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

2026-06-16 · Source: Artificial Intelligence · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Human Resources & Workforce Development · Depth: Expert, quick

Summary

The study investigates GenAI adoption within a multinational tech company's Human Resources department, specifically during a transition from a legacy search system to a GenAI-supported one. Analyzing search log data, survey data (n=25), and ten semi-structured interviews, the research found that adoption depended on the GenAI system's design assumptions aligning with employees' work positionalities, including role, spoken language, and tenure. Trust in GenAI answers was cultivated through source-checking, comparing systems, and consulting colleagues or HR. The findings provide empirical evidence that GenAI adoption is influenced by situational fit, search literacy, trust calibration, content quality, employee training, and guidance, offering design considerations for inclusive deployment in high-stakes environments like HR.

Key takeaway

For HR Professionals or Directors of AI/ML deploying GenAI in high-stakes environments, you must prioritize system design that aligns with diverse employee roles, languages, and tenure. Focus on building trust through transparent source-checking mechanisms and treating your organizational knowledge infrastructure as a core AI component. This approach ensures inclusive adoption and improves accountability and usability for your workforce.

Key insights

GenAI adoption in HR hinges on system-employee fit, trust calibration, and robust organizational knowledge infrastructure.

Principles

• Adoption depends on system-design fit with employee positionalities.
• Trust in GenAI is built via source-checking and peer consultation.
• Organizational knowledge infrastructure is critical AI infrastructure.

Method

The study analyzed search log data, survey data (n=25), and ten semi-structured interviews during a live organizational transition from a legacy HR search system to a GenAI-supported system.

In practice

• Design GenAI systems considering role and context-sensitive benefits.
• Improve accountability and usability by treating organizational knowledge as AI infrastructure.

Topics

• GenAI Adoption
• Human Resources AI
• Sociotechnical Systems
• Trust Calibration
• Organizational Knowledge
• Human-Computer Interaction

Best for: Executive, AI Scientist, AI Product Manager, Research Scientist, Director of AI/ML, HR Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence.