Why will out-of-the-box AI fail in energy and utility operations?
Why will out-of-the-box AI fail in energy and utility operations?
Mark Simpson contributed a thought leadership piece to Energy Sustainability Solutions on AI adoption in energy and utility operations.
The article covers:
Why adoption is rising but many initiatives remain stuck in pilots, with the UK Clean Energy AI review citing poor data observability and fragmented systems as barriers
Limits of out-of-the-box AI on estates not designed for AI-driven operations, and on models trained on public data rather than proprietary engineering and asset knowledge
Strengthening foundations first: data accessibility, connected systems, and architectures that support deployment at scale
Targeted use cases tied to clear outcomes (documentation, regulatory reporting, asset information, field knowledge) rather than organisation-wide rollouts
Governance, auditability, and explainability as operational requirements for maintenance, outage, and network decisions on regulated infrastructure
