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市場調查報告書
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2007780

人工智慧智慧城市市場預測至2034年—按組件、部署模式、技術、應用、最終用戶和地區分類的全球分析

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個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球人工智慧智慧城市市場規模將達到 647 億美元，在預測期內將以 27.8% 的複合年成長率成長，到 2034 年將達到 4,604.5 億美元。

人工智慧智慧城市是指利用人工智慧、數據分析和連網數位技術來提升城市環境效率、永續性和居住的城市生態系統。這些城市整合了智慧基礎設施、物聯網設備和先進演算法，以最佳化交通、能源管理、公共、廢棄物管理和管治。透過實現即時資料收集和預測性決策，人工智慧智慧城市能夠改善資源配置、減少環境影響並提升市民服務。它們還能促進創新、經濟成長和韌性城市規劃，同時應對快速都市化和人口成長帶來的複雜挑戰。

快速的都市化和人口壓力

快速的都市化和不斷成長的人口密度使得高效的城市管理系統需求日益迫切。人工智慧智慧城市透過數據驅動的洞察，最佳化基礎設施、交通和資源利用，從而應對這些挑戰。各國政府正擴大採用智慧解決方案來管理交通堵塞、能源需求和公共服務。隨著城市擴張，整合人工智慧平台能夠確保永續發展、提升生活品質和提高營運效率，使城市環境更具韌性和適應性，並增強其滿足未來社會需求的能力。

高昂的初始投資和基礎設施成本

實施人工智慧智慧城市解決方案需要對數位基礎設施、先進感測器、網際網路和數據管理系統進行大量前期投資。許多市政當局，尤其是在發展中地區，面臨預算限制，難以進行大規模部署。此外，將舊有系統與尖端技術整合會增加複雜性和成本。這些財務和技術障礙正在減緩技術的普及速度。成本管理是市場廣泛擴張的關鍵挑戰，因為相關人員必須仔細權衡長期收益和短期支出。

人工智慧、物聯網、5G 和數據分析領域的進步

人工智慧、物聯網 (IoT)、5G 通訊和數據分析的持續進步正在為市場創造巨大的成長機會。這些技術能夠實現城市系統間的無縫通訊和預測性決策。更完善的連結性和智慧自動化提高了交通、能源、醫療和管治等領域的效率。隨著創新加速和技術成本的降低，城市正日益採用整合的數位生態系統，為更智慧的基礎設施和永續的城市發展開闢了新的可能性。

對資料隱私和網路安全的擔憂

人工智慧智慧城市中互聯設備和數據驅動平台的廣泛應用引發了人們對資料隱私和網路安全的嚴重擔憂。從公民和基礎設施系統中收集的大量敏感資訊極易遭受網路攻擊和未授權存取。確保穩健的安全態勢並遵守資料保護條例仍然是各國政府和組織面臨的重大挑戰。這些風險可能會損害公眾信任並延緩專案實施。

新冠疫情的影響：

新冠疫情加速了人工智慧智慧城市技術的應用，各國政府都在尋求建構更具韌性和反應能力的城市系統。智慧監控和即時數據監測等數位化解決方案對於公共衛生管理和保障服務連續性至關重要。這場危機凸顯了智慧基礎設施在危機管理和緊急應變中的重要性。後疫情時代，城市正增加對人工智慧驅動平台的投資，以強化緊急準備、提升醫療衛生系統，並建構更具適應性、技術驅動的城市環境。

在預測期內，智慧交通領域預計將佔據最大的市場佔有率。

在預測期內，智慧交通領域預計將佔據最大的市場佔有率。這主要歸功於擁擠的都市區對高效出行解決方案日益成長的需求。人工智慧驅動的交通管理、智慧公共交通系統和聯網汽車技術能夠改善交通流量、縮短旅行時間並降低排放氣體。各國政府正優先推動智慧運輸計劃，以提升城市的可及性和永續性。自動駕駛汽車和即時導航系統的日益普及進一步鞏固了該領域的領先地位。

預計雲端運算產業在預測期內將呈現最高的複合年成長率。

在預測期內，雲端運算領域預計將呈現最高的成長率，這主要得益於其擴充性、成本效益以及滿足大量資料儲存和處理需求的能力。雲端平台能夠將人工智慧、物聯網和分析解決方案無縫整合到城市營運的各個環節，從而實現即時數據存取、遠端管理以及智慧應用的快速部署。隨著城市對數位生態系統的依賴程度日益加深，雲端運算將成為建構靈活、安全、高效的智慧城市基礎設施的關鍵基礎。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這得益於其強大的技術基礎設施、對智慧城市項目的巨額投資以及眾多行業巨頭的存在。該地區各國政府正積極透過扶持政策和資金支持計畫推動數位轉型。人工智慧、物聯網和雲端運算技術的早期應用，以及先進的城市規劃策略，使北美成為智慧城市發展和創新領域的領導者。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於快速的都市化、人口成長以及各國政府對智慧基礎設施建設日益重視。新興經濟體正大力投資數位轉型，以因應城市挑戰並提升生活水準。 5G網路的擴展、物聯網設備的日益普及以及有利的法規結構正在加速市場成長。亞太地區正逐漸成為一個充滿活力的創新中心，並將引領人工智慧智慧城市的未來發展。

免費客製化服務：

所有購買此報告的客戶均可享受以下免費自訂選項之一：

  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 對主要企業進行SWOT分析（最多3家公司）
  • 區域分類
    • 應客戶要求，我們提供主要國家和地區的市場估算和預測，以及複合年成長率（註：需進行可行性檢查）。
  • 競爭性標竿分析
    • 根據產品系列、地理覆蓋範圍和策略聯盟對主要企業進行基準分析。

目錄

第1章：執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要企業市佔率分析
  • 產品基準評效和效能比較

第5章：全球人工智慧智慧城市市場：按組件分類

  • 硬體
  • 軟體
  • 服務

第6章：全球人工智慧智慧城市市場：依部署方式分類

  • 現場
  • 基於雲端的

第7章 全球人工智慧智慧城市市場：按技術分類

  • 人工智慧和機器學習
  • 物聯網 (IoT)
  • 巨量資料分析
  • 雲端運算
  • 邊緣運算
  • 機器人與自動化

第8章：全球人工智慧智慧城市市場：按應用分類

  • 智慧交通
  • 智慧型能源與公共產業
  • 智慧管治
  • 智慧建築
  • 公共保障
  • 廢棄物和水資源管理

第9章：全球人工智慧智慧城市市場：按最終用戶分類

  • 政府/市政當局
  • 交通運輸和基礎設施營運商
  • 能源和公共產業公司
  • 房地產和設施管理
  • 醫療和公共

第10章：全球人工智慧智慧城市市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第11章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第12章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第13章：公司簡介

  • 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.