AI Adoption Across a Multinational Workforce: Sociotechnical Conditions for GenAI Acceptance in Human Resources

arXiv:2606.17887v1 Announce Type: cross Abstract: Generative AI (GenAI) deployment in the workplace is accelerating rapidly. Nevertheless, questions of who adopts, who benefits, and who is left behind and why are still understudied. In this paper, we investigate these dynamics in the context of a multinational tech company transitioning from a legacy Human Resources (HR) search system to a GenAI-supported system, analyzing search log data, survey data (n=25), and ten semi-structured interviews. Our findings show that adoption depended on the fit between the GenAI system's design assumptions an
The rapid acceleration of GenAI deployment in workplaces makes understanding adoption dynamics crucial, as companies transition from legacy systems to AI-supported solutions.
This research provides early empirical evidence on who adopts and benefits from GenAI within multinational corporations, highlighting key sociotechnical conditions for successful integration in HR.
The understanding of GenAI adoption shifts from broad theoretical discussions to specific factors influencing acceptance and integration within a critical corporate function like HR.
- · AI-powered HR tech developers
- · Companies with adaptable workforces
- · Early GenAI adopters demonstrating ROI
- · Legacy HR system providers
- · Companies with rigid organizational structures
- · Workforces resistant to new AI tools
Increased pressure on HR departments to effectively integrate GenAI for talent management and operational efficiency.
A widening gap between companies that successfully leverage GenAI and those struggling with adoption, impacting competitive advantage.
The emergence of new training and change management paradigms specifically tailored for rapid, widespread AI adoption across diverse global workforces.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.AI