arbiter
JournalsPricingAccount

Beyond Skills: The Role of Professional Involvement as a Safeguard Against AI‐Driven Automation Risk

Tania Saba et al.

Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration2026https://doi.org/10.1002/cjas.70057article
AJG 2ABDC B
Weight
0.50

What the paper says

Research studies on technological change indicates a growing risk of AI‐driven job transformation. Automated systems have increasingly taken over routine tasks, shifting workers toward roles requiring advanced thinking and feeling skills. Although these skills act as barriers to automation, little is known about their development pathways. Grounded in the job replacement and conservation of resources (COR) theories, this study examines the relationship between these skills and risk of automation by AI, along with the moderating role of professional involvement. Our analysis of data gathered from 1380 Canadian workers across seven occupations using structural equation modeling (SEM) confirms that feeling skills protect against automation. Moreover, a higher level of professional involvement fosters both thinking and feeling skills, enhancing adaptability, reducing AI‐related risks, and improving AI implementation. This study offers insights for researchers, as well as for organizations and policymakers navigating AI‐driven automation.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1002/cjas.70057

Or copy a formatted citation

@article{tania2026,
  title        = {{Beyond Skills: The Role of Professional Involvement as a Safeguard Against AI‐Driven Automation Risk}},
  author       = {Tania Saba et al.},
  journal      = {Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/cjas.70057},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Beyond Skills: The Role of Professional Involvement as a Safeguard Against AI‐Driven Automation Risk

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.