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1865484

全球人工智慧賦能行動平台市場：預測至2032年－按產品、運輸方​​式、部署方法、技術、應用、最終用戶和地區進行分析

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個工作天內

價格

根據 Stratistics MRC 的一項研究，全球人工智慧賦能的行動平台市場預計到 2025 年將達到 35.1 億美元，到 2032 年將達到 139.5 億美元，在預測期內的複合年成長率為 21.8%。

人工智慧驅動的出行平台利用機器學習、巨量資料和即時分析，革新現代交通營運和通勤服務。它們整合城市交通數據、導航系統、感測器和公共交通網路，提供高效的路線引導，減少延誤，降低能耗。這些平台支援自動駕駛車輛決策支援、共乘最佳化和數位化車隊管理。預測分析使營運商能夠將車輛分配到擁塞區，減少等待時間，提高服務可用性。自動追蹤和智慧警報等安全功能增強了乘客保護。隨著城市智慧基礎設施和電動出行的擴展，人工智慧驅動的出行解決方案正成為實現更清潔、更快捷、更智慧的城市交通的核心。

根據 Gitnux 的一項調查，76% 的消費者願意與旅遊公司共用他們的數據，尤其是在人工智慧驅動的洞察和預測分析能夠改善個人化、安全性、路線最佳化和整體旅行體驗的情況下。

對智慧高效城市交通的需求日益成長

人工智慧驅動的出行市場的主要驅動力是對智慧高效城市交通日益成長的偏好。不斷成長的城市人口和車輛數量導致嚴重的交通堵塞、出行時間延長以及環境問題。人工智慧出行平台處理持續的交通資訊、路側感測器資料和GPS輸入，進而實現路線調整、擁塞控制並提高出行效率。這些解決方案還支持共用出行、減少能源浪費，並幫助城市實現其排放目標。市政當局正在部署數位基礎設施和自動化交通管理系統，以改善通勤流量。隨著市民期望獲得快速、安全且環保的出行體驗，基於人工智慧的出行工具正成為建構面向未來的交通網路不可或缺的一部分。

實施成本高且基礎設施需求複雜

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礎設施所需的巨額投資。基於人工智慧的交通解決方案依賴物聯網設備、感測器網路、5G連接、先進的運算能力和持續的數據傳輸。建造智慧道路和自動交通控制系統需要大量資金投入，這使得市政當局和小規模車隊所有者難以採用。小規模運輸公司難以承擔實施智慧車隊管理工具和自動駕駛技術的成本。現有系統也需要昂貴的升級才能與人工智慧平台整合。這些資金障礙，加上發展中地區數位基礎設施的匱乏，延緩了人工智慧出行平台的大規模應用，並限制了市場成長潛力。

擴大智慧城市計劃和智慧交通基礎設施

全球智慧城市計畫的擴展為人工智慧出行平台帶來了巨大的機會。現代城市系統包括自動交通號誌、感測器驅動的交通管理、智慧停車以及連網汽車專用車道。人工智慧解決方案分析來自城市感測器和交通網路的數據，以緩解交通堵塞、最佳化路線並提高公車和地鐵的營運效率。地方政府正在部署智慧移動工具，以減少排放並提升通勤者的便利性。隨著物聯網設備、雲端平台和5G連接的普及，基於人工智慧的交通解決方案市場正在不斷擴大。這些計劃在數位化交通管理和數據驅動的城市規劃領域創造了新的商機。

針對連網行程和自動駕駛系統的網路攻擊

由於車輛高度互聯且資料交換頻繁，網路風險對人工智慧出行平台構成最大威脅之一。駭客可以攻擊自動駕駛車輛、車隊管理伺服器和智慧交通網路，可能導致系統故障、資料竊取或車輛行為異常。如果通訊鏈路遭到破壞，攻擊者可以篡改路線規劃或干擾車輛控制。人工智慧出行系統儲存著敏感的乘客和交通數據，這增加了漏洞被利用的風險。網路攻擊手段的日益複雜使得各國政府和業者對全面採用自動駕駛出行持謹慎態度。如果沒有強力的網路安全措施，人工智慧驅動的交通途徑的廣泛部署可能會面臨法規核准延遲和公眾抵制。

新冠疫情的影響：

新冠疫情為人工智慧出行市場帶來了挑戰與機會。旅行限制和封鎖導致客運量驟降，降低了共用出行的需求，並延緩了自動駕駛汽車的普及。預算削減和零件短缺也導致許多交通計劃延期。然而，這場危機也推動了城市和企業轉型為數位化、非接觸式服務和數據驅動的交通管理。電子商務的蓬勃發展使得人們更加依賴人工智慧工具進行最後一公里配送、路線最佳化和車輛調度。隨著各國逐步解除限制，對智慧交通系統、自動交通控制和安全出行平台的投資也開始反彈。最終，疫情加速了以人工智慧為基礎的交通技術的普及，這將增強城市出行的韌性。

預計在預測期內，人工智慧軟體平台細分市場將佔據最大的市場佔有率。

預計在預測期內，人工智慧軟體平台細分市場將佔據最大的市場佔有率，因為它為智慧運輸營運提供了所需的智慧。這些平台分析來自遠端資訊處理、導航系統和車載感測器的資訊，從而實現路線最佳化、安全警報和自主決策流程。車隊營運商和城市交通網路依靠軟體進行即時監控、預測性維護以及車輛與基礎設施之間的無縫通訊。軟體比硬體更具適應性，無需更換實體零件即可進行頻繁升級。它與電動出行、共用出行應用和自動化物流的兼容性，使其成為尋求高效、擴充性且數位化互聯的交通解決方案的組織的理想選擇。

預計在預測期內，微出行領域將實現最高的複合年成長率。

預計在預測期內，微出行領域將迎來最高的成長率，因為小型電動車輛（例如Scooter、共享單車和電動自行車）正迅速成為都市區短途出行的主要方式。人工智慧解決方案能夠實現持續追蹤、電池管理、位置預測和智慧停車管理。營運商可以利用需求預測來最佳化車輛在擁塞路段的投放，從而避免運作。隨著人們對交通堵塞和空氣污染的日益關注，小型電動車輛提供了一種低成本、環保的出行方式。智慧城市計劃、基於應用程式的租賃服務和便利的數位支付正在推動其大規模擴張。隨著城市更加關注最後一公里連接和低排放出行，人工智慧驅動的微出行平台將繼續以最快的速度成長。

佔比最大的地區：

預計北美將在預測期內佔據最大的市場佔有率，這主要得益於其強大的數位生態系統、對自動駕駛和聯網汽車汽車的早期應用以及先進的交通網路。 5G 連接、交通感測器和雲端基礎的出行平台在該地區得到廣泛應用，實現了即時路線規劃和車隊協調。技術供應商和汽車製造商正在積極試點自動駕駛系統、人工智慧導航和智慧車輛分析技術。公共交通和物流公司正在利用人工智慧來改善調度、提高燃油效率和安全性。有利的法規、電動車的廣泛普及以及智慧城市計畫正在推動進一步的投資。共乘、自動駕駛接駁車和微旅行服務的日益普及也鞏固了該地區在人工智慧驅動的出行解決方案領域的領先地位。

年複合成長率最高的地區：

預計亞太地區在預測期內將實現最高的複合年成長率，這主要得益於智慧基礎設施的擴張和對數位交通的大力投資。該地區的主要經濟體正在推行自動駕駛汽車試驗、電動車出行服務和人工智慧輔助交通管理。密集的城市環境和高人口密度推動了對最佳化路線、智慧公共交通和小型電動車的需求。科技主導的物流、電子商務配送和共用旅遊Start-Ups進一步推動了這些技術的普及。各國政府正在推廣無現金支付、互聯道路和低排放出行策略，以幫助實現城市交通網路的現代化。在快速數位化、高行動普及率和對高效出行方式日益成長的需求的推動下，人工智慧出行平台在亞太地區正以最快的速度擴張。

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目錄

第1章執行摘要

第2章 引言

  • 概述
  • 相關利益者
  • 分析範圍
  • 分析方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 分析方法
  • 分析材料
    • 原始研究資料
    • 二手研究資訊來源
    • 先決條件

第3章 市場趨勢分析

  • 介紹
  • 促進要素
  • 抑制因素
  • 市場機遇
  • 威脅
  • 技術分析
  • 應用分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的感染疾病

第4章 波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代產品的威脅
  • 新參與企業的威脅
  • 公司間的競爭

第5章 全球人工智慧行動平台市場（按產品/服務分類）

  • 介紹
  • 人工智慧軟體平台
  • 整合硬體模組
  • 專業服務

6. 全球人工智慧賦能出行平台市場（以交通方式分類）

  • 介紹
  • 乘客流動
  • 貨運和物流流動性
  • 微移動性
  • 公共運輸

第7章 全球人工智慧行動平台市場（依部署方式分類）

  • 介紹
  • 雲端基礎的人工智慧平台
  • 車載邊緣人工智慧系統
  • 混合人工智慧架構

8. 全球人工智慧行動平台市場（按技術分類）

  • 介紹
  • 感知與感測器融合
  • 決策演算法
  • 人機介面（HMI）
  • 連接方式/通訊

第9章 全球人工智慧行動平台市場（按應用分類）

  • 介紹
  • 自動駕駛車輛調度服務
  • 車隊最佳化與部署
  • 預測性維護
  • 智慧交通和基礎設施管理
  • 實現最後一公里配送自動化
  • 出行即服務 (MaaS) 整合
  • 駕駛員行為監測與評分

第10章：全球人工智慧行動平台市場（按最終用戶分類）

  • 介紹
  • 行動服務提供者
  • 汽車OEM廠商
  • 市政當局和交通管理部門
  • 物流和配送公司

第11章 全球人工智慧行動平台市場（按地區分類）

  • 介紹
  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第12章 重大進展

  • 合約、商業夥伴關係和合資企業
  • 企業合併（M&A）
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第13章：公司簡介

  • 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.