๐ช๐ต๐ฎ๐ ๐ต๐ฎ๐ฝ๐ฝ๐ฒ๐ป๐ ๐๐ต๐ฒ๐ป ๐๐ฉ ๐ฑ๐ฟ๐ถ๐๐ฒ๐ฟ๐ ๐ด๐ฒ๐ ๐๐๐ฝ๐ฝ๐ผ๐ฟ๐ ๐ฏ๐ฒ๐ณ๐ผ๐ฟ๐ฒ ๐ฎ ๐ฐ๐ต๐ฎ๐ฟ๐ด๐ถ๐ป๐ด ๐๐ฒ๐๐๐ถ๐ผ๐ป ๐๐๐ฎ๐ฟ๐๐?
We just wrapped a pilot with a public DC fast charging network built around a simple idea: Give drivers real-time, machine-aware support without forcing them to call a phone line.
The results were hard to ignore:
๐ ๐ญ.๐ตx ๐บ๐ผ๐ฟ๐ฒ ๐ฑ๐ฟ๐ถ๐๐ฒ๐ฟ๐ ๐๐ฒ๐ฟ๐๐ฒ๐ฑ vs. the call center alone
๐ ๐ฐ๐ด% ๐ฟ๐ฒ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป in inbound support calls after AI chat went live
๐ ๐๐ต๐ฎ๐ฟ๐ด๐ถ๐ป๐ด ๐๐ถ๐๐ถ๐ ๐๐๐ฐ๐ฐ๐ฒ๐๐ ๐ฟ๐ฎ๐๐ฒ: ๐ด๐ฒ.๐ฌ% โ ๐ต๐ญ.๐ณ% during the pilot period
โ
A few takeaways for charging operators:
1) Most interactions happened before a charge ever started, pointing to driver friction around authentication and payment โ including Plug & Charge.
2) AI support reached a different segment of drivers โ those who prefer to self-serve instead of calling.
3) When issues occurred mid-session, the highest impact areas were ending a charge without the e-stop button, troubleshooting charger faults, and safely removing stuck plugs.
โ
Even small improvements in DC fast charging success rates compound quickly at scale โ more completed sessions, fewer abandoned attempts, lower operating costs, more loyal drivers.
Call centers are great at resolving issues after a session has already failed. AI is better at intervening before a failure happens, while the charging session can still be recovered. If you own charging reliability or support costs, this is where the leverage is.
