AI · PRISMA systematic review of five databases (EBSCOhost, Embase, Inspec, Scopus, Web of Science).
What factors contribute to the acceptance of artificial intelligence? A systematic review
Telematics and Informatics · 2022
Summary
Perceived usefulness, performance expectancy, attitudes, trust, and effort expectancy positively predicted intention, willingness, and use across industries; in some cultural contexts human contact could not be replaced.
For your marketing
Possible founder application
Prioritize measurable usefulness and performance value, low effort, trust, and appropriate human contact in adoption experiments; do not treat stated intent as equivalent to sustained usage.
Reported result
What the study found
Perceived usefulness, performance expectancy, attitudes, trust, and effort expectancy positively predicted intention, willingness, and use across industries; in some cultural contexts human contact could not be replaced.
Research question
What the authors investigated
What research designs, theories, industries, and factors explain user acceptance of AI technologies?
Design
PRISMA systematic review of five databases (EBSCOhost, Embase, Inspec, Scopus, Web of Science).
Sample and setting
7,912 records identified; 60 studies included, spanning multiple industries and contexts; acceptance was behavioral intention or willingness to use, buy, or try AI.
Scope and transfer
Limitations to keep in view
Most reviewed studies relied on self-reported data; 31 did not define AI and 38 did not define it for participants; the authors call for naturalistic validation.
Research sources
Publisher abstract and methodology sections support the database search, 60-study sample, predictors, definitional gaps, self-report limitation, and naturalistic-research recommendation. Firecrawl research job 01a14366-d263-71d0-bc44-b95482987b7b returned this citation and metadata.