Energy and chemicals companies accelerate investment in AI for smarter operations

In recent months, energy and chemicals companies have intensified their investments in AI-driven smart operational strategies. This shift is largely motivated by ongoing uncertainties surrounding global energy demand and the rapid advancements in Generative AI technology. Companies see opportunities in smart operations to increase efficiency by leveraging applications such as equipment failure prediction and condition-based maintenance programs. However, while many of these initiatives are prompted by necessity, there is a contest among business units to innovate, which often leads to poorly coordinated efforts that impede successful scaling of technologies across entire enterprises. The interconnected nature of smart operations means that a single technological upgrade can have cascading implications across various business functions and operational units. For instance, employing drone surveillance for equipment inspections instead of traditional on-site personnel not only streamlines the inspection process but also requires a robust foundation of IT infrastructure, cybersecurity measures, and employee training to realize its full benefits. Companies must therefore assess their digital transformation strategies to ensure all components, from IT to operations technology (OT), align with their overall business objectives. This investment in AI does not merely emphasize technology; rather, it calls for a holistic transformation that encompasses human elements, including workforce readiness and process adjustments. A structured approach to integrating IT and OT can facilitate a smooth transition, addressing both technological advancements and enabling a workforce equipped with the necessary skills to operate within this evolving framework. Companies may rely on comprehensive models like the Deloitte Global FoF framework to develop this structured approach and to build investment strategies that take into account both current limitations and future possibilities. As competitors continue to experiment with different use cases for AI, the potential to enhance operational metrics and overall efficiency increases, making successful implementation vital. Ultimately, the transition to smart operations in energy and chemicals hinges not just on adopting new technologies but on fostering a culture of coordination, training, and strategic foresight to successfully navigate the complex landscape of digital transformation.