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TRUVACE RECORD VERSION
record: TRV-2026-2550
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T07:52:43.049328Z
status: published
lens: trace
sector: labor
headline: The suppressing effect of AI dependency in the workplace: Can frequent use of AI enhance practitioners' job self‐efficacy?
dek: Abstract Artificial intelligence (AI) is rapidly becoming a primary channel through which employees access information and solve problems at work. Drawing on media dependency theory, we theorize that workplace AI use exerts a suppressing effect on practitioners' job self‐efficacy in task‐focused achievement contexts. Specifically, AI use can directly bolster job self‐efficacy by facilitating task accomplishment. At the same time, frequent AI use may foster AI dependency, reducing employees' engagement in compete…
gain_title: In a time-lagged field study and a scenario experiment, frequent workplace AI use was directly associated with higher job self-efficacy among practitioners, because it helped them accomplish tasks.
problem_title: In the same field study and experiment, AI dependency carried a negative indirect effect on job self-efficacy, weakening employees' mastery-based confidence by reducing their engagement in competence-relevant cognitive work.
trace_subject: Workplace AI use, AI dependency and employees' job self-efficacy
gain_reading: In a time-lagged field study and a scenario experiment, frequent workplace AI use was directly associated with higher job self-efficacy among practitioners, because it helped them accomplish tasks.
gain_evidence: workplace AI use showed a positive direct association with job self‐efficacy
problem_reading: In the same field study and experiment, AI dependency carried a negative indirect effect on job self-efficacy, weakening employees' mastery-based confidence by reducing their engagement in competence-relevant cognitive work.
problem_evidence: AI dependency carried a negative indirect effect | weakening mastery‐based confidence
quick_read: A multi-source, time-lagged field study and a scenario experiment examined how using AI at work affects practitioners' confidence in their own job abilities. Workplace AI use showed a positive direct association with job self-efficacy, while AI dependency carried a negative indirect effect, producing a significant suppressing effect.

The authors, drawing on media dependency theory, argue that frequent use can breed dependency, which reduces the competence-relevant cognitive work through which people build mastery-based confidence. AI is becoming a primary channel through which employees get information and solve problems, so the pattern bears on how organizations deploy it.

Proactive feedback to AI, meaning employees actively giving the system feedback, weakened the negative effect of dependency. At higher levels of that feedback, the suppressing effect was no longer significant.
limitation: 
tag: Dual reading
key_points: The research combined a multi-source, time-lagged field study with a scenario experiment. | Workplace AI use was positively and directly associated with job self-efficacy because it helps people complete tasks. | AI dependency had a negative indirect effect on job self-efficacy, creating a significant suppressing effect. | The proposed mechanism is that dependency reduces engagement in competence-relevant cognitive work and weakens mastery-based confidence. | Proactive feedback to AI acted as a boundary condition that attenuated the harm of dependency. | At higher levels of proactive feedback, the suppressing effect became nonsignificant.
rundown: The study applies media dependency theory to workplace AI, treating it as a main channel through which employees obtain information and solve problems. It theorizes two competing processes: a direct route in which AI helps task accomplishment and raises job self-efficacy, and an indirect route through dependency that lowers it.

Results from both the time-lagged field study and the scenario experiment supported this competing-process account. The positive direct association and the negative indirect effect together produced what the authors call a suppressing effect, in which dependency partly offsets the confidence gains from AI use.

Proactive feedback to AI emerged as the key boundary condition. It reduced the negative effect of dependency on job self-efficacy and made the suppressing effect nonsignificant at higher feedback levels, which the authors present as a way for organizations to gain performance benefits while protecting employees' perceived capability.
sources:
- peer_reviewed | Applied Psychology | https://doi.org/10.1111/apps.70121 | 2026-07-09
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