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市场调查报告书
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2007780

人工智慧智慧城市市场预测至2034年—按组件、部署模式、技术、应用、最终用户和地区分類的全球分析

AI Smart Cities Market Forecasts to 2034- Global Analysis By Component (Hardware, Software and Services), Deployment, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，预计到 2026 年，全球人工智慧智慧城市市场规模将达到 647 亿美元，在预测期内将以 27.8% 的复合年增长率成长，到 2034 年将达到 4,604.5 亿美元。

人工智慧智慧城市是指利用人工智慧、数据分析和连网数位技术来提升城市环境效率、永续性和居住的城市生态系统。这些城市整合了智慧基础设施、物联网设备和先进演算法，以优化交通、能源管理、公共、废弃物管理和管治。透过实现即时资料收集和预测性决策，人工智慧智慧城市能够改善资源配置、减少环境影响并提升市民服务。它们还能促进创新、经济成长和韧性城市规划，同时应对快速都市化和人口成长带来的复杂挑战。

快速的都市化和人口压力

快速的都市化和不断增长的人口密度使得高效的城市管理系统需求日益迫切。人工智慧智慧城市透过数据驱动的洞察，优化基础设施、交通和资源利用，从而应对这些挑战。各国政府正越来越多地采用智慧解决方案来管理交通拥堵、能源需求和公共服务。随着城市扩张，整合人工智慧平台能够确保永续发展、提升生活品质和提高营运效率，使城市环境更具韧性和适应性，并增强其满足未来社会需求的能力。

高昂的初始投资和基础设施成本

实施人工智慧智慧城市解决方案需要对数位基础设施、先进感测器、互联网和数据管理系统进行大量前期投资。许多市政当局，尤其是在发展中地区，面临预算限制，难以进行大规模部署。此外，将旧有系统与尖端技术整合会增加复杂性和成本。这些财务和技术障碍正在减缓技术的普及速度。成本管理是市场广泛扩张的关键挑战，因为相关人员必须仔细权衡长期收益和短期支出。

人工智慧、物联网、5G 和数据分析领域的进步

人工智慧、物联网 (IoT)、5G 通讯和数据分析的持续进步正在为市场创造巨大的成长机会。这些技术能够实现城市系统间的无缝通讯和预测性决策。更完善的连结性和智慧自动化提高了交通、能源、医疗和管治等领域的效率。随着创新加速和技术成本的降低，城市正日益采用整合的数位生态系统，为更智慧的基础设施和永续的城市发展开闢了新的可能性。

对资料隐私和网路安全的担忧

人工智慧智慧城市中互联设备和数据驱动平台的广泛应用引发了人们对资料隐私和网路安全的严重担忧。从公民和基础设施系统中收集的大量敏感资讯极易遭受网路攻击和未授权存取。确保稳健的安全态势并遵守资料保护条例仍然是各国政府和组织面临的重大挑战。这些风险可能会损害公众信任并延缓专案实施。

新冠疫情的影响：

新冠疫情加速了人工智慧智慧城市技术的应用，各国政府都在寻求建构更具韧性和反应能力的城市系统。智慧监控和即时数据监测等数位化解决方案对于公共卫生管理和保障服务连续性至关重要。这场危机凸显了智慧基础设施在危机管理和紧急应变中的重要性。后疫情时代，城市正增加对人工智慧驱动平台的投资，以强化紧急准备、提升医疗卫生系统，并建构更具适应性、技术驱动的城市环境。

在预测期内，智慧交通领域预计将占据最大的市场份额。

在预测期内，智慧交通领域预计将占据最大的市场份额。这主要归功于拥挤的都市区对高效出行解决方案日益增长的需求。人工智慧驱动的交通管理、智慧公共交通系统和联网汽车技术能够改善交通流量、缩短旅行时间并降低排放气体。各国政府正优先推动智慧运输计划，以提升城市的可及性和永续性。自动驾驶汽车和即时导航系统的日益普及进一步巩固了该领域的领先地位。

预计云端运算产业在预测期内将呈现最高的复合年增长率。

在预测期内，云端运算领域预计将呈现最高的成长率，这主要得益于其扩充性、成本效益以及满足大量资料储存和处理需求的能力。云端平台能够将人工智慧、物联网和分析解决方案无缝整合到城市营运的各个环节，从而实现即时数据存取、远端管理以及智慧应用的快速部署。随着城市对数位生态系统的依赖程度日益加深，云端运算将成为建构灵活、安全、高效的智慧城市基础设施的关键基础。

市占率最大的地区：

在预测期内，北美预计将占据最大的市场份额，这得益于其强大的技术基础设施、对智慧城市项目的巨额投资以及众多行业巨头的存在。该地区各国政府正积极透过扶持政策和资金支持计画推动数位转型。人工智慧、物联网和云端运算技术的早期应用，以及先进的城市规划策略，使北美成为智慧城市发展和创新领域的领导者。

复合年增长率最高的地区：

在预测期内，亚太地区预计将呈现最高的复合年增长率，这主要得益于快速的都市化、人口增长以及各国政府对智慧基础设施建设日益重视。新兴经济体正大力投资数位转型，以因应城市挑战并提升生活水准。 5G网路的扩展、物联网设备的日益普及以及有利的法规结构正在加速市场成长。亚太地区正逐渐成为一个充满活力的创新中心，并将引领人工智慧智慧城市的未来发展。

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所有购买此报告的客户均可享受以下免费自订选项之一：

  • 企业概况
    • 对其他市场参与者（最多 3 家公司）进行全面分析
    • 对主要企业进行SWOT分析（最多3家公司）
  • 区域划分
    • 应客户要求，我们提供主要国家和地区的市场估算和预测，以及复合年增长率（註：需进行可行性检查）。
  • 竞争性标竿分析
    • 根据产品系列、地理覆盖范围和策略联盟对主要企业进行基准分析。

目录

第一章：执行摘要

  • 市场概览及主要亮点
  • 驱动因素、挑战与机会
  • 竞争格局概述
  • 战略洞察与建议

第二章：研究框架

  • 研究目标和范围
  • 相关人员分析
  • 研究假设和限制
  • 调查方法

第三章 市场动态与趋势分析

  • 市场定义与结构
  • 主要市场驱动因素
  • 市场限制与挑战
  • 投资成长机会和重点领域
  • 产业威胁与风险评估
  • 技术与创新展望
  • 新兴市场/高成长市场
  • 监管和政策环境
  • 新冠疫情的影响及復苏前景

第四章：竞争环境与策略评估

  • 波特五力分析
    • 供应商的议价能力
    • 买方的议价能力
    • 替代品的威胁
    • 新进入者的威胁
    • 竞争公司之间的竞争
  • 主要企业市占率分析
  • 产品基准评效和效能比较

第五章：全球人工智慧智慧城市市场：按组件划分

  • 硬体
  • 软体
  • 服务

第六章：全球人工智慧智慧城市市场：依部署方式划分

  • 现场
  • 基于云端的

第七章 全球人工智慧智慧城市市场：按技术划分

  • 人工智慧和机器学习
  • 物联网 (IoT)
  • 巨量资料分析
  • 云端运算
  • 边缘运算
  • 机器人与自动化

第八章：全球人工智慧智慧城市市场：按应用划分

  • 智慧交通
  • 智慧型能源与公共产业
  • 智慧管治
  • 智慧建筑
  • 公共保障
  • 废弃物和水资源管理

第九章：全球人工智慧智慧城市市场：按最终用户划分

  • 政府/市政当局
  • 交通运输和基础设施营运商
  • 能源和公共产业公司
  • 房地产和设施管理
  • 医疗和公共

第十章：全球人工智慧智慧城市市场：按地区划分

  • 北美洲
    • 我们
    • 加拿大
    • 墨西哥
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 荷兰
    • 比利时
    • 瑞典
    • 瑞士
    • 波兰
    • 其他欧洲国家
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 韩国
    • 澳洲
    • 印尼
    • 泰国
    • 马来西亚
    • 新加坡
    • 越南
    • 其他亚太国家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥伦比亚
    • 智利
    • 秘鲁
    • 其他南美国家
  • 世界其他地区（RoW）
    • 中东
      • 沙乌地阿拉伯
      • 阿拉伯聯合大公国
      • 卡达
      • 以色列
      • 其他中东国家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲国家

第十一章 策略市场资讯

  • 工业价值网络和供应链评估
  • 空白区域和机会地图
  • 产品演进与市场生命週期分析
  • 通路、经销商和打入市场策略的评估

第十二章 产业趋势与策略倡议

  • 併购
  • 伙伴关係、联盟和合资企业
  • 新产品发布和认证
  • 扩大生产能力和投资
  • 其他策略倡议

第十三章：公司简介

  • Cisco Systems, Inc.
  • IBM Corporation
  • Microsoft Corporation
  • Siemens AG
  • Huawei Technologies Co., Ltd.
  • Intel Corporation
  • Oracle Corporation
  • Google LLC
  • Schneider Electric SE
  • NEC Corporation
  • Ericsson AB
  • SAP SE
  • NVIDIA Corporation
  • Honeywell International Inc.
  • Bosch GmbH
Product Code: SMRC34652

According to Stratistics MRC, the Global AI Smart Cities Market is accounted for $64.70 billion in 2026 and is expected to reach $460.45 billion by 2034 growing at a CAGR of 27.8% during the forecast period. AI Smart Cities refer to urban ecosystems that leverage artificial intelligence, data analytics, and interconnected digital technologies to enhance the efficiency, sustainability, and livability of city environments. These cities integrate smart infrastructure, IoT devices, and advanced algorithms to optimize transportation, energy management, public safety, waste handling, and governance. By enabling real-time data collection and predictive decision-making, AI Smart Cities improve resource allocation, reduce environmental impact, and enhance citizen services. They foster innovation, economic growth, and resilient urban planning while addressing complex challenges associated with rapid urbanization and population expansion.

Market Dynamics:

Driver:

Rapid urbanization and population pressure

Rapid urbanization and rising population density are intensifying the need for efficient urban management systems. AI Smart Cities address these pressures by optimizing infrastructure, transportation, and resource utilization through data-driven insights. Governments are increasingly adopting intelligent solutions to manage traffic congestion, energy demand, and public services. As cities expand, the integration of AI-powered platforms ensures sustainable growth, improved quality of life, and enhanced operational efficiency, making urban environments more resilient, adaptive, and capable of meeting future societal demands.

Restraint:

High initial investment and infrastructure costs

The deployment of AI Smart City solutions requires substantial upfront investments in digital infrastructure, advanced sensors, connectivity networks, and data management systems. Many municipalities, particularly in developing regions, face budget constraints that limit large scale implementation. Additionally, the integration of legacy systems with modern technologies increases complexity and cost. These financial and technical barriers slow adoption rates, as stakeholders must carefully balance long term benefits against immediate expenditures, making cost management a critical challenge in widespread market expansion.

Opportunity:

Advancements in AI, IoT, 5G, and data analytics

Continuous advancements in artificial intelligence, Internet of Things (IoT), 5G connectivity, and data analytics are creating significant growth opportunities in the market. These technologies enable seamless communication and predictive decision-making across urban systems. Enhanced connectivity and intelligent automation improve efficiency in transportation, energy, healthcare, and governance. As innovation accelerates and technology costs decline, cities are increasingly adopting integrated digital ecosystems, unlocking new possibilities for smarter infrastructure and sustainable urban development.

Threat:

Data privacy and cybersecurity concerns

The extensive use of interconnected devices and data-driven platforms in AI Smart Cities raises critical concerns regarding data privacy and cybersecurity. Large volumes of sensitive information collected from citizens and infrastructure systems are vulnerable to cyberattacks and unauthorized access. Ensuring robust security frameworks and compliance with data protection regulations remains a major challenge for governments and organizations. These risks can hinder public trust and slow adoption.

Covid-19 Impact:

The COVID-19 pandemic accelerated the adoption of AI Smart City technologies as governments sought resilient and responsive urban systems. Digital solutions such as smart surveillance and real time data monitoring became essential for managing public health and ensuring continuity of services. The crisis highlighted the importance of intelligent infrastructure in crisis management and emergency response. Post-pandemic, cities are increasingly investing in AI-driven platforms to enhance preparedness, strengthen healthcare systems, and build more adaptive, technology enabled urban environments.

The smart transportation segment is expected to be the largest during the forecast period

The smart transportation segment is expected to account for the largest market share during the forecast period, due to increasing demand for efficient mobility solutions in congested urban areas. AI-driven traffic management, intelligent public transit systems, and connected vehicle technologies enhance traffic flow, reduce travel time, and lower emissions. Governments are prioritizing smart mobility initiatives to improve urban accessibility and sustainability. The growing adoption of autonomous vehicles and real time navigation systems further strengthens the dominance of this segment.

The cloud computing segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the cloud computing segment is predicted to witness the highest growth rate, due to its scalability, cost-efficiency, and ability to support vast data storage and processing needs. Cloud platforms enable seamless integration of AI, IoT, and analytics solutions across city operations. They facilitate real-time data access, remote management, and faster deployment of smart applications. As cities increasingly rely on digital ecosystems, cloud computing becomes a critical backbone for enabling flexible, secure, and efficient smart city infrastructures.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to strong technological infrastructure, high investment in smart city initiatives, and the presence of major industry players. Governments in the region aктивнo promote digital transformation through supportive policies and funding programs. Early adoption of AI, IoT, and cloud technologies, combined with advanced urban planning strategies, positions North America as a leader in smart city development and innovation.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, owing to rapid urbanization, growing population, and increasing government focus on smart infrastructure development. Emerging economies are investing heavily in digital transformation to address urban challenges and improve living standards. The expansion of 5G networks, rising adoption of IoT devices, and supportive regulatory frameworks are accelerating market growth. Asia Pacific is becoming a dynamic hub for innovation, driving the future evolution of AI Smart Cities.

Key players in the market

Some of the key players in AI Smart Cities Market include Cisco Systems, Inc., IBM Corporation, Microsoft Corporation, Siemens AG, Huawei Technologies Co., Ltd., Intel Corporation, Oracle Corporation, Google LLC, Schneider Electric SE, NEC Corporation, Ericsson AB, SAP SE, NVIDIA Corporation, Honeywell International Inc. and Bosch GmbH.

Key Developments:

In February 2026, CGI Inc. and Schneider Electric expanded their strategic partnership to deliver end-to-end digital solutions for energy providers in the DACH region. The collaboration integrates CGI's IT consulting, systems integration, and managed services with Schneider Electric's grid technologies such as ADMS and GIS to help utilities modernize networks.

In November 2025, Schneider Electric and Switch announced a two-phase supply capacity agreement (SCA) totaling $1.9 billion in sales. The milestone deal includes prefabricated power modules and the first North American deployment of chillers. Schneider Electric and Switch have evolved their longstanding partnership to support the growing AI and hyperscale computing demand of AI factories.

Components Covered:

  • Hardware
  • Software
  • Services

Deployments Covered:

  • On-Premises
  • Cloud-Based

Technologies Covered:

  • Artificial Intelligence & Machine Learning
  • Internet of Things (IoT)
  • Big Data Analytics
  • Cloud Computing
  • Edge Computing
  • Robotics & Automation

Applications Covered:

  • Smart Transportation
  • Smart Energy & Utilities
  • Smart Governance
  • Smart Buildings
  • Public Safety & Security
  • Waste & Water Management

End Users Covered:

  • Government & Municipalities
  • Transportation & Infrastructure Providers
  • Energy & Utility Companies
  • Real Estate & Facility Management
  • Healthcare & Public Safety

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of 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 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • 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

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI Smart Cities Market, By Component

  • 5.1 Hardware
  • 5.2 Software
  • 5.3 Services

6 Global AI Smart Cities Market, By Deployment

  • 6.1 On-Premises
  • 6.2 Cloud-Based

7 Global AI Smart Cities Market, By Technology

  • 7.1 Artificial Intelligence & Machine Learning
  • 7.2 Internet of Things (IoT)
  • 7.3 Big Data Analytics
  • 7.4 Cloud Computing
  • 7.5 Edge Computing
  • 7.6 Robotics & Automation

8 Global AI Smart Cities Market, By Application

  • 8.1 Smart Transportation
  • 8.2 Smart Energy & Utilities
  • 8.3 Smart Governance
  • 8.4 Smart Buildings
  • 8.5 Public Safety & Security
  • 8.6 Waste & Water Management

9 Global AI Smart Cities Market, By End User

  • 9.1 Government & Municipalities
  • 9.2 Transportation & Infrastructure Providers
  • 9.3 Energy & Utility Companies
  • 9.4 Real Estate & Facility Management
  • 9.5 Healthcare & Public Safety

10 Global AI Smart Cities Market, By Geography

  • 10.1 North America
    • 10.1.1 United States
    • 10.1.2 Canada
    • 10.1.3 Mexico
  • 10.2 Europe
    • 10.2.1 United Kingdom
    • 10.2.2 Germany
    • 10.2.3 France
    • 10.2.4 Italy
    • 10.2.5 Spain
    • 10.2.6 Netherlands
    • 10.2.7 Belgium
    • 10.2.8 Sweden
    • 10.2.9 Switzerland
    • 10.2.10 Poland
    • 10.2.11 Rest of Europe
  • 10.3 Asia Pacific
    • 10.3.1 China
    • 10.3.2 Japan
    • 10.3.3 India
    • 10.3.4 South Korea
    • 10.3.5 Australia
    • 10.3.6 Indonesia
    • 10.3.7 Thailand
    • 10.3.8 Malaysia
    • 10.3.9 Singapore
    • 10.3.10 Vietnam
    • 10.3.11 Rest of Asia Pacific
  • 10.4 South America
    • 10.4.1 Brazil
    • 10.4.2 Argentina
    • 10.4.3 Colombia
    • 10.4.4 Chile
    • 10.4.5 Peru
    • 10.4.6 Rest of South America
  • 10.5 Rest of the World (RoW)
    • 10.5.1 Middle East
      • 10.5.1.1 Saudi Arabia
      • 10.5.1.2 United Arab Emirates
      • 10.5.1.3 Qatar
      • 10.5.1.4 Israel
      • 10.5.1.5 Rest of Middle East
    • 10.5.2 Africa
      • 10.5.2.1 South Africa
      • 10.5.2.2 Egypt
      • 10.5.2.3 Morocco
      • 10.5.2.4 Rest of Africa

11 Strategic Market Intelligence

  • 11.1 Industry Value Network and Supply Chain Assessment
  • 11.2 White-Space and Opportunity Mapping
  • 11.3 Product Evolution and Market Life Cycle Analysis
  • 11.4 Channel, Distributor, and Go-to-Market Assessment

12 Industry Developments and Strategic Initiatives

  • 12.1 Mergers and Acquisitions
  • 12.2 Partnerships, Alliances, and Joint Ventures
  • 12.3 New Product Launches and Certifications
  • 12.4 Capacity Expansion and Investments
  • 12.5 Other Strategic Initiatives

13 Company Profiles

  • 13.1 Cisco Systems, Inc.
  • 13.2 IBM Corporation
  • 13.3 Microsoft Corporation
  • 13.4 Siemens AG
  • 13.5 Huawei Technologies Co., Ltd.
  • 13.6 Intel Corporation
  • 13.7 Oracle Corporation
  • 13.8 Google LLC
  • 13.9 Schneider Electric SE
  • 13.10 NEC Corporation
  • 13.11 Ericsson AB
  • 13.12 SAP SE
  • 13.13 NVIDIA Corporation
  • 13.14 Honeywell International Inc.
  • 13.15 Bosch GmbH

List of Tables

  • Table 1 Global AI Smart Cities Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI Smart Cities Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI Smart Cities Market Outlook, By Hardware (2023-2034) ($MN)
  • Table 4 Global AI Smart Cities Market Outlook, By Software (2023-2034) ($MN)
  • Table 5 Global AI Smart Cities Market Outlook, By Services (2023-2034) ($MN)
  • Table 6 Global AI Smart Cities Market Outlook, By Deployment (2023-2034) ($MN)
  • Table 7 Global AI Smart Cities Market Outlook, By On-Premises (2023-2034) ($MN)
  • Table 8 Global AI Smart Cities Market Outlook, By Cloud-Based (2023-2034) ($MN)
  • Table 9 Global AI Smart Cities Market Outlook, By Technology (2023-2034) ($MN)
  • Table 10 Global AI Smart Cities Market Outlook, By Artificial Intelligence & Machine Learning (2023-2034) ($MN)
  • Table 11 Global AI Smart Cities Market Outlook, By Internet of Things (IoT) (2023-2034) ($MN)
  • Table 12 Global AI Smart Cities Market Outlook, By Big Data Analytics (2023-2034) ($MN)
  • Table 13 Global AI Smart Cities Market Outlook, By Cloud Computing (2023-2034) ($MN)
  • Table 14 Global AI Smart Cities Market Outlook, By Edge Computing (2023-2034) ($MN)
  • Table 15 Global AI Smart Cities Market Outlook, By Robotics & Automation (2023-2034) ($MN)
  • Table 16 Global AI Smart Cities Market Outlook, By Application (2023-2034) ($MN)
  • Table 17 Global AI Smart Cities Market Outlook, By Smart Transportation (2023-2034) ($MN)
  • Table 18 Global AI Smart Cities Market Outlook, By Smart Energy & Utilities (2023-2034) ($MN)
  • Table 19 Global AI Smart Cities Market Outlook, By Smart Governance (2023-2034) ($MN)
  • Table 20 Global AI Smart Cities Market Outlook, By Smart Buildings (2023-2034) ($MN)
  • Table 21 Global AI Smart Cities Market Outlook, By Public Safety & Security (2023-2034) ($MN)
  • Table 22 Global AI Smart Cities Market Outlook, By Waste & Water Management (2023-2034) ($MN)
  • Table 23 Global AI Smart Cities Market Outlook, By End User (2023-2034) ($MN)
  • Table 24 Global AI Smart Cities Market Outlook, By Government & Municipalities (2023-2034) ($MN)
  • Table 25 Global AI Smart Cities Market Outlook, By Transportation & Infrastructure Providers (2023-2034) ($MN)
  • Table 26 Global AI Smart Cities Market Outlook, By Energy & Utility Companies (2023-2034) ($MN)
  • Table 27 Global AI Smart Cities Market Outlook, By Real Estate & Facility Management (2023-2034) ($MN)
  • Table 28 Global AI Smart Cities Market Outlook, By Healthcare & Public Safety (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.