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TRUVACE RECORD VERSION
record: TRV-2026-0390
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-07-20T10:13:41.693262Z
status: published
lens: g_space
sector: labor
headline: How does artificial intelligence impact employees’ engagement in lean organisations?
dek: Driven by the digital transformation currently pursued by organisations, artificial intelligence (AI) applications have become more frequent. Nevertheless, its impact on employees’ behaviors and attitudes is still poorly known. As employees’ engagement (EE) is a key element for a successful Lean Production (LP) implementation, there is the need to understand such AI’s implications on EE in this scenario. This paper aims to investigate the impact of AI on EE in lean organisations. We performed a qualitative-empir…
gain_title: In lean manufacturing organizations, AI applications may increase employees' engagement across physical, cognitive and emotional dimensions and improve psychological conditions of safety, meaningfulness and availability.
problem_title: (none)
trace_subject: (none)
gain_reading: In lean manufacturing organizations, AI applications may increase employees' engagement across physical, cognitive and emotional dimensions and improve psychological conditions of safety, meaningfulness and availability.
gain_evidence: AI may positively impact EE dimensions (physical, cognitive, and emotional) in human-centred work environments, such as lean organisations | employees psychological conditions (safety, meaningfulness, and availability) are positively affected by the relationship between AI and EE
problem_reading: (none)
problem_evidence: (none)
quick_read: Researchers investigated how AI applications affect employees' engagement in lean organisations, combining twelve academic expert interviews with a multi-case study of manufacturing firms implementing Lean Production, and formulated propositions for future testing.

The reported positive link matters for lean manufacturing workplaces where engagement is critical to success, but because the evidence is qualitative and confined to manufacturing lean contexts, the extent and transferability of benefits remain to be validated.
limitation: Findings are based on a qualitative design with twelve academic experts and a multi-case study limited to manufacturing organisations undergoing Lean Production implementation, limiting generalizability beyond that context.
tag: Evidence-backed gain
key_points: Study used qualitative-empirical design with twelve academic expert interviews followed by multi-case study in manufacturing firms implementing Lean Production. | Findings suggest positive effects on engagement dimensions but not to the same extent across physical, cognitive and emotional aspects. | Authors frame results as propositions for future theory testing to help anticipate issues impairing Lean Production in the Fourth Industrial Revolution.
rundown: The authors first interviewed twelve academic experts to explore how AI relates to engagement, then refined insights through a multi-case study in manufacturing organisations undergoing Lean Production implementation.

They report commonalities across stages leading to propositions that AI can support engagement dimensions and psychological conditions in human-centred lean work environments, aiming to help practitioners anticipate implementation issues.
sources:
- peer_reviewed | International Journal of Production Research | https://doi.org/10.1080/00207543.2024.2368698 | 2024-07-01
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