704)
• Jain, H., Padmanabhan, B., Pavlou, P. A., & Raghu, T. S. (2021). Editorial for the special section on humans, algorithms, and augmented intelligence: The future of work, organizations, and society. Information Systems Research, 32(3), 675-687.
• Li, M., & Suh, A. (2021, January). Machinelike or humanlike? A literature review of anthropomorphism in AI-enabled technology. In 54th Hawaii International Conference on System Sciences (HICSS 2021) (pp. 4053-4062).
• Pellert, M., Lechner, C. M., Wagner, C., Rammstedt, B., & Strohmaier, M. (2023). AI Psychometrics: Assessing the psychological profiles of large language models through psychometric inventories. Perspectives on Psychological Science, 17456916231214460.
• Seymour, M., Yuan, L., Riemer, K., & Dennis, A. R. (2024). Less artificial, more intelligent: understanding affinity, trustworthiness, and preference for digital humans. Information Systems Research.
• Wang, L., Huang, N., He, Y., Liu, D., Guo, X., Sun, Y., & Chen, G. (2025). Artificial Intelligence (AI) Assistant in Online Shopping: A Randomized Field Experiment on a Livestream Selling Platform. Information Systems Research.
• Zhang, D., Peng, G., Yao, Y., & Browning, T. R. (2023). Is a college education still enough? The IT-Labor relationship with education level, task routineness, and artificial intelligence. Information Systems Research.

Track chairs are evaluating and discussing the opportunities for authors of accepted papers to be fast-tracked in leading journals.