{"id":223273,"date":"2025-04-08T11:00:42","date_gmt":"2025-04-08T03:00:42","guid":{"rendered":"https:\/\/www.grab.com\/sg\/?post_type=editorial&p=223273"},"modified":"2026-03-31T18:37:11","modified_gmt":"2026-03-31T10:37:11","slug":"grabrideguide-our-new-ai-tool-that-predicts-high-demand-areas","status":"publish","type":"editorial","link":"https:\/\/www.grab.com\/sg\/inside-grab\/stories\/grabrideguide-our-new-ai-tool-that-predicts-high-demand-areas\/","title":{"rendered":"GrabX: AI ride guidance"},"content":{"rendered":"\t\t
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For Grab driver-partners, every minute on the road counts\u2014but the reality of navigating city streets in Southeast Asia means there can be unwanted idle time, for instance due to unexpected traffic- and demand fluctuations. Drivers then have to make guesses about where best to go to find the next passenger or delivery task.<\/p>

The way we help to optimise driver earnings is to improve their productivity, so that they can get more done in the same span of time and earn more for every hour that they\u2019re on our platform.\u00a0<\/p>

This year, we piloted our AI ride guidance, a fully automated real-time ride demand finder for Grab driver-partners. This feature is now available in 14 cities across Southeast Asia. More than 80,000 drivers have access to the Beta version to codesign the experience with us. In the Beta phase, we saw an average earnings increase of 21 per cent per online hour in August, compared to the baseline of drivers who weren\u2019t using AI ride guidance.<\/p>

How the AI ride guidance works\u00a0<\/h5>

Our AI ride guidance offers a dynamic real-time demand map, which continually updates as conditions change. It identifies ride demand based on real-time and historical data and can analyse past trends considering various factors like the time of day, weather, and local events.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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It then suggests optimal routes not just for the current ride but also for positioning the driver advantageously for future pickups.<\/p>

AI technologies are driving this in the background, making it a significant enhancement of Grab\u2019s already existing demand heat map.<\/p>

AI ride guidance not only enables real-time tracking of driver distribution but also predictively analyses the movement patterns towards areas of ride demand. With this, Grab can proactively manage supply imbalances, ensuring an optimal distribution of drivers across regions.\u00a0<\/p>

Driver-partners who trialled AI ride guidance in the Beta version have told us that they found the feature useful. They think it\u2019s a particularly good tool for newer drivers who lack the years of experience it takes to understand a city\u2019s fluctuating demand patterns.<\/p>

AI to enhance the driver-partner experience<\/h5>

The insights gained through AI ride guidance will allow us to expand its capabilities beyond real-time demand. It will get better at predicting future ride demand areas and grow to understand driver-partners’ routines and preferences, as they often also use their vehicles to complete personal chores throughout the day, such as dropping off kids at school, or driving their spouse to their office. It could help them plan their rides optimally around these other tasks, and still maximise their earnings.\u00a0<\/p>

The long-term vision is for AI ride guidance to be integrated into a broader suite of AI-enhanced tools that will support the Grab driver-partner experience. This is the heart of our AI-driven productivity tools: technology with compassion that empowers our driver-partners.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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