AI-Driven Fleet Optimization and Demand Forecasting in Micromobility

Artificial Intelligence

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AI-Driven Fleet Optimization and Demand Forecasting in Micromobility

publish date

Mar 12, 2025

duration

min

Difficulty

Intermediate

Beginner

Case details

In the rapidly changing landscape of micromobility, data analytics and AI have become integral to optimizing operations and enhancing urban transportation systems. This presentation examines how data-driven approaches enable fleet management, demand forecasting, and operational efficiency, helping companies meet the needs of rapidly changing urban environments. Additionally, it explores AI-driven innovations such as dynamic pricing and route optimization, which improve service reliability and customer satisfaction. By focusing on the broader trends and strategies enabled by data and AI, this piece provides insights into their transformative potential in driving smarter, more efficient micromobility solutions.

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About Author

Kaan Tas

General Manager

Kaan Tas is the General Manager at Lime, the world’s largest micromobility company, where he has driven over 5x growth in his region within three years, positioning it as a market leader. With expertise in leveraging data analytics and AI for operational efficiency, he has played a crucial role in optimizing urban transportation solutions and reducing carbon footprints. Prior to Lime, he led AI-driven strategies at Bricklane, a leading property investment platform, and played a key role in scaling operations at OYO, the SoftBank-backed hospitality giant. His experience spans business scaling, sustainability initiatives, and implementing AI-powered decision-making across various industries. Passionate about micromobility, cryptocurrencies, and digital transformation, he brings a unique perspective on how technology can drive efficiency and innovation in both emerging and traditional sectors.