Positioning AI-Driven Technologies as Support for Effective Workplace Collaborations: A Study Based on the Oil and Gas Sector in the United Arab Emirates (UAE)

The UAE oil and gas sector is undergoing a significant digital transformation, driven by national initiatives such as the UAE AI Strategy 2031 and Net Zero commitments. Technologies including AI, IoT and cloud computing are enabling enhanced real-time coordination, data-informed decision-making and improved cross-functional collaboration. However, these advancements are constrained by organisational readiness challenges, cultural resistance and integration complexities. Despite growing adoption, empirical research on innovative digital practices within the UAE energy context remains limited. This study, therefore, examines the role of AI, IoT and cloud computing in influencing workplace collaboration in the UAE oil and gas sector through an exploratory sequential mixed-methods approach. Phase 1 involved interviews with 15 professionals in operations, IT and leadership roles from major energy companies, analysed via thematic analysis. Phase 2 distributed a survey to a broader sample, yielding 115 valid responses, which were analysed quantitatively. 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. Findings show that AI, IoT and cloud platforms enhance collaboration, especially in remote coordination and predictive decision support, but adoption is hindered by resistance to change, fragmented systems and uneven digital literacy. Practical implications include phased implementation of digital platforms to reduce resistance to change, targeted digital literacy programmes to address capability gaps and integration of AI-driven decision-support tools to enhance cross-functional coordination. At the policy level, the findings suggest the need for formalised collaboration frameworks across energy entities, alignment of performance metrics with digital integration objectives and support for cross-organisational innovation initiatives. The study contributes to digital engineering and applied AI literature by demonstrating how integrated AI, IoT and cloud architectures support coordination across distributed energy systems, offering system-level insight into technology-enabled collaboration in complex operational environments.