When AI become infrastructure
AI is becoming part of how energy organisations operate. It is helping improve forecasting, optimise assets, support decisions and manage increasingly complex systems.
But as AI becomes embedded in operations, the question changes. It is no longer just about what AI can do. It is about what happens when your operations start to depend on it.
That dependency brings new questions around infrastructure, capacity, resilience and trust. AI relies on data, cloud platforms, models, suppliers, OEM systems and the connections between IT and OT. A weakness in any of these can have consequences far beyond the original system.
The sector is not heading towards fully autonomous energy infrastructure overnight. But the shift is already underway, and organisations need to understand where AI is becoming operationally significant – and what proof they need before relying on it.
In this webinar, AECOM and Resillion will explore where AI is already creating value for energy organisations, and what happens as that value becomes dependency.
You’ll find out:
Where AI is already changing energy operations, from forecasting and optimisation to asset and infrastructure management
What greater reliance on AI means for capacity, resilience and critical assets
How AI dependencies extend across data, cloud, models, suppliers, OEMs and IT/OT environments
When a useful AI capability becomes an operational dependency – and what changes when it does
What evidence, assurance and controls organisations should have in place before trusting AI with consequential decisions
How to think about AI for energy and energy for AI as two sides of the same challenge
You’ll leave with a clearer view of where your organisation is building around AI, what that means for the infrastructure and operations supporting it, and whether you have the evidence needed to trust those dependencies.
