The 3Cs Framework — A Strategic Guide to A.I. in Construction
Despite their regional status and reputation for reliable work, a mid-sized construction company faced an undeniable truth: they were falling behind competitors who had embraced artificial intelligence.
The realization came gradually, then all at once. Late last year, they began receiving automated emails from the general contractors on their projects. Though the emails were sent by actual people, it was clear that A.I. had generated some of the information requests and submittals.
Soon after, they noticed an acceleration in the pace at which other firms were iterating on layouts and design options. Changes and constructability reviews that used to take weeks were now being completed in hours.
Finally, in recent months, long-standing general contractor clients — partners they had worked with for decades — began reporting that delays, cost overruns, and communication breakdowns, while still an issue, were considerably less frequent on projects handled by their competitors already utilizing A.I. tools.
The company started losing work.
It was a double-edged sword. The client relationships that had nurtured the family business for decades and expanded it to a team of over 50 employees had, ironically, fostered a sense of complacency, insulating them from the industry’s swift pivot toward an A.I.-driven future.
Confronted with these growing challenges, the company realized that establishing a dedicated A.I. Committee was essential to navigating this new landscape and ensuring its future competitiveness.
A.I. is no longer a luxury but a necessity for the construction industry. With technology advancing rapidly, the integration of A.I. has become essential for firms determined to remain competitive. When done well, A.I. Committees help steer this future direction and build the internal muscle that sustains responsible A.I. use.
Today’s A.I. promises to streamline operations and drive innovation, making it a game-changer across the industry.
Companies that act swiftly to integrate A.I. into their operations will gain a significant advantage, while those who delay risk falling behind. The time to act is now, and for many, the first step in this journey is the formation of an A.I. Committee.
In early 2023, not long after ChatGPT’s release, there was an annual gathering of CIOs from large construction companies. It was the first time that they’d met since ChatGPT’s release — and they were nervous.
Publicly available, this new large language model had finally landed on the radar of the wider industry and people everywhere were starting to use them for daily work. By the time Placer Solutions’ industry research was released, nearly two-thirds of construction survey respondents had indicated that they used the tools at least weekly.
This was the first technology to take off like wildfire among frontline construction teams. While still primarily a non-manual tool, project teams were already organically using ChatGPT and Google Gemini for everything from cross-referencing industry codes to drafting emails.
A sizeable number of the CIOs attending the meeting were in favor of locking down access to ChatGPT for their organizations. Concerned about the risks associated with large language models — such as hallucinations and data security — they thought it best to take a cautious approach.
Since then, as the implications and risks of the technology have reached nearly all construction companies, I’ve witnessed that most mid and small-sized construction firms have either taken a wait-and-see approach or simply not done anything too proactive about A.I.
Over the course of 2024, I’ve advised more and more construction companies on implementing A.I. task forces for their business. This article provides a general framework for how construction companies can begin strategically approaching A.I., based on years of consulting across the industry on A.I. and understanding the concerns and best practices that exist today.
This framework is designed to guide construction firms through this pivotal moment. It encourages a proactive approach, ensuring that A.I. is not just “implemented”, but integrated into the very fabric of the organization.
Pillar #1: Core Strategy
Key considerations: Technology understanding, market research, cross-functional alignment, internal vs. external development, partnership strategy, use case prioritization
The first step for an A.I. Committee is to thoroughly understand what technologies exist today and how these can address your core business needs. This means that it’s not enough to document business requirements; your team must also grasp existing technologies (and anticipate future ones) to align these innovations with your business needs.
In summary, this requires getting smart about where technology stands in relation to your Core Strategy.
To accomplish this, your A.I. Committee should develop a working understanding of concepts like large language models, explainable A.I., secure A.I. systems, data controls, A.I. computing costs, and enterprise data architecture.
Hiring an outside consultant or creating a task force within the A.I. Committee to help your team on these concepts is a critical first step. While you don’t need PhDs in A.I. technology, it’s essential for the A.I. Committee to be able to differentiate reality from hype and fact from fiction.
Because construction is an industry of industries, each with its own unique challenges, your business is likely tailored to meet specific client needs with your own diverse cost centers and business workflows.
Your project delivery might include activities like estimating, engineering, preconstruction planning, quality control, material procurement, field management, equipment management, environmental, safety, and/or IT, to name just a few.
At a certain size, functional silos tend to exist — at least culturally, if not operationally — in nearly all construction companies. If these silos remain unaddressed, they can lead to misaligned priorities, duplicated efforts, and inefficient use of resources.
To mitigate these risks, it’s important to involve a cross-section of leaders from within the organization to help vet and align A.I. initiatives.
Developing a use case prioritization matrix can be particularly effective in this process. This matrix helps prioritize your A.I. use cases based on factors like potential impact and feasibility, ensuring that resources are directed towards initiatives that offer the greatest value. The process of achieving this level of business alignment will facilitate resource planning, align technical needs, break down silos, and ultimately enhance the long-term success of your A.I. initiatives.
Pillar #2: Compliance
Key considerations: Understanding A.I. risks, data privacy and security, hallucinations, explainable A.I., governance frameworks, continuous monitoring of A.I. tools
Once Core Strategy is established, the insights gained will position the task force to effectively implement guardrails for responsible A.I. use across the business.
This begins with the A.I. Committee’s solid understanding of A.I. concepts, which helps inform the potential risks and shortcomings at a business level. A practical first step is to review your existing company policies to identify areas that need updates or expansion to accommodate A.I. technologies.
Don’t get overwhelmed. In many cases, your business operations already has safeguards in place to address concerns that A.I. adoption raises. While the unique risks of A.I. are important, remember that this isn’t the first technology to impact construction — similar policies likely already exist for tools like social media or use of design and project management software.
For example, if you’re a design-build firm integrating A.I. into your operations, you may need to update your data handling policies to ensure that client data that is used by A.I. systems is securely stored, processed, and anonymized where necessary.
While this might align with existing project data protocols, A.I. introduces new challenges — specifically, the risk that data could be used to train algorithms and inadvertently appear in outputs for other customers. To mitigate this, your policies might update existing ones to specify that only vetted A.I. solutions that either anonymize data, limiting training, or avoid using sensitive project data are permitted.
Additionally, you might establish protocols for monitoring A.I.-generated designs to ensure that they comply with your standards. This might involve setting up processes for human oversight, where A.I.-driven decisions are flagged as A.I.-generated during the review process in order to ensure that they’re reviewed by qualified professionals before implementing.
Keep in mind, these approaches are not unlike existing processes. The review process in particular is like a professional stamp on a final design — a process that you’re likely already familiar with.
When addressing compliance, considerations could include:
- Establishing a governance framework for project-based work that ensures that the A.I. Committee’s recommendations are embedded into the project planning, execution, and handover phases of a project.
- Appointing an A.I. compliance officer or SME to oversee A.I. initiatives, conduct audits, and serve as the point of contact for compliance-related issues.
- Engaging third-party auditors or consultants for periodic reviews of A.I. systems and processes to ensure adherence to industry best practices and regulatory requirements.
- Updating legal agreements like contracts, NDAs, and other legal agreements to include clauses specific to A.I. use, such as data usage rights, intellectual property concerns, and liability for A.I.-generated outcomes.
These guardrails are intended to maximize the benefits of A.I. while minimizing risks. With a strong understanding of both the business and the technology, the A.I. Committee should be able to efficiently navigate these challenges and set the company’s use of these tools in a responsible direction.
Pillar #3: Communication
Key considerations: Employee training and awareness, change management, learning & development, consistency in messaging, highlighting quick wins, leadership visibility and support
At the end of the day, the success of the A.I. Committee’s work depends on its integration into your daily operations. This is where the rubber meets the road in construction — on the ground, with people in the field and on projects.
Change management is perhaps the most challenging aspect and it all starts with leadership and effective communication. In construction, where project and field teams are constantly on the move, consistently communicating and adapting best practices to project-specific demands is not always easy.
Standard playbooks that work in other industries often fall short here. Fragmentation and project-based work in construction means that change management must be handled on a case-by-case basis for each organization.
This is where your A.I. Committee’s dedication comes full circle. Having engaged Core Strategy with a diverse cross-functional team and developing Compliance to ensure responsible A.I. use, the committee will be equipped with a deep understanding of both the business and the technology. This positions them perfectly to lead the communication of these initiatives to the wider organization.
Effective communication can take various forms depending on the organization:
- Leveraging existing internal communication channels, such as functional newsletters or weekly email updates, to keep the company informed about the A.I. Committee’s progress
- Demonstrating strong executive support for A.I. initiatives, through messages from the CEO or discussions at all-hands meetings, where employees can openly engage with the topic.
- Developing a centralized online resource hub where employees can access information about A.I. tools, company policies, best practices, and training materials.
- Distributing project playbooks that educate frontline employees on the opportunities and risks of A.I., as well as the new policies designed to address them.
- Hosting hands-on workshops where employees can directly engage with A.I. tools and ask questions about them.
- Establishing a champion network where employees who are early adopters of A.I. can mentor others and spread knowledge organically throughout the organization — these are especially powerful in construction because the industry’s work is so project and field-based.
People often talk about fostering a “culture of innovation” in construction, but this needs to be backed by practical advice that truly understands the challenges of change in this industry. Communication is the key piece and it must address the real concerns of employees in your organization — and we know from Placer Solutions’ research that people in our industry are already thinking seriously about A.I. as a concern.
Failing to communicate effectively can lead to the worst of both worlds: employees using A.I. in risky, suboptimal ways that puts the company’s integrity on the line. In construction, where shadow IT on projects is already prevalent, employees are likely to be using these tools regardless of whether or not they’re officially sanctioned.
If the A.I. Committee does its job well, the company will be positioned to maximize the benefits of A.I. while mitigating its risks. The committee will become a center of excellence for a technology that has the potential to profoundly change our industry.
Nate Fuller is a passionate and accomplished construction technology leader with a diverse background in corporate innovation, construction technology, and entrepreneurship.
His proven track record defining strategy and directing change management in construction has helped North America’s largest construction contractors build and scale effective technology programs.
If you found this article insightful, please consider signing up for my newsletter at placersolutions.io
