AI in Construction Market Driven by the Growing Demand for Advanced Safety Measures

Market Research Future has published a Half-Cooked Research Report on the Global AI in Construction Market.

AI in Construction Market Outlook

In its research report, Market Research Future (MRFR), asserts that the global AI in Construction market 2032 is slated to grow exponentially over the review period, securing a considerable market valuation of USD 2.87 Billion, and a healthy 32.66% CAGR over the review period.

Drivers and Restraints

Over the forecast period, the AI in Construction Market is projected to rise significantly. Increasing demand for safety considerations and shortening project delays with accuracy are expected to drive the development of AI in the building market over the evaluation period. AI-enabled applications in the construction sector is at a nascent stage and are presumed to be witnessing their integration with Building Information Modeling (BIM) and GPS which would be very helpful for project planning, scheduling and inventory purposes. In addition, the AI is expected to support the construction sector in mitigating the current and repetitive challenges of precision margin, project schedule delay, and security concerns that are presumed to be one of the key drivers of AI growth in the construction market over the evaluation period. On the flip side, the slow rate of AI adoption in the construction sector and the complex algorithms to build unique construction programs are expected to inhibit AI growth in the construction market over the forecast period.

Segmental Analysis

The AI in construction market is differentiated by component, technology, organization size, deployment, stage, and application.

On the basis of stage, the market is segmented into construction stage, pre-construction, and post-construction.

Based on the component, the AI in construction market is bifurcated as solutions and services. The solution segment is categorized as demand forecasting, virtual assistant, revenue estimation, design & planning, predictive maintenance, and others.  The service sub-segment comprised implementation services, training & consulting, and other support services.

In terms of technology, the market is segregated into machine learning & deep learning, neural networks, and natural learning programming (NLP).

Based on the deployment, the market is divided into on-cloud and on-premise.

Based on the organization size, the market is bifurcated into large enterprises, and small & medium enterprise (SMEs).

On the basis of application, the market is categorized as, project management, schedule management, risk management, equipment management, building information management, and supply chain management.

Regional Overview

The geographical overview of the global market has been analyzed in four major regions, comprising the Asia Pacific, North America, Europe, and the rest of the world.

On the building industry, North America is believed to have substantial growth in the AI, with the U.S. and Canada being the sector leading countries. Regional domination is due to increased investment by companies such as IBM Corporation, Oracle Corporation and many others, which invest directly in the advancement of technologies such as neural networks and machine learning in research and development.

However, Asia Pacific is also expected to experience a strong market growth rate. The leading countries in this field are China, Japan, South Korea and India. The market growth is due to rise in demand by the region to improve smart city projects which require better facilities that boost the real estate sector.

Competitive Synopsis

The major market players operating in the global market as identified by MRFR are Oracle Corporation (U.S), IBM Corporation (U.S.), SAP SE (Germany), Alice Technologies.(U.S.), Microsoft Corporation (U.S.), Autodesk (U.S.), Aurora Computer Services(U.K), eSUB (U.S.), Smartvid.io(U.S.),and Building System Planning (U.S.).

Some other market players who are involved in AI construction market are Jaroop, Deepomatic, Lili.Ai, Predii, Assignar, Coins Global, Beyond Limits, Doxel Askporter, Bentley Systems, Plangrid, and Renoworks Software