Digital Supply Chain and AI Integration in Energy Infrastructure

AVEVA is showcasing its CONNECT industrial intelligence platform to help the energy sector integrate engineering, operations, and enterprise data across the physical asset lifecycle. The technology supports oil, gas, and renewable energy operators in strengthening grid resilience, optimizing performance, and meeting regional decarbonization targets through a continuous digital supply chain.

Operational Data Integration and Decarbonization Metrics
The Middle East manages a significant portion of global oil output while actively pursuing large-scale emission reductions, including a target to cut emissions by 47 percent by 2035 from 2019 levels. To remain aligned with 2050 net-zero targets, the United Arab Emirates has committed to tripling its renewable energy capacity, backed by investments of up to AED 200 billion by 2030. Achieving these production and sustainability metrics requires continuous tracking of industrial environments to prevent unplanned downtime and eliminate data blind spots. Nayef Bou Chaaya, Vice President for Middle East, Turkey & Central Asia at AVEVA, noted that combining raw data and embedding intelligence across energy systems is required to maintain energy resilience, affordability, and operational scaling.

System Architecture and Predictive Asset Optimization
The CONNECT platform functions as the data architecture for the design, build, operation, and optimization phases of industrial assets. At the ADIPEC 2026 exhibition (November 2–5, 2026, at the ADNEC Centre in Abu Dhabi), the system's integration with industrial workflows is being demonstrated through data-centric engineering, digital twin foundations, and AI-driven asset health monitoring. Operators can integrate their own large language models with industrial data utilizing the CONNECT MCP Server. Additionally, software modules including Unified Supply Chain, Process Optimization, and Predictive Asset Optimization enable operators to run what-if scenarios and anticipate mechanical or process issues across the value chain.

During the event, AVEVA Chief Executive Officer Caspar Herzberg is scheduled to address the strategic conference on November 3 in Plenary Hall B regarding technology partnerships and the energy landscape. On the same day, Moresh Wankhede, Director of AI Strategy and Adoption, will detail the platform's artificial intelligence capabilities in the AI Auditorium. The primary system demonstrations located in Hall 4 (booth #4410) focus on these software suites, while a dedicated AI Zone in Hall 13 demonstrates natural-language processing applications for querying operational equipment data and predicting failures.

Digital Twin Deployment and Telemetry Analytics
In application, ADNOC utilizes these systems to extract operational value from localized industrial data. Furthermore, in collaboration with regional partner Al Masaood Energy (Hall 4, booth #4210), the platform supports a living digital twin that merges engineering and operational data to generate a 360-degree view of facility energy consumption and emissions. The system's capacity for high-speed data management, data visualization, and performance analytics is also utilized in high-frequency environments like motorsports, where it processes race and vehicle telemetry for the Porsche Motorsport Formula E team—a partnership utilized during their 2025/26 Drivers' and Manufacturers' World Championship titles.

Additional Context
This section details technical specifications and competitive benchmarking not included in the original news release.

Within the industrial data ecosystem, AVEVA’s CONNECT platform competes with other enterprise-level industrial IoT and data integration platforms, such as Siemens Insights Hub (formerly MindSphere), Cognite Data Fusion, and GE Vernova’s Proficy software suite. Competitive benchmarking in this sector typically evaluates the capacity for high-frequency time-series data ingestion (often measured in millions of data points or "tags" per second), the breadth of industrial protocol support (such as OPC UA, MQTT, and Modbus), and the ability to contextualize unstructured data into relational knowledge graphs. While platforms like Cognite emphasize DataOps and contextualization for heavy asset industries, AVEVA's architecture builds heavily on its OSIsoft PI System heritage, focusing on real-time operational data management, historian capabilities, and native integration with engineering and process simulation environments.

Edited by Aishwarya Mambet, Induportals Editor, with AI assistance.

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