Building the data infrastructure for AI in energy

Without a strong data foundation, AI initiatives in energy quickly stall. Many organisations still struggle with fragmented datasets, legacy systems and unclear ownership, making it hard to build consistent, reliable models. Accenture found that only 32% of leaders report having achieved sustained, enterprise-wide AI impact. Leading organisations are modernising data architectures, including data lakes and real-time platforms, to create unified, interoperable environments while managing cloud, security and governance trade-offs. Some are treating data itself as a commercial asset, building models that generate new revenue streams or reduce costs across the value chain. The gap between current capability and that goal is primarily one of governance and organisational will, not technology. Organisations that resolve these challenges establish the foundation for scalable, high-value AI deployment.