December 14, 2025 [ Oilandgasmiddleeast ]- AI is revolutionising oil and gas project management in the Middle East, enhancing efficiency, safety, and strategic decision-making while supporting national energy and sustainability goals.

rtificial intelligence (AI) is rapidly reshaping project management in the Middle East’s oil and gas sector, offering unprecedented opportunities while presenting unique challenges, according to Gert Kloeck, co-founder of Kairos.

Kloeck is also a volunteer member of the Association for Project Management (APM), which recently completed a study on the use of AI in project management.

“In the Middle East, where mega-projects intersect with ambitious national visions, AI is emerging as both a strategic enabler and a complex challenge. Its potential to transform project management is vast, but realising that potential requires overcoming structural, cultural and technological hurdles,” Kloeck explains.

He adds that one of AI’s most impactful contributions is in enhancing decision-making. By analysing real-time data and applying predictive models, project managers can anticipate delays, cost overruns and even equipment failures before they occur.

“Digital twins and predictive maintenance systems are already providing operational foresight, reducing downtime and extending asset lifecycles,” Kloeck notes.

AI also drives efficiency and cost optimisation. Intelligent scheduling and resource allocation tools have been shown to cut project delays by up to 40% and accelerate returns on investment by as much as 25%.

Generative design and virtual prototyping further reduce costly rework, allowing projects to move from planning to execution with greater speed and precision. Safety and compliance are equally critical, Kloeck says, noting that computer vision systems and smart personal protective equipment (PPE) enhance on-site monitoring, while automated documentation and risk modelling streamline regulatory compliance.

“The result is a safer workforce and stronger accountability across operations,” Kloeck says. He points to ADNOC’s HSECockpit.ai platform, as an example, which has reportedly reduced incident frequency by 25%.

Beyond operations, Kloeck notes that AI adoption aligns with national transformation agendas such as Saudi Arabia’s Vision 2030 and the UAE’s Masdar City.

Embedding AI into project management allows oil and gas companies to improve performance while contributing to broader economic diversification and energy transition goals.

“AI enables data-driven execution across the value chain. From seismic interpretation and reservoir modelling to supply chain logistics, AI tools process vast datasets that would be impossible to manage manually. At Kairos, this is our prime focus, as projects generate terabytes of data, which used to largely remain untapped. AI-enabled tools can transform this data into actionable insights,” Kloeck adds.

Despite its promise, he warns that AI adoption comes with challenges, especially as data quality and integration remain major barriers. Legacy systems, fragmented documentation and inconsistent data formats often undermine AI reliability. Building accurate digital twins, for example, requires validated and unified data across every project phase. Workforce readiness is another concern.

“Successful AI deployment depends on teams equipped with skills in data science, digital workflows and AI tools. Resistance to change and limited digital literacy can slow adoption, making cultural transformation as important as technological investment,” Kloeck explains.

Infrastructure is also a critical consideration. Many facilities still rely on aging systems that must be modernised to support AI applications. Integrating IoT devices, sensors and cloud platforms is essential, but the capital investment required can be significant. Cybersecurity and governance risks also rise with digitisation. AI systems handle sensitive operational and financial data, making robust security frameworks and data privacy critical to maintaining trust.

“Across the region, there is a strong focus on creating sovereign clouds to safeguard these assets,” Kloeck notes, though he highlights that Middle Eastern organisations are addressing these challenges through targeted initiatives.

Upskilling programmes, partnerships with AI providers, and AI Centres of Excellence are building technical capability.

Saudi Aramco, for example, partners with Cloudera to train local talent, while SAS has pledged $1 billion globally, focusing on Saudi Arabia, to support AI education. Digital system integrators are helping integrate AI into existing workflows, ensuring tools operate on structured, validated data. Platforms such as ADNOC’s Neuron 5 and ENERGY.ai demonstrate how AI can move from experimental pilots to core operational systems, enabling predictive maintenance, anomaly detection, and automated decision-making in real time.

Additionally, Kloeck notes that data privacy and governance remain non-negotiable. UAE and Saudi regulatory frameworks, such as the UAE’s Federal Decree-Law No. 45 of 2021 and Saudi Arabia’s PDPL, provide clear standards for responsible data handling. Secure AI architectures and blockchain integration enhance integrity, traceability and trust, particularly for cross-border collaborations.

AI is also transforming strategic decision-making in the sector. Predictive models optimise drilling schedules, equipment usage and workforce deployment, ensuring resources are allocated efficiently even in remote or offshore environments.

Machine learning models improve forecasting, integrating historical consumption, market trends and geopolitical signals to predict demand and prices more accurately. Risk management is becoming predictive rather than reactive, with AI monitoring equipment health, simulating financial and operational scenarios, and reducing human error in high-stakes environments.

Supply chain optimisation, sustainability, and compliance are also benefiting. AI supports real-time logistics tracking, smarter contract pricing, emissions monitoring, energy optimisation, and automated regulatory reporting.

“AI-driven sustainability planning ensures that operations are aligned with national visions such as the UAE’s Net Zero 2050 and Saudi Arabia’s Vision 2030,” Kloeck says, adding that this alignment strengthens trust with governments, investors and communities, positioning companies as partners in long-term transformation.”

Ensuring AI outputs are accurate and trustworthy relies on a combination of technology, governance, and human oversight. Digital twins provide validated data, AI governance committees enforce ethical standards, and rigorous testing with historical and simulated scenarios ensures reliability.

Cross-functional teams of data scientists, engineers, and project managers collaborate to interpret insights and make actionable decisions. Embedded cybersecurity and compliance safeguards protect data integrity and support regulatory adherence.

Overall, Kloeck emphasises that ethical, safe, and value-driven AI requires embedding principles at every stage. Organisations must scrutinise training data to mitigate bias, ensure transparency, safeguard privacy, and maintain human oversight. Structured governance frameworks, technical standards, sustainability considerations, cultural alignment, and workforce literacy all underpin responsible AI adoption in oil and gas project management.

“AI may be transforming project management, but trust remains a human responsibility,” Kloeck concludes.