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.
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.
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.
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.
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.
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Report Attribute |
Specifications |
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Market Size Value In 2023 |
USD 36.9 Bn |
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Revenue Forecast In 2031 |
USD 138.8 Bn |
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Growth Rate CAGR |
CAGR of 18.1% from 2024 to 2031 |
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Quantitative Units |
Representation of revenue in US$ Bn and CAGR from 2024 to 2031 |
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Historic Year |
2019 to 2023 |
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Forecast Year |
2024-2031 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Deployment Mode, By Application, By Component, By End User |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea |
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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. |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
AI in the Smart Cities Market- By Component
AI in the Smart Cities Market- By Application
AI in the Smart Cities Market- By Deployment Mode
AI in the Smart Cities Market- By End-User
AI in the Smart Cities Market- By Region
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
