세계의 AI 기반 모빌리티 플랫폼 시장 예측(-2032년)

According to Stratistics MRC, the Global AI-Powered Mobility Platforms Market is accounted for $3.51 billion in 2025 and is expected to reach $13.95 billion by 2032 growing at a CAGR of 21.8% during the forecast period. AI-powered mobility platforms rely on machine learning, big data, and instant analytics to transform modern transport operations and commuter services. They integrate city traffic data, navigation systems, sensors, and public transportation networks to offer efficient routing, reduced delays, and lower energy usage. These platforms support autonomous vehicle decision-making, ride-sharing optimization, and digital fleet supervision. Through predictive insights, operators can position vehicles in busy regions, reduce idle time, and improve service availability. Safety features such as automated tracking and smart alerts enhance passenger protection. As cities expand intelligent infrastructure and electric mobility, AI-enabled mobility solutions are becoming central to cleaner, faster, and smarter urban travel.

According to Gitnux, 76% of consumers are willing to share their data with mobility companies to improve services, especially when it enhances personalization, safety, route optimization, and overall travel experience through AI-driven insights and predictive analytics.

Market Dynamics:

Driver:

Growing demand for smart and efficient urban transportation

A major driver for the AI-powered mobility market is the rising preference for intelligent and efficient city transportation. Expanding urban populations and increased vehicle numbers cause heavy traffic, longer journeys, and environmental concerns. AI mobility platforms process continuous traffic feeds, roadside sensor data, and GPS inputs to adjust routing, control congestion, and improve trip efficiency. These solutions also support shared mobility, reduce energy waste, and help cities meet emissions targets. Municipal authorities are adopting digital infrastructure and automated traffic management systems to improve commuter flow. As citizens expect quick, safe, and eco-friendly travel experiences, AI-based mobility tools are becoming a necessity for future-ready transportation networks.

Restraint:

High implementation costs and complex infrastructure requirements

One major limitation for AI mobility platforms is the substantial investment needed for deployment and supporting infrastructure. AI-based transport solutions depend on IoT devices, sensor networks, 5G connectivity, advanced computing power, and continuous data transfer. Building smart roads and automated traffic control systems demands heavy spending, making adoption difficult for municipalities and small fleet owners. Smaller transport companies struggle to afford intelligent fleet tools or self-driving technologies. Legacy systems also require costly upgrades to integrate with AI platforms. These financial hurdles, along with limited digital infrastructure in developing regions, delay large-scale adoption and restrict the market's growth potential.

Opportunity:

Expansion of smart city projects and intelligent transport infrastructure

Growing smart city programs across the globe provide a major opportunity for AI mobility platforms. Modern urban systems include automated traffic signals, sensor-driven transit management, smart parking, and connected vehicle corridors. AI solutions analyze data from city sensors and transportation networks to manage congestion, speed up routes, and improve bus or metro efficiency. Local governments are deploying intelligent mobility tools to lower emissions and improve commuter experiences. With wider adoption of IoT devices, cloud platforms, and 5G connectivity, the market for AI-based transport solutions is expanding. These projects create new revenue possibilities in digital transit management and data-driven urban planning.

Threat:

Cyber attacks on connected mobility and autonomous systems

Cyber risks are one of the biggest threats for AI mobility platforms due to high vehicle connectivity and data exchange. Hackers can target autonomous cars, fleet servers, or smart traffic networks, leading to system shutdowns, stolen data, or unsafe vehicle behavior. If communication links are compromised, attackers could alter routing decisions or interfere with vehicle controls. Since AI mobility systems store sensitive passenger and transport data, any vulnerability increases the danger of misuse. As cyberattacks become more advanced, governments and operators hesitate to fully adopt automated mobility. Without strong cybersecurity measures, widespread deployment of AI-powered transportation could face regulatory delays and public resistance.

Covid-19 Impact:

COVID-19 created both challenges and opportunities for the AI mobility market. Travel restrictions and shutdowns sharply reduced passenger movement, lowering demand for shared mobility and slowing autonomous vehicle deployments. Many transportation projects faced delays due to budget cuts and component shortages. Still, the crisis pushed cities and businesses toward digital mobility, touch-free services, and data-driven traffic management. E-commerce growth increased reliance on AI tools for last-mile deliveries, route optimization, and fleet scheduling. As nations lifted restrictions, investment returned to intelligent transportation, automated traffic control, and safety-focused mobility platforms. The pandemic ultimately encouraged faster adoption of AI-based transport technologies for resilient urban movement.

The AI software platforms segment is expected to be the largest during the forecast period

The AI software platforms segment is expected to account for the largest market share during the forecast period because they provide the intelligence required to manage smart mobility operations. These platforms analyze information from telematics, navigation systems, and onboard sensors to enhance routing, safety alerts, and autonomous decision processes. Fleet operators and city transport networks depend on software for real-time monitoring, predictive diagnostics, and seamless communication across vehicles and infrastructure. Software is more adaptable than hardware and can be upgraded frequently without replacing physical components. Its compatibility with electric mobility, shared mobility apps, and automated logistics makes it the preferred choice for organizations seeking efficient, scalable, and digitally connected transportation solutions.

The micro-mobility segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the micro-mobility segment is predicted to witness the highest growth rate because compact electric vehicles such as scooters, shared bikes, and e-cycles are rapidly becoming a preferred mode of short-distance travel in urban areas. AI solutions enable continuous tracking, battery management, location prediction, and smart parking enforcement. Operators use demand forecasting to balance fleets across busy routes and avoid downtime. With rising congestion and air-quality concerns, small electric vehicles provide an inexpensive and environmentally friendly mobility option. Smart city projects, app-based rentals, and seamless digital payments support large-scale expansion. As cities focus on last-mile connectivity and low-emission travel, AI-driven micro-mobility platforms continue to grow at the fastest pace.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to its strong digital ecosystem, early adoption of autonomous and connected vehicles, and sophisticated transportation networks. The region features widespread use of 5G connectivity, traffic sensors, and cloud-based mobility platforms that enable real-time routing and fleet coordination. Technology providers and automakers actively test self-driving systems, AI navigation, and intelligent fleet analytics. Public transportation agencies and delivery companies use AI to improve scheduling, fuel efficiency, and safety. Supportive regulations, electric vehicle growth, and smart city initiatives drive further investment. Increasing popularity of ride-sharing, autonomous shuttles, and micro-mobility services also strengthens regional dominance in AI-powered mobility solutions.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, led by expanding smart infrastructure and strong investment in digital transportation. Major economies in the region are rolling out autonomous vehicle tests, EV-based mobility services, and AI-supported traffic management. Dense urban environments and high population levels increase the need for optimized routing, intelligent public transit, and compact electric vehicles. Tech-driven logistics, e-commerce deliveries, and shared mobility startups further strengthen adoption. Governments encourage cashless ticketing, connected roads, and low-emission mobility strategies, helping cities modernize transport networks. With rapid digitization, strong mobile penetration, and rising demand for efficient travel, AI mobility platforms are scaling at the fastest rate in Asia-Pacific.

Key players in the market

Some of the key players in AI-Powered Mobility Platforms Market include ANI Technologies Private Limited (Ola Cabs), Beep, Inc., Bird Rides, Inc., Bolt Technology OU, Bridj Technology Pty Ltd., Cabify Espana, S.L., Comuto SA (BlaBlaCar), Cubic Corporation, Daimler AG, Flix SE, Free2move by Stellantis, Grab Holdings Limited, Lyft, Inc., Moovit and Via Transportation.

Key Developments:

In September 2025, Beep, Inc and ADASTEC announced a formal partnership to accelerate the safe deployment of shared autonomous transportation at scale. Through this alliance, the companies will combine Beep's expertise in planning, deploying, integrating, and operating autonomous mobility networks with ADASTEC's advanced automated driving system (ADS) technology and OEM partnerships.

In June 2025, Grab Holdings Ltd. announced plans for a $1.25 billion sale of bonds convertible into stock, the biggest of its kind among Asian companies this year, fueling speculation it's bulking up its warchest to take over rival Southeast Asian delivery-and-transport provider GoTo Group.

In April 2025, Lyft, Inc announced it has entered into a definitive agreement to acquire FREENOW, a leading European multi-mobility app with a taxi offering at its core, from BMW Group and Mercedes-Benz Mobility for approximately €175 million or $197 million* in cash. The transaction is expected to close in the second half of 2025, subject to customary closing conditions.

Offerings Covered:

• AI Software Platforms
• Integrated Hardware Modules
• Professional Services

Transportation Modes Covered:

• Passenger Mobility
• Freight & Logistics Mobility
• Micro-Mobility
• Public Transit Systems

Deployment Modes Covered:

• Cloud-Based AI Platforms
• On-Vehicle Edge AI Systems
• Hybrid AI Architectures

Technologies Covered:

• Perception & Sensor Fusion
• Decision-Making Algorithms
• Human-Machine Interfaces (HMI)
• Connectivity & Communication

Applications Covered:

• Autonomous Ride-Hailing
• Fleet Optimization & Dispatch
• Predictive Maintenance
• Smart Traffic & Infrastructure Management
• Last-Mile Delivery Automation
• Mobility-as-a-Service (MaaS) Integration
• Driver Behavior Monitoring & Scoring

End Users Covered:

• Mobility Service Operators
• Automotive OEMs
• Municipal & Transit Authorities
• Logistics & Delivery Enterprises

Regions Covered:

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • Italy
  • France
  • Spain
  • Rest of Europe
• Asia Pacific
  • Japan
  • China
  • India
  • Australia
  • New Zealand
  • South Korea
  • Rest of Asia Pacific
• South America
  • Argentina
  • Brazil
  • Chile
  • Rest of South America
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Qatar
  • South Africa
  • Rest of Middle East & Africa

What our report offers:

• Market share assessments for the regional and country-level segments
• Strategic recommendations for the new entrants
• Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
• Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
• Strategic recommendations in key business segments based on the market estimations
• Competitive landscaping mapping the key common trends
• Company profiling with detailed strategies, financials, and recent developments
• Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

• Company Profiling
  • Comprehensive profiling of additional market players (up to 3)
  • SWOT Analysis of key players (up to 3)
• Regional Segmentation
  • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
  • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

• 2.1 Abstract
• 2.2 Stake Holders
• 2.3 Research Scope
• 2.4 Research Methodology
  • 2.4.1 Data Mining
  • 2.4.2 Data Analysis
  • 2.4.3 Data Validation
  • 2.4.4 Research Approach
• 2.5 Research Sources
  • 2.5.1 Primary Research Sources
  • 2.5.2 Secondary Research Sources
  • 2.5.3 Assumptions

3 Market Trend Analysis

• 3.1 Introduction
• 3.2 Drivers
• 3.3 Restraints
• 3.4 Opportunities
• 3.5 Threats
• 3.6 Technology Analysis
• 3.7 Application Analysis
• 3.8 End User Analysis
• 3.9 Emerging Markets
• 3.10 Impact of Covid-19

4 Porters Five Force Analysis

• 4.1 Bargaining power of suppliers
• 4.2 Bargaining power of buyers
• 4.3 Threat of substitutes
• 4.4 Threat of new entrants
• 4.5 Competitive rivalry

5 Global AI-Powered Mobility Platforms Market, By Offering

• 5.1 Introduction
• 5.2 AI Software Platforms
• 5.3 Integrated Hardware Modules
• 5.4 Professional Services

6 Global AI-Powered Mobility Platforms Market, By Transportation Mode

• 6.1 Introduction
• 6.2 Passenger Mobility
• 6.3 Freight & Logistics Mobility
• 6.4 Micro-Mobility
• 6.5 Public Transit Systems

7 Global AI-Powered Mobility Platforms Market, By Deployment Mode

• 7.1 Introduction
• 7.2 Cloud-Based AI Platforms
• 7.3 On-Vehicle Edge AI Systems
• 7.4 Hybrid AI Architectures

8 Global AI-Powered Mobility Platforms Market, By Technology

• 8.1 Introduction
• 8.2 Perception & Sensor Fusion
• 8.3 Decision-Making Algorithms
• 8.4 Human-Machine Interfaces (HMI)
• 8.5 Connectivity & Communication

9 Global AI-Powered Mobility Platforms Market, By Application

• 9.1 Introduction
• 9.2 Autonomous Ride-Hailing
• 9.3 Fleet Optimization & Dispatch
• 9.4 Predictive Maintenance
• 9.5 Smart Traffic & Infrastructure Management
• 9.6 Last-Mile Delivery Automation
• 9.7 Mobility-as-a-Service (MaaS) Integration
• 9.8 Driver Behavior Monitoring & Scoring

10 Global AI-Powered Mobility Platforms Market, By End User

• 10.1 Introduction
• 10.2 Mobility Service Operators
• 10.3 Automotive OEMs
• 10.4 Municipal & Transit Authorities
• 10.5 Logistics & Delivery Enterprises

11 Global AI-Powered Mobility Platforms Market, By Geography

• 11.1 Introduction
• 11.2 North America
  • 11.2.1 US
  • 11.2.2 Canada
  • 11.2.3 Mexico
• 11.3 Europe
  • 11.3.1 Germany
  • 11.3.2 UK
  • 11.3.3 Italy
  • 11.3.4 France
  • 11.3.5 Spain
  • 11.3.6 Rest of Europe
• 11.4 Asia Pacific
  • 11.4.1 Japan
  • 11.4.2 China
  • 11.4.3 India
  • 11.4.4 Australia
  • 11.4.5 New Zealand
  • 11.4.6 South Korea
  • 11.4.7 Rest of Asia Pacific
• 11.5 South America
  • 11.5.1 Argentina
  • 11.5.2 Brazil
  • 11.5.3 Chile
  • 11.5.4 Rest of South America
• 11.6 Middle East & Africa
  • 11.6.1 Saudi Arabia
  • 11.6.2 UAE
  • 11.6.3 Qatar
  • 11.6.4 South Africa
  • 11.6.5 Rest of Middle East & Africa

12 Key Developments

• 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 12.2 Acquisitions & Mergers
• 12.3 New Product Launch
• 12.4 Expansions
• 12.5 Other Key Strategies

13 Company Profiling

• 13.1 ANI Technologies Private Limited (Ola Cabs)
• 13.2 Beep, Inc.
• 13.3 Bird Rides, Inc.
• 13.4 Bolt Technology OU
• 13.5 Bridj Technology Pty Ltd.
• 13.6 Cabify Espana, S.L.
• 13.7 Comuto SA (BlaBlaCar)
• 13.8 Cubic Corporation
• 13.9 Daimler AG
• 13.10 Flix SE
• 13.11 Free2move by Stellantis
• 13.12 Grab Holdings Limited
• 13.13 Lyft, Inc.
• 13.14 Moovit
• 13.15 Via Transportation