Accelerating project delivery with AI and connected technologies

Nayef Bou Chaaya, vice president for the Middle East, Turkey and Central Asia at industrial software company AVEVA, discusses the growing power demand from data centres, the evolution of AI deployment and how the CONNECT platform improves project delivery and reduces inefficiencies

Growing investment in AI infrastructure across Saudi Arabia and the UAE is expected to increase electricity consumption as energy companies accelerate digitalisation and expand production capacity. The rapid expansion of artificial intelligence data centres across the Middle East is driving demand for electricity, adding pressure on regional energy producers to increase capacity while improving efficiency and reducing emissions, according to AVEVA.

Bou Chaaya said the growing number of data centres being developed across the region, particularly in Saudi Arabia and Abu Dhabi, would reshape energy requirements over the coming years.

"Electricity is increasing, as we see, because of the data centres that are being built in the regions," Bou Chaaya said in an exclusive interview with Oil Review Middle East on the sidelines of ADIPEC 2026 in Abu Dhabi.

The increase in power demand comes as regional governments invest in AI infrastructure, cloud computing and digital technologies, creating additional requirements for reliable electricity supplies alongside existing industrial and commercial consumption.

Bou Chaaya expects conventional energy production to remain important, while renewable energy, natural gas and carbon capture technologies play an increasing role in meeting demand and reducing emissions. The challenge for energy producers will be to expand electricity generation while maintaining operational reliability, improving efficiency and supporting the transition towards lower-carbon energy sources.

For AVEVA, which provides industrial software to energy companies, the shift is creating opportunities to deploy digital technologies across power generation, oil and gas production and industrial infrastructure.

AI moves beyond pilot projects

While AI infrastructure is contributing to rising electricity demand, the technology is also becoming increasingly important in helping energy companies manage their operations.
Bou Chaaya said the Middle East's energy sector was moving beyond small-scale AI experiments towards large deployments capable of delivering measurable improvements in operational performance.

Predictive analytics, which uses artificial intelligence and machine learning to identify potential equipment failures before they occur, has emerged as one of the most mature applications.

Over the past two to three years, energy companies have moved from testing the technology on approximately 10 assets to implementations covering as many as 10,000, according to Bou Chaaya.

The technology allows operators to monitor equipment conditions, analyse historical performance and identify early warning signs of potential failures. By anticipating maintenance requirements, companies can prevent unexpected shutdowns, protect production levels and improve workplace safety. Reducing unplanned shutdowns can also help lower emissions and energy consumption associated with operational disruptions.

Bou Chaaya said major energy companies were increasingly recognising the commercial benefits of predictive analytics and moving towards wider implementation.
The transition reflects a broader shift in the industry's approach to AI, with companies increasingly focused on demonstrating financial and operational returns rather than experimenting with emerging technologies.

Digital platforms improve project delivery

At ADIPEC 2026, AVEVA showcased its industrial intelligence capabilities, including its CONNECT platform, which integrates engineering, construction and operational information across the lifecycle of industrial assets.

Bou Chaaya said connecting these processes through a shared digital platform could significantly improve project delivery and reduce inefficiencies caused by disconnected systems.

Traditionally, engineering design, construction and operations have relied on separate teams and databases, creating challenges when technical information needs to be transferred between project stages.

AVEVA's technology aims to address these gaps by providing a common information platform that allows different teams to access and work with the same data. One application involves AI-assisted engineering design, including the routing of pipelines and equipment within complex industrial facilities.

Designing infrastructure such as a refinery requires engineers to coordinate extensive networks of pipelines, machinery and supporting systems. Bou Chaaya said AI-enabled engineering tools could reduce the number of people required for certain design tasks while accelerating completion times. Digital integration can also shorten the handover process between engineering and operations, which can traditionally take six to nine months. By reducing repeated verification and allowing teams to work from consistent information, companies can accelerate project delivery and bring industrial assets into operation sooner.

The technology is particularly relevant as the Middle East expands its energy infrastructure to accommodate rising electricity demand and new industrial developments.

Clean data key to AI adoption

Despite growing investment in artificial intelligence, Bou Chaaya said data quality remained one of the biggest challenges facing energy companies seeking to scale the technology.

"Most important, AI is proper data. It's clean data," he said.

Industrial operators collect significant volumes of information from production equipment, engineering systems and operational facilities, but much of it remains fragmented across different platforms. AVEVA is focusing on integrating these sources into a unified information environment, allowing companies to analyse data more effectively and generate reliable operational insights.

Bou Chaaya also highlighted the importance of developing workforce capabilities alongside technological investment. As AI becomes more widely embedded in industrial operations, engineers and technical specialists will need the skills to interpret its recommendations, verify results and intervene when necessary. He said subject matter experts would become increasingly important in ensuring that AI-generated outputs are accurate and appropriate for complex industrial environments.

For energy companies facing growing demand from data centres and other electricity-intensive industries, the combination of reliable data, skilled personnel and AI-enabled operations could become critical to maintaining supply security.

As the region expands its digital infrastructure, Bou Chaaya expects the energy sector to continue investing in gas, renewable energy and emissions-reduction technologies while accelerating the adoption of AI.

The challenge will be to ensure that the technology driving new electricity demand can also help energy producers operate more efficiently, reliably and sustainably.