Borouge International scales AI and digitalization globally

Key highlights
  • Targets $100 million in AI and digitalization value generation by 2027.
  • Signed strategic partnerships with Microsoft, Emerson, Immensa and Cognite at ADIPEC 2026.
  • Deployed an RTO in the UAE across three ethane crackers and 20 furnaces, analysing over 2,500 parameters per minute.
  • AI-powered autonomous operations proof of concept at Ruwais showed up to 20% efficiency gains, 20% less downtime and up to 15% lower operating costs.

Scope and objectives

Borouge International is accelerating deployment of artificial intelligence and digitalization across production, innovation, supply chain, logistics and customer engagement. The initiative, supported by the integration of Borouge, Borealis and NOVA Chemicals, targets $100 million in value generation by 2027 and aims to improve operational availability, productivity, decision-making and HSE performance.

Partnerships announced

At ADIPEC 2026 the company signed strategic partnerships with Microsoft, Emerson, Immensa and Cognite to accelerate global deployment and scaling of AI and digital solutions across its value chain.

Industrial deployments and results

Borouge has deployed a large Real-Time Optimisation system in the UAE across three ethane crackers and 20 furnaces that analyses more than 2,500 parameters per minute to support faster data-driven decisions, higher productivity, lower energy consumption and reduced emissions. The RTO is planned for rollout to facilities worldwide, including North America. A live proof of concept for AI-powered autonomous operations at Ruwais, developed with Honeywell, indicated potential improvements of up to 20% in efficiency, 20% reduction in downtime and up to 15% lower operating costs, while enhancing process safety and reducing energy use and emissions.

Scaling model and technologies

The company pursues a 'build once, scale globally' approach to replicate proven AI&D solutions across its footprint. Technologies cited for scaling include machine learning for forecasting, digital twins for predictive maintenance and 3D printing for industrial additive manufacturing and supply-chain efficiency.

Source: Borouge

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