Innovative technologies and workplace collaborations in the energy sector based in the United Arab Emirates

Introduction: The UAE energy sector is navigating digital transformation mandates such as the UAE AI Strategy 2031 and Net Zero commitments, with technologies like AI, IoT and cloud computing creating new avenues for real-time coordination, data-driven decision-making and cross-functional collaboration. These oppor tunities are tempered by challenges of organisational readiness, cultural iner tia and technological integration. Yet, research on innovative practices in the UAE energy context remains limited. Therefore, this study investigates the role of AI, IoT and cloud computing in shaping workplace collaboration in the UAE energy sector. Methods: An explanatory sequential mixed-methods design was adopted which involved Phase 1 (15 October, 2024-31 January, 2025) interviews with 15 professionals in operations, IT and leadership roles from major energy companies, analysed via thematic analysis. Phase 2 (15 February, 2025-15 May, 2025) distributed a survey to a broader sample, yielding 115 valid responses, which were analysed quan titatively. The study is primarily grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT), with the Technology Acceptance Model (TAM), Resource-Based View (RBV) and Actor-Network Theory (ANT) serving as supporting interpretive lenses. Results: Findings show that AI, IoT, and cloud platforms enhance collaboration, especially in remote coordination and predictive decision sup port, but adoption is hindered by resistance to change, fragmented systems and uneven digital literacy. Discussion: Practical implications include modular rollouts, digital maturity audits and AI onboarding programs. Policy recommendations include national collaboration standards, KPI integration and incentives for joint innova tion projects.

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Publication Details

Journal
Frontiers in Artificial Intelligence
Published
2026-04-22
DOI
https://doi.org/10.3389/frai.2026.1798647
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
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article

Innovative technologies and workplace collaborations in the energy sector based in the United Arab Emirates

Sayed Abdul Majid Gilani, Ansarullah Tantry, Jack Charles Boath, Tamaralaiyefa Harold Tiemo
Frontiers in Artificial Intelligence
Organizational and Employee Performance
article

Innovative technologies and workplace collaborations in the energy sector based in the United Arab Emirates

Sayed Abdul Majid Gilani, Ansarullah Tantry, Jack Charles Boath, Tamaralaiyefa Harold Tiemo
article en

Abstract

Introduction: The UAE energy sector is navigating digital transformation mandates such as the UAE AI Strategy 2031 and Net Zero commitments, with technologies like AI, IoT and cloud computing creating new avenues for real-time coordination, data-driven decision-making and cross-functional collaboration. These oppor tunities are tempered by challenges of organisational readiness, cultural iner tia and technological integration. Yet, research on innovative practices in the UAE energy context remains limited. Therefore, this study investigates the role of AI, IoT and cloud computing in shaping workplace collaboration in the UAE energy sector. Methods: An explanatory sequential mixed-methods design was adopted which involved Phase 1 (15 October, 2024-31 January, 2025) interviews with 15 professionals in operations, IT and leadership roles from major energy companies, analysed via thematic analysis. Phase 2 (15 February, 2025-15 May, 2025) distributed a survey to a broader sample, yielding 115 valid responses, which were analysed quan titatively. The study is primarily grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT), with the Technology Acceptance Model (TAM), Resource-Based View (RBV) and Actor-Network Theory (ANT) serving as supporting interpretive lenses. Results: Findings show that AI, IoT, and cloud platforms enhance collaboration, especially in remote coordination and predictive decision sup port, but adoption is hindered by resistance to change, fragmented systems and uneven digital literacy. Discussion: Practical implications include modular rollouts, digital maturity audits and AI onboarding programs. Policy recommendations include national collaboration standards, KPI integration and incentives for joint innova tion projects.

Frontiers in Artificial IntelligenceVol. 9
Birmingham City University (GB), King's College - North Carolina (US)
Quality Education
Openalex Percentile: Top 20%
Organizational and Employee Performance
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