KUALA LUMPUR: inDrive, the global ride-hailing service, revealed how artificial intelligence (AI) is increasingly integrated into every aspect of its ride-hailing app to enhance efficiency and accuracy, lower costs, improve safety and elevate user experience.
This integration is pivotal in a rapidly evolving market like Malaysia, where urbanisation and technological advancements are shaping the future of transportation, aligning with the Malaysian government’s initiative to actively promote AI through the National AI Framework and the Malaysia AI Blueprint, with the aim to position the country as a regional leader in AI technology.
inDrive differs from many of its competitors in that it adopted a peer-to-peer negotiation model, allowing drivers and passengers to directly negotiate the price for a ride by utilising machine learning in the pricing models to improve the accuracy of the recommended price when customers bid for rides, providing a starting point for negotiation that is fair to both customers and drivers.
Using pricing and matching models, inDrive can account for local conditions such as traffic surges, sporting events, and accidents, becoming more accurate in its predictions with more local data collected.
These conditions can also affect the number of drivers available and, in turn, customers’ ability to book rides. inDrive uses this information to create heat maps, guiding drivers to hotspots to increase supply where it is needed and better serve its users.
“Internally, AI can be used to improve operational efficiency by streamlining processes, for example, during security checks. When a driver wants to register in the app, they must supply several documents, including an Identification Card (IC) and driver’s licence. These are manually and digitally verified by a dedicated team of professionals using different filters, currently testing machine learning-based features to better identify fraudulent documents,” said inDrive Chief Technology and Product Officer (CTPO) Stephen Kruger.
Meanwhile, in some countries, inDrive uses a facial recognition tool to validate its users’ identities and machine learning to review users’ profile images and exclude sensitive, potentially dangerous, or commercial content.
As inDrive operates in many countries, it adapts to the different laws and regulations, balancing technological advancement with privacy protection and societal well-being on a regional basis.
As in many other industries, AI and machine learning are enabling the ride-hailing sector to rapidly evolve in quality, safety, and efficiency, impacting every aspect of the business. The use of AI has transitioned from a futuristic concept to a fundamental component of the present, with its benefits being experienced each time a ride is hailed.
On this, inDrive Malaysia Regional Driver Acquisition & Activation Team Lead, Mohamed Khalil says, “As we continue to integrate AI and machine learning to improve our services, inDrive remains committed to enhancing the ride-hailing experience in Malaysia by improving efficiency, safety, and customer satisfaction to benefit both drivers and passengers – paving the way towards transforming the local ride-hailing scene.”
