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Five ways AI is shaping EV charging and payments

AI is transforming EV charging and payments in these five ways: enhancing customer service with digital assistants, automating quality assurance in software updates, improving billing accuracy, detecting fraud through pattern recognition, and enabling predictive maintenance of charge points.

18 June 2024

At a glance

AI is transforming EV charging and payments in these five ways: enhancing customer service with digital assistants, automating quality assurance in software updates, improving billing accuracy, detecting fraud through pattern recognition, and enabling predictive maintenance of charge points.

Artificial intelligence and machine learning often get a bad rap in the media as threats to jobs and even national security. However, like any technology, it can also drive productivity. Our industry is no exception, and at Road, AI is already improving our offering. Here are five ways we’re using AI to propel our products and services, along with an insight into its future impact.

1. Customer service

Our mission is to make EV charge payments frictionless, and to do this we need to provide best-in-class customer service. We offer 24/7 support and answer calls within an average of 150 seconds. As our customer base grows rapidly, naturally so does the number of calls we receive from customers needing support.

With the help of AI, we are able to resolve more than two-thirds of customer issues using digital assistants. At the back end, our product marketing team analyses the most frequent issues raised by customers, and creates content that the digital assistants use to answer these queries. This frees up our (human) agents to handle more complex issues, and cuts down the time that our customers spend on hold. The key is that while we use automation to solve common issues, it doesn't replace the option to speak with a real person promptly.

2. Quality assurance

When we release new applications and software updates, regression testing is crucial for quality assurance. We use AI to do additional quality checks on any changes or updates, ensuring that they don’t cause unexpected problems or “regressions” to our system functionality.

AI helps to automate our testing process, removing the need for manual checks.. We also use AI to analyse data and identify patterns and risks, which helps us to continuously improve the testing process. This ensures our software updates and changes are free of unexpected issues.

3. Billing and transaction settlement

Our billing and transaction accuracy is already at 9..5%, but we’re aiming even higher by moving to automated processing. AI generates invoices by accurately aggregating charging data and calculating usage fees, eliminating the need for human intervention. This reduces the finance team’s workload, and minimises billing errors.

4. Fraud detection

AI helps us to analyse large volumes of transaction data and to establish a baseline of normal activity. It helps us to identify any unusual patterns or behaviours indicating fraud, such as inconsistencies in charging locations and time or payment methods that deviate from a driver's typical usage patterns.

5. Predictive maintenance

AI proactively identifies issues with charge point hardware, alerting charge point owners and field service technicians. By analysing common data patterns before an outage occurs, we can increase the overall uptime of the charging network.

### And one for the roadmap: Algorithmic tariffs

Currently we offer advanced tariffs, such as blocking fees for extended parking, via EPEX. We’re exploring other tariffs, such as smart pricing or surge pricing, to optimise charge points in key locations and encourage drivers to use lesser-known locations. For instance, a business could pay a premium for immediate charging before an important meeting. AI will help us develop and implement these variable tariffs.

For more information on any of our products or services for EV charge point management please contact us here.

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