Smarter charging, smaller bills
Artificial intelligence is quietly transforming how we power our cars — and a major new UK trial shows just how big the impact could be.
The Centre for Net Zero (CNZ), part of Octopus Energy, has completed a year-long study involving more than 13,000 households using its Intelligent Octopus Go tariff. The results are striking: AI-managed charging reduced peak electricity use by 42% and delivered savings of up to £650 per year compared with standard flat-rate tariffs.
By automatically shifting charging to off-peak periods — typically a six-hour overnight window at £0.07/kWh — the system ensured cars were powered when energy was cheapest and cleanest. Even more telling, over half of participants never intervened with the schedule, showing strong confidence in automated charging.
Why this matters for the UK grid
The trial’s findings come at a critical time. As Britain’s electric vehicle parc continues to expand, EVs could account for 15–20% of total electricity demand by 2050. Without smart load management, that demand risks pushing the grid to its limits during evening peaks.
AI-driven charging offers a powerful solution — aligning EV demand with renewable generation and off-peak capacity. It means lower bills for consumers, fewer costly grid upgrades, and a more stable energy system overall.
The fleet perspective: flexibility equals future-proofing
For fleets, the message is clear: managed charging is the next big enabler of cost-efficient electrification.
Fleets can take the same principles tested in this trial and apply them at depot or workplace level to:
Cut operating costs by automatically avoiding peak-rate charging
Balance loads to prevent site capacity issues
Integrate renewable or time-of-use tariffs into charging schedules
Support sustainability goals with cleaner, grid-friendly energy use
The shift to electric vehicles isn’t just about switching fuel types — it’s about smarter energy use. Automation will increasingly become the backbone of efficient, scalable fleet electrification.