From Data to Impact: Scaling AI and Digital Twins for Efficient Projects and Reliable Assets
At Future Digital Twin & AI (Amsterdam) 2025, Shubham Rajvanshi, Senior Director & Client Partner at L&T Technology Services, outlined a roadmap for scaling AI and digital twins across capital projects and operational assets. He highlighted the pivotal role of trusted, high-quality data as the foundation for achieving efficient, reliable, and sustainable outcomes in the energy and industrial sectors.
Drawing from global experience and real-world deployments, Rajvanshi addressed the barriers of legacy infrastructure, siloed data, and organisational resistance, showcasing modular, AI-powered solutions that enable transformation at scale. These included predictive maintenance frameworks, anomaly detection, generative design, asset health monitoring, and real-time operational dashboards—all seamlessly integrated into digital twin platforms.
Through case studies, such as a multi-site chemical industry rollout and a $40B energy investment in the Middle East, Rajvanshi demonstrated tangible impact: reduced maintenance costs, improved productivity, and smoother project-to-asset handovers. He also emphasised hybrid AI frameworks, combining domain expertise with data science, as key to creating scalable, cloud-native platforms that support real-time, lifecycle-wide decision-making. The session closed with a forward-looking perspective on clean energy, cybersecurity, and operating model redesign as enablers of a resilient digital future..
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