Best friend or broken tool? Exploring the co-existence ofhumans and artificial intelligence in the workplace ecosystem

Katja Einola, Violetta Khoreva*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

25 Citations (Scopus)


Artificial intelligence (AI) has become an important topic in business literature and strategy talk. Yet, much of this literature is normative and conceptual in nature. How organizational members perceive AI and the job role changes that come with it is, so far, largely unknown territory for both HR scholars and practitioners. We sought to investigate the relationship between humans and AI and conducted an in-depth exploratory study into the co-existence of humans and two early-stage AI-solutions, one for “low-status” automation and another for “high-status”; augmentation. We suggest that different organizational groups may engage in distinctly different sensemaking processes regarding AI, an important insight for successful HRM strategies when AI is being introduced into the workplace. Moreover, contrary to recent conceptual work, our findings indicate that AI-enabled automation and augmentation solutions may not be detached from nor exist in tension with each other. They are deeply embedded in organizational processes and workflows for which people who co-exist with the technologies must take ownership. Our findings, in part, go against discussions on AI “taking over” jobs or deskilling humans. We describe a more nuanced version of reality fluctuating around the various ways different organizational groups encounter different AI-solutions in their daily work. Finally, our study warns against unconditional technological enthusiasm, managerial ignorance of the nature of work that employees undertake in different organizational groups, and a neglect of the time and effort required to successfully implement AI-solutions that affect not only the home organization but also members of the broader ecosystem.
Original languageEnglish
Peer-reviewed scientific journalHuman Resource Management
Issue number1
Pages (from-to)117-135
Number of pages19
Publication statusPublished - 05.10.2022
MoE publication typeA1 Journal article - refereed


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