The impact of AI Adoption on engineers’ Job Satisfaction and Organisational Culture: A Systematic Literature Review and Roadmap for Engineering Education

Document Type

Article

Source of Publication

Journal of Engineering Education Transformations

Publication Date

2-1-2026

Abstract

This systematic review examines the impact of artificial intelligence (AI) adoption on the engineer’s well-being, job satisfaction, and the overall organisational culture. Our unconventional review is based on corporate data from leading consultancy firms such as PWC and Mackensy and 200 peer-reviewed articles that address the organisational environment for engineers in major industries such as energy, construction, and telecommunications. While AI enhances operational efficiency and skill development for engineers and supports the organisational culture, it concurrently exacerbates stress, autonomy erosion, and emotional labour in control-oriented environments. Our review pointed out six interconnected dimensions: (1) AI as opportunity versus threat, (2) gigification versus full automation, (3) emotional labour under algorithmic control, (4) human skills’ enduring relevance, (5) participatory implementation, and (6) ethical safeguards. These themes were conceptualised based on a mixed framework of Job Demands-Resources (JD-R) and Socio-Technical theories to explain how the workplace culture mediates AI’s psychosocial impacts on engineers. Our study presents evidence-based recommendations for human-centric AI integration in areas of co-design protocols, continuous upskilling, and transparent governance structures. This paper contributes to the foregrounding gap on “how AI reshapes the engineer’s well-being and the organisational culture as a whole”. It also has replicable findings for technical jobs that have a similar context to the engineers serving in the energy, construction, and telecommunication industries.

ISSN

2349-2473

Publisher

Rajarambapu Institute of Technology

Volume

39

Issue

Special Issue 3

First Page

79

Last Page

90

Disciplines

Business | Computer Sciences

Keywords

Artificial intelligence, Computer Engineering Occupation, Engineering Education, Job Demands-Resources Model, Job Satisfaction, Organisational Culture, Socio-Technica Theory

Scopus ID

105033728553

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Gold: This publication is openly available in an open access journal/series

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