Skip to content
J·BJon BishopIndependent growth marketer

AI · Full-text open-access qualitative meta-synthesis/systematic review

Factors influencing artificial intelligence adoption in human resource management: a meta-synthesis and systematic review of multidimensional considerations

Journal of Work-Applied Management · 2026

Mohammad Pedrami, Seyed Kamal Vaezi

Summary

Five themes organize adoption factors: organizational/strategic, technological/operational, human-centric, challenges/opportunities, and environmental/economic; ethical and legal considerations were especially prominent. For a founder, use this as a question to test in your own context, not a universal playbook.

For your marketing

Possible founder application

Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.

Reported result

What the study found

Five themes organize adoption factors: organizational/strategic, technological/operational, human-centric, challenges/opportunities, and environmental/economic; ethical and legal considerations were especially prominent.

Research question

What the authors investigated

Which multidimensional factors influence AI adoption in HRM?

Design

Qualitative meta-synthesis systematically analyzing qualitative and quantitative studies published from 2015 to 2023.

Sample and setting

Peer-reviewed AI-in-HRM studies published 2015–2023; the accessible article synthesizes the selected literature rather than a new respondent sample.

Scope and transfer

Limitations to keep in view

Qualitative meta-synthesis depends on the included literature and search/synthesis choices; the publisher article does not report a new field sample.

Research sources

Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.

Prefer to write? Send Jon a message.