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市场调查报告书
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1865484

全球人工智慧赋能行动平台市场：预测至2032年－按产品、运输方​​式、部署方法、技术、应用、最终用户和地区进行分析

AI-Powered Mobility Platforms Market Forecasts to 2032 - Global Analysis By Offering (AI Software Platforms, Integrated Hardware Modules and Professional Services), Transportation Mode, Deployment Mode, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的一项研究，全球人工智慧赋能的行动平台市场预计到 2025 年将达到 35.1 亿美元，到 2032 年将达到 139.5 亿美元，在预测期内的复合年增长率为 21.8%。

人工智慧驱动的出行平台利用机器学习、巨量资料和即时分析，革新现代交通运营和通勤服务。它们整合城市交通数据、导航系统、感测器和公共交通网络，提供高效的路线引导，减少延误，降低能耗。这些平台支援自动驾驶车辆决策支援、共乘优化和数位化车队管理。预测分析使营运商能够将车辆分配到拥塞区，减少等待时间，提高服务可用性。自动追踪和智慧警报等安全功能增强了乘客保护。随着城市智慧基础设施和电动出行的扩展，人工智慧驱动的出行解决方案正成为实现更清洁、更快捷、更智慧的城市交通的核心。

根据 Gitnux 的一项调查，76% 的消费者愿意与旅游公司共用他们的数据，尤其是在人工智慧驱动的洞察和预测分析能够改善个人化、安全性、路线优化和整体旅行体验的情况下。

对智慧高效城市交通的需求日益增长

人工智慧驱动的出行市场的主要驱动力是对智慧高效城市交通日益增长的偏好。不断增长的城市人口和车辆数量导致严重的交通拥堵、出行时间延长以及环境问题。人工智慧出行平台处理持续的交通资讯、路侧感测器资料和GPS输入，进而实现路线调整、拥塞控制并提高出行效率。这些解决方案还支持共用出行、减少能源浪费，并帮助城市实现其排放目标。市政当局正在部署数位基础设施和自动化交通管理系统，以改善通勤流量。随着市民期望获得快速、安全且环保的出行体验，基于人工智慧的出行工具正成为建构面向未来的交通网络不可或缺的一部分。

实施成本高且基础设施需求复杂

人工智慧出行平台的主要限制因素之一是其部署和配套基础设施所需的巨额投资。基于人工智慧的交通解决方案依赖物联网设备、感测器网路、5G连接、先进的运算能力和持续的数据传输。建造智慧道路和自动交通控制系统需要大量资金投入，这使得市政当局和小规模车队所有者难以采用。小规模运输公司难以承担实施智慧车队管理工具和自动驾驶技术的成本。现有系统也需要昂贵的升级才能与人工智慧平台整合。这些资金障碍，加上发展中地区数位基础设施的匮乏，延缓了人工智慧出行平台的大规模应用，并限制了市场成长潜力。

扩大智慧城市计划和智慧交通基础设施

全球智慧城市计画的扩展为人工智慧出行平台带来了巨大的机会。现代城市系统包括自动交通号誌、感测器驱动的交通管理、智慧停车以及连网汽车专用车道。人工智慧解决方案分析来自城市感测器和交通网路的数据，以缓解交通拥堵、优化路线并提高公车和地铁的营运效率。地方政府正在部署智慧移动工具，以减少排放并提升通勤者的便利性。随着物联网设备、云端平台和5G连接的普及，基于人工智慧的交通解决方案市场正在不断扩大。这些计划在数位化交通管理和数据驱动的城市规划领域创造了新的商机。

针对连网行程和自动驾驶系统的网路攻击

由于车辆高度互联且资料交换频繁，网路风险对人工智慧出行平台构成最大威胁之一。骇客可以攻击自动驾驶车辆、车队管理伺服器和智慧交通网络，可能导致系统故障、资料窃取或车辆行为异常。如果通讯链路遭到破坏，攻击者可以篡改路线规划或干扰车辆控制。人工智慧出行系统储存着敏感的乘客和交通数据，这增加了漏洞被利用的风险。网路攻击手段的日益复杂使得各国政府和业者对全面采用自动驾驶出行持谨慎态度。如果没有强有力的网路安全措施，人工智慧驱动的交通途径的广泛部署可能会面临监管审批延迟和公众抵制。

新冠疫情的影响：

新冠疫情为人工智慧出行市场带来了挑战与机会。旅行限制和封锁导致客运量骤降，降低了共用出行的需求，并延缓了自动驾驶汽车的普及。预算削减和零件短缺也导致许多交通计划延期。然而，这场危机也推动了城市和企业转型为数位化、非接触式服务和数据驱动的交通管理。电子商务的蓬勃发展使得人们更加依赖人工智慧工具进行最后一公里配送、路线优化和车辆调度。随着各国逐步解除限制，对智慧交通系统、自动交通控制和安全出行平台的投资也开始反弹。最终，疫情加速了以人工智慧为基础的交通技术的普及，这将增强城市出行的韧性。

预计在预测期内，人工智慧软体平台细分市场将占据最大的市场份额。

预计在预测期内，人工智慧软体平台细分市场将占据最大的市场份额，因为它为智慧运输营运提供了所需的智慧。这些平台分析来自远端资讯处理、导航系统和车载感测器的信息，从而实现路线优化、安全警报和自主决策流程。车队营运商和城市交通网路依靠软体进行即时监控、预测性维护以及车辆与基础设施之间的无缝通讯。软体比硬体更具适应性，无需更换实体零件即可进行频繁升级。它与电动出行、共用出行应用和自动化物流的兼容性，使其成为寻求高效、扩充性且数位化互联的交通解决方案的组织的理想选择。

预计在预测期内，微出行领域将实现最高的复合年增长率。

预计在预测期内，微出行领域将迎来最高的成长率，因为小型电动车辆（例如Scooter、共享单车和电动自行车）正迅速成为都市区短途出行的主要方式。人工智慧解决方案能够实现持续追踪、电池管理、位置预测和智慧停车管理。营运商可以利用需求预测来优化车辆在拥塞路段的投放，从而避免运作。随着人们对交通拥堵和空气污染的日益关注，小型电动车辆提供了一种低成本、环保的出行方式。智慧城市计划、基于应用程式的租赁服务和便利的数位支付正在推动其大规模扩张。随着城市更加关注最后一公里连接和低排放出行，人工智慧驱动的微出行平台将继续以最快的速度成长。

占比最大的地区：

预计北美将在预测期内占据最大的市场份额，这主要得益于其强大的数位生态系统、对自动驾驶和联网汽车汽车的早期应用以及先进的交通网络。 5G 连接、交通感测器和云端基础的出行平台在该地区得到广泛应用，实现了即时路线规划和车队协调。技术供应商和汽车製造商正在积极试点自动驾驶系统、人工智慧导航和智慧车辆分析技术。公共交通和物流公司正在利用人工智慧来改善调度、提高燃油效率和安全性。有利的法规、电动车的广泛普及以及智慧城市计画正在推动进一步的投资。共乘、自动驾驶接驳车和微旅行服务的日益普及也巩固了该地区在人工智慧驱动的出行解决方案领域的领先地位。

年复合成长率最高的地区：

预计亚太地区在预测期内将实现最高的复合年增长率，这主要得益于智慧基础设施的扩张和对数位交通的大力投资。该地区的主要经济体正在推行自动驾驶汽车试验、电动车出行服务和人工智慧辅助交通管理。密集的城市环境和高人口密度推动了对最佳化路线、智慧公共交通和小型电动车的需求。科技主导的物流、电子商务配送和共用旅游Start-Ups进一步推动了这些技术的普及。各国政府正在推广无现金支付、互联道路和低排放出行策略，以帮助实现城市交通网络的现代化。在快速数位化、高行动普及率和对高效出行方式日益增长的需求的推动下，人工智慧出行平台在亚太地区正以最快的速度扩张。

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目录

第一章执行摘要

第二章 引言

  • 概述
  • 相关利益者
  • 分析范围
  • 分析方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 分析方法
  • 分析材料
    • 原始研究资料
    • 二手研究资讯来源
    • 先决条件

第三章 市场趋势分析

  • 介绍
  • 司机
  • 抑制因素
  • 市场机会
  • 威胁
  • 技术分析
  • 应用分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的感染疾病

第四章 波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代产品的威胁
  • 新参与企业的威胁
  • 公司间的竞争

第五章 全球人工智慧行动平台市场（按产品/服务划分）

  • 介绍
  • 人工智慧软体平台
  • 整合硬体模组
  • 专业服务

6. 全球人工智慧赋能出行平台市场（以交通方式划分）

  • 介绍
  • 乘客流动
  • 货运和物流流动性
  • 微移动性
  • 公共运输

第七章 全球人工智慧行动平台市场（依部署方式划分）

  • 介绍
  • 云端基础的人工智慧平台
  • 车载边缘人工智慧系统
  • 混合人工智慧架构

8. 全球人工智慧行动平台市场（按技术划分）

  • 介绍
  • 感知与感测器融合
  • 决策演算法
  • 人机介面（HMI）
  • 连接方式/通讯

第九章 全球人工智慧行动平台市场（按应用划分）

  • 介绍
  • 自动驾驶车辆调度服务
  • 车队优化与部署
  • 预测性维护
  • 智慧交通和基础设施管理
  • 实现最后一公里配送自动化
  • 出行即服务 (MaaS) 集成
  • 驾驶员行为监测与评分

第十章：全球人工智慧行动平台市场（按最终用户划分）

  • 介绍
  • 行动服务提供者
  • 汽车OEM厂商
  • 市政当局和交通管理部门
  • 物流和配送公司

第十一章 全球人工智慧行动平台市场（按地区划分）

  • 介绍
  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十二章 重大进展

  • 合约、商业伙伴关係和合资企业
  • 企业合併（M&A）
  • 新产品发布
  • 业务拓展
  • 其他关键策略

第十三章：公司简介

  • ANI Technologies Private Limited（Ola Cabs）
  • Beep, Inc.
  • Bird Rides, Inc.
  • Bolt Technology OU
  • Bridj Technology Pty Ltd.
  • Cabify Espana, SL
  • Comuto SA（BlaBlaCar）
  • Cubic Corporation
  • Daimler AG
  • Flix SE
  • Free2move by Stellantis
  • Grab Holdings Limited
  • Lyft, Inc.
  • Moovit
  • Via Transportation
Product Code: SMRC32152

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

List of Tables

  • Table 1 Global AI-Powered Mobility Platforms Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI-Powered Mobility Platforms Market Outlook, By Offering (2024-2032) ($MN)
  • Table 3 Global AI-Powered Mobility Platforms Market Outlook, By AI Software Platforms (2024-2032) ($MN)
  • Table 4 Global AI-Powered Mobility Platforms Market Outlook, By Integrated Hardware Modules (2024-2032) ($MN)
  • Table 5 Global AI-Powered Mobility Platforms Market Outlook, By Professional Services (2024-2032) ($MN)
  • Table 6 Global AI-Powered Mobility Platforms Market Outlook, By Transportation Mode (2024-2032) ($MN)
  • Table 7 Global AI-Powered Mobility Platforms Market Outlook, By Passenger Mobility (2024-2032) ($MN)
  • Table 8 Global AI-Powered Mobility Platforms Market Outlook, By Freight & Logistics Mobility (2024-2032) ($MN)
  • Table 9 Global AI-Powered Mobility Platforms Market Outlook, By Micro-Mobility (2024-2032) ($MN)
  • Table 10 Global AI-Powered Mobility Platforms Market Outlook, By Public Transit Systems (2024-2032) ($MN)
  • Table 11 Global AI-Powered Mobility Platforms Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 12 Global AI-Powered Mobility Platforms Market Outlook, By Cloud-Based AI Platforms (2024-2032) ($MN)
  • Table 13 Global AI-Powered Mobility Platforms Market Outlook, By On-Vehicle Edge AI Systems (2024-2032) ($MN)
  • Table 14 Global AI-Powered Mobility Platforms Market Outlook, By Hybrid AI Architectures (2024-2032) ($MN)
  • Table 15 Global AI-Powered Mobility Platforms Market Outlook, By Technology (2024-2032) ($MN)
  • Table 16 Global AI-Powered Mobility Platforms Market Outlook, By Perception & Sensor Fusion (2024-2032) ($MN)
  • Table 17 Global AI-Powered Mobility Platforms Market Outlook, By Decision-Making Algorithms (2024-2032) ($MN)
  • Table 18 Global AI-Powered Mobility Platforms Market Outlook, By Human-Machine Interfaces (HMI) (2024-2032) ($MN)
  • Table 19 Global AI-Powered Mobility Platforms Market Outlook, By Connectivity & Communication (2024-2032) ($MN)
  • Table 20 Global AI-Powered Mobility Platforms Market Outlook, By Application (2024-2032) ($MN)
  • Table 21 Global AI-Powered Mobility Platforms Market Outlook, By Autonomous Ride-Hailing (2024-2032) ($MN)
  • Table 22 Global AI-Powered Mobility Platforms Market Outlook, By Fleet Optimization & Dispatch (2024-2032) ($MN)
  • Table 23 Global AI-Powered Mobility Platforms Market Outlook, By Predictive Maintenance (2024-2032) ($MN)
  • Table 24 Global AI-Powered Mobility Platforms Market Outlook, By Smart Traffic & Infrastructure Management (2024-2032) ($MN)
  • Table 25 Global AI-Powered Mobility Platforms Market Outlook, By Last-Mile Delivery Automation (2024-2032) ($MN)
  • Table 26 Global AI-Powered Mobility Platforms Market Outlook, By Mobility-as-a-Service (MaaS) Integration (2024-2032) ($MN)
  • Table 27 Global AI-Powered Mobility Platforms Market Outlook, By Driver Behavior Monitoring & Scoring (2024-2032) ($MN)
  • Table 28 Global AI-Powered Mobility Platforms Market Outlook, By End User (2024-2032) ($MN)
  • Table 29 Global AI-Powered Mobility Platforms Market Outlook, By Mobility Service Operators (2024-2032) ($MN)
  • Table 30 Global AI-Powered Mobility Platforms Market Outlook, By Automotive OEMs (2024-2032) ($MN)
  • Table 31 Global AI-Powered Mobility Platforms Market Outlook, By Municipal & Transit Authorities (2024-2032) ($MN)
  • Table 32 Global AI-Powered Mobility Platforms Market Outlook, By Logistics & Delivery Enterprises (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.