Unlocking AI’s Full Potential in Construction
How can we ensure successful AI adoption in our projects? Murillo Piazzi explores the proven tripod for digital transformation – Process, People, Technology.
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Murillo Piazzi
Senior Digital Consultant
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January 15, 2025
From the importance of structured data to the need for secure systems and quality assurance, Murillo sets out key steps to making AI a trusted partner in delivering efficient and sustainable projects.

If you ask an information manager what the best way is to implement a new digital tool on your project, they will be fast to respond that any effective implementation will be supported by a tripod composed by process, people and technology. This has been true and verified for many innovation cycles in the construction industry, including the implementation of Building Information Modelling (BIM). Nothing indicates that this will be different for the implementation of Artificial Intelligence (AI).
The core idea is that new tools or processes are designed to address industry challenges, requiring people to upskill and collaborate for successful adoption. For instance, coordinating designs across teams has always been a complex task for design teams. In response, software vendors developed 3D coordination analysis technology, and over time, processes evolved to support their use. This included adding contractual clauses to define responsibilities, such as who uses the tools and who participates in clash resolution. Simultaneously, people needed the expertise to work within a digital clash detection framework.
In the construction industry, technology typically leads innovation, with processes and people adapting afterward – an evident trend in the rise of AI tools. Despite the increasing availability of AI solutions, there is minimal guidance on how clients can effectively procure or integrate them into their projects. Below are three critical considerations for clients looking to create a robust framework for AI implementation:
The value of structured data
While structured data is not a strict requirement for implementing AI, having consistently named and classified files, such as drawings and reports, can significantly enhance AI’s effectiveness. Organised data helps AI systems to identify project patterns faster, saving time and resources. Thus, clients should prioritise structured data as a deliverable, either before or alongside AI implementation.
Consider a closed system
Information security is a topic that often arises when people are discussing the use AI for a given task – a fair concern. Any information you share with systems like ChatGPT, Google’s Gemini or Microsoft’s Copilot will be stored somewhere and can be used to generate future responses. In this process confidential information might be shared with an audience that are not meant to access this information. Fortunately, there are companies that can provide closed-systems solutions. This means that the information shared with the AI will not be shared externally and will remain withing the boundaries of your organisation. If intellectual property and data security are a concern in your organisation, then you might want to consider asking for a closed AI system.
Always check the work
“ChatGPT can make mistakes. Check important info.” is always present at the bottom of ChatGPT’s webpage. Indeed, from time-to-time AI can provide unexpected results. Incorrect information can introduce risks to organisation’s products and reputation. Therefore, companies that implement quality check / assurance measures to make sure that information produced by employees is reliable should extend their processes to cover the information being produced by the AI systems. Including clauses in contracts that mandate QC/QA for AI-generated content can help minimise risks.
The construction industry’s journey toward embracing Artificial Intelligence represents an extraordinary opportunity to reshape processes, empower people, and leverage technology to tackle longstanding challenges. By laying the groundwork with structured data, prioritising secure and reliable systems, and incorporating robust quality assurance measures, we can ensure AI becomes a trusted partner in delivering more efficient, innovative, and sustainable projects.
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