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Smart energy, responsible future: examining human–AI synergy in renewable sector

Mai Trang Le et al.

Journal of Enterprising Communities: People and Places in the Global Community2026https://doi.org/10.1108/jec-06-2025-0174article
AJG 1ABDC C
Weight
0.50

What the paper says

Purpose The renewable energy sector faces a challenge as rapidly advancing AI technology outpaces governance frameworks, creating an imbalance between using AI’s potential and maintaining environmental and social commitments. Therefore, this study aims to examine the relationship between human–AI collaboration and responsible innovation through the mediating role of knowledge integration. In addition, this study examined how digital literacy and AI ambidexterity moderate between human–AI collaboration and responsible innovation. Design/methodology/approach This study collected the primary data from 457 respondents designated as senior and middle management personnel and technical specialists in three major cities: Hanoi, Ho Chi Minh City and Da Nang. Smart-PLS software was used to analyse the primary data. Findings The results of this study revealed that human–AI collaboration, digital literacy and AI ambidexterity have a positive relationship with responsible innovation, and digital literacy has a positive relationship with knowledge integration. Knowledge integration mediates between human–AI collaboration and responsible innovation. Digital literacy does not moderate between human–AI collaboration and knowledge integration. While AI ambidexterity negatively moderates between knowledge integration and responsible innovation. Originality/value This research advances socio-technical systems theory by identifying knowledge integration as a critical bridging mechanism between human–AI collaboration and responsible innovation outcomes, challenging traditional assumptions about technology adoption benefits. The study provides first empirical evidence from Vietnamese energy professionals, addressing the critical gap between AI advancement and governance frameworks within developing renewable energy contexts.

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https://doi.org/https://doi.org/10.1108/jec-06-2025-0174

Or copy a formatted citation

@article{mai2026,
  title        = {{Smart energy, responsible future: examining human–AI synergy in renewable sector}},
  author       = {Mai Trang Le et al.},
  journal      = {Journal of Enterprising Communities: People and Places in the Global Community},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/jec-06-2025-0174},
}

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Smart energy, responsible future: examining human–AI synergy in renewable sector

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.