AVEVA Says AI Can Raise Industrial Output by 3% to 5% Without Major New Investment

Naif Bou Chaaya, AVEVA's vice president for the Middle East, Africa, Turkey and Central Asia, told WAM that the company is exhibiting at the energy show for the fifth year in a row. This year, he said, its focus is on AI applications developed with customers to improve operating efficiency, cut energy use and emissions, and support decarbonisation.

Bou Chaaya named predictive maintenance built on AI and machine learning as one of the company's most important offerings. The models analyse data from industrial assets and equipment to learn how they normally behave, so operators can anticipate failures and act before they happen. He said this reduces unplanned shutdowns, keeps production running and improves the safety of workers and operations.

He said more than 90 percent of leading industrial organisations rely on AVEVA, which supplies software for oil and gas, power, water and other sectors across the whole asset lifecycle, from design and construction to operation and maintenance.

Data Before Technology

Bou Chaaya said AI projects depend mainly on the quality of the data behind them. Incomplete or inaccurate data can produce unreliable results even with the latest AI, he said, so companies need accurate, organised and connected data gathered in one system that the organisation trusts as its reference.

He recommended a set order for adoption. Companies should first define the operational or economic value they want, then assess the data they have and its quality, and only then choose the AI technology, rather than starting with the technology.

His comments came the same week ADNOC's upstream chief said the company's Neuron 5 AI tool has halved unplanned shutdowns. Both point to the same trend: Gulf energy producers are looking to software and AI to get more out of existing assets.