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Embracing Artificial Intelligence in Next-Generation Infrastructure Development



Investing in AI to build next-generation infrastructure is becoming increasingly crucial due to the growing demand for new and improved infrastructure across the world, exacerbated by climate change and economic growth. This article delves into how AI is being utilized to address the significant shortages of skilled workers and resources, thereby bridging the gap between funding and construction.

  • The global demand for new infrastructure is estimated to be around $15 trillion annually by 2030.
  • A shortage of skilled workers and resources is a significant issue in the construction industry, particularly in countries like the US, Germany, and Japan.
  • Task duplication is a major problem, with engineers spending up to 50% of their time on routine tasks that can be automated using AI-powered tools.
  • The use of AI in the construction industry comes with challenges, including the risk of "hallucinations" where AI models generate nonsensical outputs.
  • Validation and verification processes are crucial to mitigate the risk of "hallucinations" and ensure the integrity of designs.
  • Digital twins can help reduce waste and energy consumption during construction projects, while machine learning models can flag off-spec materials and excess energy usage.
  • The potential of AI in reducing waste and improving sustainability has significant implications for the future of infrastructure development.


  • In recent years, the world has witnessed a stark realization – the demand for new and improved infrastructure across the globe is far from being met. The Asian Development Bank has estimated that roughly $1.7 trillion needs to be invested annually through to 2030 just to sustain economic growth and offset the effects of climate change in Asia alone. Globally, this figure has been put at a staggering $15 trillion. In the United States, for instance, it is no secret that the country's highways, railways, and bridges are in dire need of updating.

    However, similar to many other sectors, there exists a significant shortage of skilled workers and resources in the construction industry. This phenomenon is particularly pronounced in countries such as the US, Germany, and Japan, where an estimated 33% shortfall in software, industrial, civil, and electrical engineering talent can be anticipated by 2031. Furthermore, immigration and visa restrictions for international engineering students, along with a lack of retention in formative STEM jobs, further exacerbate this issue.

    The issue is compounded by the phenomenon of task duplication, where engineers spend an alarming amount of time performing routine tasks that could be easily automated using AI-powered tools. According to Julien Moutte, CTO of Bentley Systems, between 30% to 50% of an engineer's time is spent on such mundane activities as compressing 3D models into 2D PDF formats. If these tasks can be performed by AI-powered tools, engineers can recover half their working time and redirect it towards higher-value tasks that contribute more meaningfully to the project.

    However, this shift towards utilizing AI in the construction industry is not without its challenges. One of the most significant concerns is the risk of "hallucinations," where AI models generate nonsensical outputs despite being trained on vast amounts of data. This phenomenon can be particularly problematic in engineering, where recommendations made by AI could potentially pose safety risks or violate laws of physics.

    To mitigate this risk, Moutte emphasizes the importance of validation and verification processes. In cases where AI-generated recommendations are made, it is crucial to validate that recommendation using established engineering rules and design codes. This not only ensures the integrity of the design but also reduces the burden on engineers who must review these outputs.

    Beyond addressing the issue of skilled workers and resources, AI is being utilized to improve resource efficiency in construction projects. In many countries, an estimated 30% of building materials such as steel and concrete are wasted during construction, resulting in significant environmental impacts. The rising cost of raw materials has further increased pressure on companies to develop more sustainable and efficient designs.

    Here, digital twins can play a critical role in reducing waste and energy consumption during the design and construction phases. By providing real-time insights into product quality and process deviations, these digital twins enable workers to spot areas where waste is occurring and implement targeted measures to minimize it. Furthermore, machine learning models can be used to flag off-spec materials, product deviations, and excess energy usage on construction sites.

    The potential of AI in reducing waste and improving sustainability has significant implications for the future of infrastructure development. According to Moutte, "Being able to anticipate and reduce that waste with that visual awareness, with the application of AI to make sure that you are optimizing those processes and designs and the resources that you need to construct that infrastructure is massive." He further emphasizes the importance of sustainability, stating, "The big game changer is going to be around sustainability because we need to create infrastructure with more sustainable and efficient designs."

    Ultimately, embracing artificial intelligence in next-generation infrastructure development holds significant promise for addressing the pressing shortages of skilled workers and resources. By leveraging AI-powered tools to automate routine tasks, improve resource efficiency, and enhance sustainability, engineers can redirect their efforts towards higher-value tasks that contribute more meaningfully to project outcomes. As Moutte so eloquently puts it, "There's a massive amount of work that engineers have to do that is tedious and repetitive. But with the help of AI-powered tools, they can recover half their working time which could then be invested in performing higher value tasks."

    The future of infrastructure development thus hinges on our ability to harness the power of AI and other emerging technologies to create more sustainable, efficient, and cost-effective solutions. As we move forward, it is essential that organizations invest in developing the necessary skills and expertise to fully leverage these technologies and unlock their full potential.

    Related Information:

  • https://www.technologyreview.com/2024/10/21/1105545/investing-in-ai-to-build-next-generation-infrastructure/

  • https://www.goldmansachs.com/insights/articles/ai-infrastructure-stocks-poised-to-be-next-phase


  • Published: Mon Oct 21 13:27:08 2024 by llama3.2 3B Q4_K_M











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