The energy industry is in the midst of profound change. While companies push to reduce emissions and accelerate renewable adoption, they must also contend with high costs, operational complexity, and global uncertainty. Between 2024 and 2030, more than 5,500 gigawatts of new renewable energy capacity is expected — nearly three times the volume added between 2017 and 2023 — a scale of growth that highlights both opportunity and pressure.
Digitalisation has quickly become central to this transition. Over the past decade, technologies such as IoT devices, cloud platforms, automation, and AI — including the rise of generative AI — have created new ways of working across the energy value chain. Today, predictive maintenance, real-time monitoring, remote operations, and low-code/no-code development are not optional add-ons, but core enablers of efficiency, reliability, and agility.
Yet, the path to digital transformation remains difficult. Studies suggest that only 25–35% of energy sector programmes deliver on their objectives. The reasons are diverse — from rising costs and interoperability gaps to cybersecurity risks and poor-quality data. Beyond these technical barriers, human challenges such as resistance to change, lack of training, and ineffective change management remain among the most common causes of failure.
To better understand these dynamics, it is useful to distinguish between overlapping but distinct concepts like digital twins, digital threads, IT-OT integration, and digital programmes. At its core, digitalisation refers to deploying programmes that create measurable business impact. Digital twins, for instance, can support engineering, geospatial analysis, monitoring, or EHS, while digital threads ensure data continuity across the asset lifecycle. When implemented effectively, these initiatives move beyond technology projects to become genuine value drivers.
Real-world examples show what is possible. L&T Technology Services recently rolled out an AI-based monitoring solution across more than 70 petrochemical plants, converging IT, OT, and ET data streams. This reduced unplanned downtime by over 10% while also lowering risk during shutdowns and start-ups, periods that are especially vulnerable to safety incidents. Results like these demonstrate that digitalisation is not just about efficiency — it is about resilience and operational security.
Looking ahead, the adoption of automation, AI, and generative AI is paving the way for the “assets of the future”: systems that are self-healing, self-optimising, and built for safety. IT departments that were once seen as cost centres are evolving into engines of business value. But for this vision to become reality, enterprises must not only embrace the technology but also address the human and cybersecurity factors that determine success. The digital future of the energy sector will depend on how well people, processes, and platforms are aligned to create a greener, more sustainable industry.
