The future of the construction industry will be shaped by a range of disruptive themes, with artificial intelligence (AI) being one of the themes that will have a significant impact on construction companies.A detailed analysis of the theme, insights into the leading companies, and their thematic and valuation scorecards are included in GlobalData’s thematic research report,Artificial Intelligence (AI) in Construction – Thematic Research.  Buy the report here.

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The uptake of AI technologies in construction has been slow, but AI has the potential to deliver tangible benefits at every step of the construction value chain, from conceptual design to operations and maintenance. The AI market can be difficult to size, as the technology is often embedded into larger systems. Furthermore, GlobalData predicts that construction companies will spend additionally on AI platforms by 2024 wherein the spending is expected to increase by 19.2%.


The construction industry is ripe for AI adoption. Since the construction value chain is fragmented, effective collaboration and communication between multiple stakeholders is key. AI-powered tools can automate processes and provide intelligent business insights, from sending documents and responding to requests for information (RFIs) to tracking open issues and automatically notifying participants when reality deviates from plans. There is growing potential for AI to augment productivity at the construction stage. Smart robots and context-aware computing can alleviate current industry-wide productivity stagnation and protect against the shortage of skilled labour workers.

However, not all companies are equal when it comes to their capabilities and investments in the key themes that matter most to their industry. Understanding how companies are positioned and ranked in the most important themes can be a key leading indicator of their future earnings potential and relative competitive position.

According to GlobalData’s thematic research report, AI in Construction, leading adopters include: Acciona, AECOM, Bechtel, Doosan, Samsung, Shimizu, Siemens, Skanska, and Vinci.

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Acciona has developed its BIONS (Business Intelligence of Network Solutions) system in-house. Using collected data and machine learning (ML) techniques, BIONS detects and analyses problems in water supply networks. The company’s AI-powered Maestro platform is also supporting the Umm Al Houl desalination plant in Qatar.


AECOM partners with many AI-specialist companies to enhance their services such as EnginSoft’s ML-powered StrategicGiant to forecast the flooding impact of future housing developments. The company is also developing its own AI-powered platform, Capture, to aid project management and analyse the construction process over time.


Shimizu is rolling out Shimz Smart Site at the Toranomon-Azabudai District urban redevelopment project. On-site, humans and AI-equipped autonomous robots collaborate to perform construction work. Robo-welder, which has six arms with human-like movement, is already in operation, and Robo-carrier, an automated conveyor robot that can pick up palletised materials and load them onto a freight elevator, was rolled out in mid-2021. The company also partners with specialist AI providers, such as CV start-up OpenSpace, to automatically document and capture construction site images. In 2020, the company also debuted an AI suitcase designed for the visually impaired.

To further understand the key themes and technologies disrupting the construction industry, access GlobalData’s latest thematic research report on AI in Construction.

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Frequently asked questions

  • 1. How are Construction companies using artificial intelligence (AI)?

    Construction companies are using artificial intelligence (AI) in various ways to improve their operations. AI is being used for tasks such as conceptual design, feasibility studies, financing, procurement, construction, and operation and maintenance. It helps in optimizing project planning, bidding, and building processes. AI technologies like deep learning and neural networks are being employed to analyze data, generate insights, and make predictions. For example, ALICE Technologies has developed a construction optioneering platform that uses AI algorithms to determine optimal sequences and plans for building projects.

  • 2. How does artificial intelligence impact the Construction industry?

    Artificial intelligence has a significant impact on the construction industry. It helps in mitigating historical construction issues such as inaccurate cost estimates, optimistic timelines, and lack of risk analysis. AI enables construction companies to improve productivity, enhance decision-making capabilities, and streamline processes across the project lifecycle. It facilitates effective data management by providing intelligent data processing and analysis capabilities. AI algorithms using machine learning and natural language processing techniques assist in collecting, cleaning, and updating data. AI also enables generative applications, improving customer service, navigation of building information, and automating data filtering and processing.

  • 3. Who are leading adopters of artificial intelligence (AI) in Construction?

    Leading adopters of artificial intelligence (AI) in the construction industry include companies like Skanska, Shimizu, Siemens, AECOM, Bechtel, Balfour Beatty, Larsen & Toubro, Laing O'Rourke, Willmott Dixon, and Honeywell.

  • 4. Who are the leading vendors of artificial intelligence (AI) solutions to the Construction industry?

    The leading vendors of artificial intelligence (AI) solutions to the construction industry include ALICE Technologies, Autodesk, Trimble, Buildots, and Procore.

  • 5. How can machine learning, data science, and context-aware computing help Construction companies?

    Machine learning, data science, and context-aware computing play crucial roles in helping construction companies. Machine learning algorithms can analyze large datasets to identify patterns, make predictions, and optimize processes. Data science techniques enable effective data management, including data extraction, cleaning, normalization, and anomaly detection. Context-aware computing ensures that AI systems understand and adapt to the specific context of construction projects, improving accuracy and efficiency. These technologies enable construction companies to make data-driven decisions, enhance productivity, and streamline operations.

  • 6. What are the challenges with adoption of artificial intelligence in Construction?

    The adoption of artificial intelligence (AI) in the construction industry faces several challenges. The industry has been historically slow in digitalization, making it difficult to process the vast and complex datasets required for building information management (BIM). The construction sector's tight profit margins, critical deadlines, and health and safety considerations make it hesitant to invest in new technology. Additionally, specialized AI applications need to be developed and integrated accurately to address the unique requirements of the construction industry. Overcoming these challenges requires collaboration, investment, and a focus on specialized AI solutions.

  • 7. What is the projected market size of artificial intelligence in Construction?

    According to GlobalData forecasts, the total artificial intelligence (AI) market in the construction industry is expected to grow at a compound annual growth rate (CAGR) of 35.2% from 2022 to 2030. This growth is driven by the increasing adoption of AI technologies in construction processes, the potential for productivity gains, and the continued digital transformation of the industry.

  • 8. Who are the leading specialist artificial intelligence vendors in Construction?

    The leading specialist artificial intelligence (AI) vendors in the construction industry include ALICE Technologies, Autodesk, Trimble, Buildots, and Procore. These vendors specialize in developing AI solutions specifically tailored for the construction sector. They offer platforms and tools that assist in project planning, bidding, building, and data management.

  • 9. What are the components of the artificial intelligence value chain?

    The artificial intelligence (AI) value chain in the construction industry consists of several components. These include hardware, data management, foundational AI, advanced AI capabilities, and delivery. Hardware components include semiconductors, cameras, sensors, and edge equipment. Data management involves collecting, cleaning, and updating data throughout the project lifecycle. Foundational AI includes machine learning algorithms and natural language processing techniques. Advanced AI capabilities encompass computer vision, conversational platforms, and other sensory AI technologies. Delivery involves the implementation and deployment of AI solutions in construction processes.


GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData’s Thematic Scorecard ranks companies within a sector based on their overall leadership in the 10 themes that matter most to their industry, generating a leading indicator of their future earnings and relative position within key strategic areas.