AI in Smart Cities Market Size, Share & Trends Analysis Report, By Application: Smart Mobility, Energy Management, Healthcare, Public Safety and Security, Waste Management, Environmental Monitoring, Water Management, Others), By Deployment Mode, By Component, By End User, By Region, Forecasts, 2024-2031
The AI in Smart Cities Market Size was valued at USD 36.9 Bn in 2023 and is predicted to reach USD 138.8 Bn by 2031 at a 18.1% CAGR during the forecast period for 2024-2031.
AI in smart cities integrates artificial intelligence technology to improve efficiency, sustainability, and quality of living, thus enhancing urban living. Using data analysis and automation, artificial intelligence helps smart cities manage better resources, control traffic flow, lower energy consumption, and improve public safety. Key factors driving the industry ahead are the building of smart transportation systems to reduce traffic congestion, enhancing public safety with cutting-edge monitoring and response systems, and optimizing sustainable energy usage, which are all factors that are expected to drive the market. The application of AI in smart cities is expected to increase demand in the future due to its ability to improve water distribution efficiency, waste management, and predictive infrastructure maintenance, all of which contribute to smarter, more resilient communities with greater quality of life. In addition, the market is anticipated to be propelled by increased government investments in research and development to optimize better smart city development.
However, the market growth is hindered by data privacy worries, expensive implementation expenses, a shortage of trained AI experts, and problems with regulation and compliance. Several variables can hinder adoption in this market. Global markets expanded during the coming years due to technological developments, heightened globalization, increasing consumer demand, and expanding infrastructure investments. Global market growth is being propelled by these elements, which improve productivity and open up new company opportunities in this market growth.
Competitive Landscape
Some of the Major Key Players in the AI in Smart Cities Market are
- IBM Corporation
- Microsoft Corporation
- Google LLC
- Intel Corporation
- Cisco Systems, Inc.
- Siemens AG
- Huawei Technologies Co., Ltd.
- NVIDIA Corporation
- Hitachi Vantara
- NEC Corporation
Market Segmentation:
The AI in smart cities market is segmented based on application, component, deployment mode, and end-user. The market is segmented by application into smart mobility, energy management, healthcare, public safety and security, waste management, environmental monitoring, water management, etc. The market is segmented by components into hardware, software, and services. By deployment mode, the market is segmented into cloud-based and on-premises. The market is segmented by end-user government, utilities, transportation companies, healthcare providers, real estate developers, and others.
Based On The Component, The Software Segment Is Accounted As A Major Contributor To The AI In The Smart Cities Market
Software segment in the AI in the smart cities market are expected to hold a major global market share in 2023 because increasing demand for data analytics, automation, and real-time decision-making to optimize city functions like traffic management, energy usage, and public safety. AI software enables scalable, flexible solutions that process vast amounts of data from IoT devices and sensors, allowing cities to improve efficiency and sustainability. Additionally, advancements in cloud computing, machine learning, and AI algorithms further propel the adoption of software solutions in smart city initiatives.
Real Estate Developer Segment to Witness Growth at a Rapid Rate
The real estate developer segment is projected to grow rapidly in the global AI in smart cities market because developers are increasingly using AI to create smart, environmentally friendly structures. Additionally, with AI’s predictive maintenance and energy optimization features, property management is made easier, which appeals to purchasers who are looking for contemporary, environmentally conscious homes. In addition, developers can benefit from data-informed decisions made possible by AI-driven insights, which enhances urban project planning and execution.
In the Region, the North American AI in Smart Cities Market Holds a Significant Revenue Share
The North American AI in smart cities market is expected to register the highest market share in revenue in the near future. This can be attributed to the fact that the government is heavily invested in smart infrastructure, prioritizes innovation, strongly backs sustainable urban development, and improves urban living standards while simultaneously cutting carbon emissions. In addition, Asia Pacific is projected to grow rapidly in the AI in smart cities market because the use of artificial intelligence to improve the effectiveness of public services, sophisticated technical infrastructure, substantial governmental funding for smart city initiatives, and a growing need for effective urban solutions will boost the market's growth.
Recent Developments:
- In July 2024, Oracle opened a second cloud region in Saudi Arabia, Riyadh. This is part of a $1.5 billion plan by Oracle to increase the country’s cloud capacity in line with Saudi Vision 2030. Saudi businesses can use Oracle Cloud Infrastructure’s fast speed, built-in security, powerful data, distributed cloud, and disaster recovery features to speed up AI creation and make their businesses more resilient.
- In January 2024, IBM and the Department of Science and Technology, Government of Gujarat, signed an MoU to create and promote an AI Cluster using IBM Watson. The goal is to promote new ideas and collaboration among these institutions. This partnership will provide financial institutions with digital assistant solutions, an AI sandbox, help with proof-of-concept creation, and AI literacy initiatives.
AI in Smart Cities Market Report Scope
| Report Attribute | Specifications |
| Market Size Value In 2023 | USD 36.9 Bn |
| Revenue Forecast In 2031 | USD 138.8 Bn |
| Growth Rate CAGR | CAGR of 18.1% from 2024 to 2031 |
| Quantitative Units | Representation of revenue in US$ Bn and CAGR from 2024 to 2031 |
| Historic Year | 2019 to 2023 |
| Forecast Year | 2024-2031 |
| Report Coverage | The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
| Segments Covered | By Deployment Mode, By Application, By Component, By End User |
| Regional Scope | North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
| Country Scope | U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea |
| Competitive Landscape | IBM Corporation, Microsoft Corporation, Google LLC, Intel Corporation, Cisco Systems, Inc., Siemens AG, Huawei Technologies Co., Ltd., NVIDIA Corporation, Hitachi Vantara, and NEC Corporation. |
| Customization Scope | Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
| Pricing And Available Payment Methods | Explore pricing alternatives that are customized to your particular study requirements. |
Segmentation of AI in the Smart Cities Market-
AI in the Smart Cities Market- By Component
- Hardware
- Software
- Services (Consulting, Maintenance, Training)
AI in the Smart Cities Market- By Application
- Smart Mobility
- Energy Management
- Healthcare
- Public Safety and Security
- Waste Management
- Environmental Monitoring
- Water Management
- Others
AI in the Smart Cities Market- By Deployment Mode
- Cloud-based
- On-premises
AI in the Smart Cities Market- By End-User
- Government
- Utilities
- Transportation Companies
- Healthcare Providers
- Real Estate Developers
- Others
AI in the Smart Cities Market- By Region
North America-
- The US
- Canada
- Mexico
Europe-
- Germany
- The UK
- France
- Italy
- Spain
- Rest of Europe
Asia-Pacific-
- China
- Japan
- India
- South Korea
- South East Asia
- Rest of Asia Pacific
Latin America-
- Brazil
- Argentina
- Rest of Latin America
Middle East & Africa-
- GCC Countries
- South Africa
- Rest of the Middle East and Africa
Research Design and Approach
This study employed a multi-step, mixed-method research approach that integrates:
- Secondary research
- Primary research
- Data triangulation
- Hybrid top-down and bottom-up modelling
- Forecasting and scenario analysis
This approach ensures a balanced and validated understanding of both macro- and micro-level market factors influencing the market.
Secondary Research
Secondary research for this study involved the collection, review, and analysis of publicly available and paid data sources to build the initial fact base, understand historical market behaviour, identify data gaps, and refine the hypotheses for primary research.
Sources Consulted
Secondary data for the market study was gathered from multiple credible sources, including:
- Government databases, regulatory bodies, and public institutions
- International organizations (WHO, OECD, IMF, World Bank, etc.)
- Commercial and paid databases
- Industry associations, trade publications, and technical journals
- Company annual reports, investor presentations, press releases, and SEC filings
- Academic research papers, patents, and scientific literature
- Previous market research publications and syndicated reports
These sources were used to compile historical data, market volumes/prices, industry trends, technological developments, and competitive insights.
Primary Research
Primary research was conducted to validate secondary data, understand real-time market dynamics, capture price points and adoption trends, and verify the assumptions used in the market modelling.
Stakeholders Interviewed
Primary interviews for this study involved:
- Manufacturers and suppliers in the market value chain
- Distributors, channel partners, and integrators
- End-users / customers (e.g., hospitals, labs, enterprises, consumers, etc., depending on the market)
- Industry experts, technology specialists, consultants, and regulatory professionals
- Senior executives (CEOs, CTOs, VPs, Directors) and product managers
Interview Process
Interviews were conducted via:
- Structured and semi-structured questionnaires
- Telephonic and video interactions
- Email correspondences
- Expert consultation sessions
Primary insights were incorporated into demand modelling, pricing analysis, technology evaluation, and market share estimation.
Data Processing, Normalization, and Validation
All collected data were processed and normalized to ensure consistency and comparability across regions and time frames.
The data validation process included:
- Standardization of units (currency conversions, volume units, inflation adjustments)
- Cross-verification of data points across multiple secondary sources
- Normalization of inconsistent datasets
- Identification and resolution of data gaps
- Outlier detection and removal through algorithmic and manual checks
- Plausibility and coherence checks across segments and geographies
This ensured that the dataset used for modelling was clean, robust, and reliable.
Market Size Estimation and Data Triangulation
Bottom-Up Approach
The bottom-up approach involved aggregating segment-level data, such as:
- Company revenues
- Product-level sales
- Installed base/usage volumes
- Adoption and penetration rates
- Pricing analysis
This method was primarily used when detailed micro-level market data were available.
Top-Down Approach
The top-down approach used macro-level indicators:
- Parent market benchmarks
- Global/regional industry trends
- Economic indicators (GDP, demographics, spending patterns)
- Penetration and usage ratios
This approach was used for segments where granular data were limited or inconsistent.
Hybrid Triangulation Approach
To ensure accuracy, a triangulated hybrid model was used. This included:
- Reconciling top-down and bottom-up estimates
- Cross-checking revenues, volumes, and pricing assumptions
- Incorporating expert insights to validate segment splits and adoption rates
This multi-angle validation yielded the final market size.
Forecasting Framework and Scenario Modelling
Market forecasts were developed using a combination of time-series modelling, adoption curve analysis, and driver-based forecasting tools.
Forecasting Methods
- Time-series modelling
- S-curve and diffusion models (for emerging technologies)
- Driver-based forecasting (GDP, disposable income, adoption rates, regulatory changes)
- Price elasticity models
- Market maturity and lifecycle-based projections
Scenario Analysis
Given inherent uncertainties, three scenarios were constructed:
- Base-Case Scenario: Expected trajectory under current conditions
- Optimistic Scenario: High adoption, favourable regulation, strong economic tailwinds
- Conservative Scenario: Slow adoption, regulatory delays, economic constraints
Sensitivity testing was conducted on key variables, including pricing, demand elasticity, and regional adoption.
Request Customization
Add countries, segments, company profiles, or extend forecast — free 10% customization with purchase.
Customize This Report →Enquire Before Buying
Speak with our analyst team about scope, methodology, pricing, or deliverable formats.
Enquire Now →Frequently Asked Questions
The AI in Smart Cities Market Size was valued at USD 36.9 Bn in 2023 and is predicted to reach USD 138.8 Bn by 2031
The AI in Smart Cities Market is expected to grow at a 18.1% CAGR during the forecast period for 2024-2031.
IBM Corporation, Microsoft Corporation, Google LLC, Intel Corporation, Cisco Systems, Inc., Siemens AG, Huawei Technologies Co., Ltd., NVIDIA Corporat