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TRUVACE RECORD VERSION
record: TRV-2026-2606
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T08:01:54.923012Z
status: published
lens: p_space
sector: labor
headline: Augment or replace? AI implementation and employee job insecurity
dek: Purpose This research aims to investigate how front-of-house artificial intelligence (AI) implementation (human replacement vs human augmentation) affects job insecurity among tourism and hospitality employees. Design/methodology/approach Three scenario-based experiments were conducted with hospitality and tourism employees from the United States and the United Kingdom. Data were collected via Prolific. ANOVA and PROCESS modeling were adopted to analyze the data. Findings The results demonstrate that AI implemen…
gain_title: (none)
problem_title: In three scenario-based experiments with US and UK hospitality and tourism employees, front-of-house AI increased job insecurity, and replacing staff produced more insecurity than augmenting them.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: In three scenario-based experiments with US and UK hospitality and tourism employees, front-of-house AI increased job insecurity, and replacing staff produced more insecurity than augmenting them.
problem_evidence: AI implementation significantly increased job insecurity either directly or indirectly through perceived threats to identity value | Human replacement led to greater job insecurity than human augmentation
quick_read: Three scenario-based experiments with hospitality and tourism employees from the United States and the United Kingdom found that front-of-house AI increased job insecurity. The effect appeared directly and indirectly, through employees' perceived threats to the value of their professional identity.

Framing mattered: scenarios in which AI replaced human staff produced greater job insecurity than scenarios in which AI augmented them. Even AI intended to augment workers raised insecurity, which suggests that reassurance about augmentation may not fully protect staff.

Organizational support did not significantly moderate the pathway through identity threat, while technology readiness did play a significant moderating role. Employees' own comfort with technology therefore appeared to shape how threatened they felt.
limitation: The findings come from scenario-based experiments with online participants recruited via Prolific, rather than from observation of workers whose employers have actually introduced AI.
tag: Evidence-backed problem
key_points: The research used three scenario-based experiments rather than observing real workplaces. | Participants were hospitality and tourism employees from the United States and the United Kingdom, recruited via Prolific. | Data were analyzed with ANOVA and PROCESS modeling. | AI implementation raised job insecurity directly and through perceived threats to identity value. | Human replacement produced greater job insecurity than human augmentation. | Organizational support did not significantly moderate the mediation through identity threat. | Technology readiness played a significant moderating role.
rundown: The study examined front-of-house AI in tourism and hospitality, comparing implementations designed to replace human workers with those designed to augment them. It measured how each affected employees' job insecurity.

Researchers ran three scenario-based experiments with employees from the US and UK, collecting data through Prolific and analyzing it with ANOVA and PROCESS modeling.

Results showed AI implementation increased job insecurity both directly and through perceived threats to identity value. Replacement scenarios produced more insecurity than augmentation scenarios, though augmentation still raised it.

Organizational support did not significantly moderate the identity-threat mediation, but technology readiness did, so employees more ready for technology responded differently from less ready colleagues.
sources:
- peer_reviewed | International Journal of Contemporary Hospitality Management | https://doi.org/10.1108/ijchm-08-2025-1290 | 2026-07-10
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