tech
AI efficiency gains come at a high energy cost
Simply sign up to the Artificial intelligence myFT Digest -- delivered directly to your inbox.
TL;DR
- Energy efficiency, despite being cost-effective, is underused due to complexity and time constraints in identifying waste.
- AI can analyze vast datasets to identify inefficiencies and make adjustments, particularly in large industrial operations.
- Progress in global energy efficiency targets is slowing, especially in industry, where the financial case is clear.
- Barriers to adoption include the less visible and rapid results of efficiency investments compared to renewables, and the complexity of equipment upgrades.
- AI combined with digital twin technology can simulate facility operations, test changes virtually, and accelerate efficiency adjustments.
- Studies show AI-powered digital twins can significantly cut unplanned downtime, increase energy production, and reduce energy costs.
- AI's own energy consumption must be weighed against the efficiency gains it enables.
- AI alone is not a solution; systems need to be ready, and it works best with electrification, infrastructure investment, and supportive policy.