Table 5 Subjective and theoretical... | Emerald Publishing

Table 5

Subjective and theoretical contributions to the notion of meaningful work in human-AI environments

Subjective contribution	Empirical results (from ideal types)	Key-literature	Theoretical contribution
Autonomy as bounded	Ideal Type [1]: the Efficiency-Seeking employees impose boundaries on AI use to safeguard autonomy; AI is valued but kept subordinate	Raisch and Fomina (2024), Yeoman (2014), Laaser and Karlsson (2021)	Extends Laaser and Karlsson’s framework by showing that autonomy is actively curated through cognitive containment
Recognition and interpersonal relationships	Ideal Type [2]: the Pragmatic Integrator employees appreciate AI assistance but fear loss of peer interaction and interpersonal validation	Bailey et al. (2019), Laaser and Karlsson (2021), O’Neill et al. (2020), Faulconbridge et al. (2025)	Reveals a paradox of meaningfulness where AI-enabled efficiency may erode dignity rooted in social recognition
AI as co-creator in value construction	Ideal Type [3]: the Collaborative Optimiser employees see AI as a partner; AI helps shape professional judgement and recognition	Orlikowski and Scott (2008), Baptista et al. (2020), Laaser and Karlsson (2021)	Challenges the mediator role of AI by showing it participates in value and expertise recognition
Algorithmic mediation and new paradox of meaningfulness	Ideal Type [3]: Despite high agency perception, system design and prompting shape decisions and recognition	Bailey et al. (2019), Laaser and Karlsson (2021), Raisch and Fomina (2024)	Suggest the emergence of a new paradox: perceived autonomy coexists with algorithmic constraint—meaningfulness is co-authored yet asymmetrically shaped
Prompting as hybrid cognitive-relational labour	Ideal Type [3]: Prompting becomes a dynamic process involving knowledge articulation, delegation, and identity shifts	Adam et al. (2024), Brown (2015), Orlikowski and Scott (2008)	Expand on the notion of prompting as labour involving epistemic, metacognitive, and identity dimensions—reframing how expertise is enacted

Subjective contribution	Empirical results (from ideal types)	Key-literature	Theoretical contribution
Autonomy as bounded	Ideal Type [1]: the Efficiency-Seeking employees impose boundaries on AI use to safeguard autonomy; AI is valued but kept subordinate	Raisch and Fomina (2024), Yeoman (2014), Laaser and Karlsson (2021)	Extends Laaser and Karlsson’s framework by showing that autonomy is actively curated through cognitive containment
Recognition and interpersonal relationships	Ideal Type [2]: the Pragmatic Integrator employees appreciate AI assistance but fear loss of peer interaction and interpersonal validation	Bailey et al. (2019), Laaser and Karlsson (2021), O’Neill et al. (2020), Faulconbridge et al. (2025)	Reveals a paradox of meaningfulness where AI-enabled efficiency may erode dignity rooted in social recognition
AI as co-creator in value construction	Ideal Type [3]: the Collaborative Optimiser employees see AI as a partner; AI helps shape professional judgement and recognition	Orlikowski and Scott (2008), Baptista et al. (2020), Laaser and Karlsson (2021)	Challenges the mediator role of AI by showing it participates in value and expertise recognition
Algorithmic mediation and new paradox of meaningfulness	Ideal Type [3]: Despite high agency perception, system design and prompting shape decisions and recognition	Bailey et al. (2019), Laaser and Karlsson (2021), Raisch and Fomina (2024)	Suggest the emergence of a new paradox: perceived autonomy coexists with algorithmic constraint—meaningfulness is co-authored yet asymmetrically shaped
Prompting as hybrid cognitive-relational labour	Ideal Type [3]: Prompting becomes a dynamic process involving knowledge articulation, delegation, and identity shifts	Adam et al. (2024), Brown (2015), Orlikowski and Scott (2008)	Expand on the notion of prompting as labour involving epistemic, metacognitive, and identity dimensions—reframing how expertise is enacted

Source(s): Authors’ own work