Customer experience:
Uber has been leveraging behavioural science, backed by insights from across the customer journey, to reduce friction and create a simple, intuitive, fast, and easy customer experience. (Forbes) Uber has used data to improve its in-app help centre for customers and riders, suggest ways to optimise Chat Support, and uncover issues affecting the user experience. (Forbes) The end result has been a consistent improvement in the company’s customer satisfaction across all channels.
AI has improved Uber’s user experience in various ways. AI has improved efficiency, reduced wait times, and provided personalised recommendations, making riding more convenient and pleasurable. Pattern recognition is another tactic used by Uber’s AI. If a consistent route or food order is placed in the app, Uber will pre-emptively send a notification before you even decide to place an order or call a ride (Business Insider). Additionally, AI-powered safety features such as driver background checks and real-time tracking help to ensure the safety of riders.
Revenue:
Uber has been employing AI to optimise its pricing approach, which has resulted in increased revenue. Uber has used machine learning to forecast demand for rides and modify costs accordingly. This has allowed Uber to grow income while simultaneously giving clients with more affordable rides. By increasing efficiency and decreasing costs, AI has enabled Uber to cut its fares and attract more riders. Furthermore, AI-powered personalisation tools are utilised to target advertising to specific riders, potentially increasing revenue from advertising. For the first time in its decade long history, Uber made a profit in 2023. Uber reported a 118% increase to its revenue in the third quarter of 2023 and this earnings increase is comes after a hard implantation of AI in its revenue streams However, in its earnings report AI was only mentioned once. An article from the messenger alluded to this being a result of Uber “downplaying” the impact AI has had on Uber’s success (The Messenger). It is hard to determine the direct impact of AI on Uber’s profitability, though one may infer that there is a direct correlation.
Efficiency:
Uber has been leveraging AI and machine learning to detect and handle user experience incidents, ensuring that their app remains operational. Uber has used machine learning to identify and resolve problems with its payment system. This has helped Uber enhance its efficiency and reduce the number of problems affecting its consumers. AI has also increased Uber’s operational efficiency. With the implementation of AI, there has been a 12.3% increase improvement in demand forecasting, which better determines the price of Uber’s at a given time (Uber).
Another example is AI-powered chatbots, which are used to manage client inquiries, decreasing the strain of human support personnel. AI is also utilised to automate duties such as data analysis and reporting, allowing personnel to focus on more strategic objectives.
Operations:
Other specific cases on the use of AI in Uber are as follows:
• Demand Forecasting: Uber optimises fleet allocation and reduces empty vehicles through demand forecasting using AI algorithms. This increases efficiency and lowers fuel usage, saving the drivers money.
• Route Optimization: AI-powered algorithms optimise routes to reduce travel time and enhance the consumer experience.
• Pricing Optimization: AI algorithms optimise pricing based on real-time demand and supply, ensuring riders pay fair prices and drivers make a respectable profit.
• Fraud Detection: AI detects fraudulent activity on Uber’s platform, protecting riders and drivers from scams.
Sources:
- https://stratechery.com/company/uber/)
- https://www.businessinsider.com/uber-filed-patent-to-predict-customer-habits-artificial-intelligence-2023-5)
- https://www.cnbc.com/2023/05/19/heres-how-companies-in-the-sharing-economy-can-benefit-from-ai-and-boost-profits-.html)
- “ https://www.uber.com/us/en/uberai/)
- World Economic Forum 2:
Engine used:
Deep AI

