AI for Construction: 5 Tips to Get Started

If you are unclear on the actual process of sourcing, implementing, and managing a new AI program, look no further. As AI and ML gain traction as valuable business tools, leaders will have to recognize their importance and build a strategy to fold these technologies into their companies. Certainly every organization is different, but there are universal guidelines to consider in this process.

We have laid out 5 key pillars that should be a part of any AI strategy for those working in the build world.

1. Experiment early with pilot projects, but don’t get stuck in “pilot purgatory”.

Pilot projects are a great way to demonstrate the value of a new technology, but there is a tendency for pilots to get stuck in purgatory. Pilots are valuable in that they mitigate risk, they allow for hypotheses and ideas to be tested, and they convince skeptical team members of the investment, but an AI or ML program will only have lasting, real outcomes when it is scaled and implemented as an integral piece of the organization.

2. Target a specific project or department and leverage on its success

Rolling out an AI package that is focused on addressing a specific corporate department, such as Business Development, Finance, HR, or Legal, gives the AI program a better chance to succeed. Even targeting the scope of work within a project– such as the supply chain or bidding process– is a great place to start. It helps to think about which department might be most ready for an AI program– and you might be pleasantly surprised to learn you’re more ready for an AI program than you would expect. Build a strong strong case in your area of influence, and expand to other departments and projects from there.

3. Ready your team to embrace a “human in the loop” mentality

Investing in an AI program is not about handing over the keys of your car to a robot and hoping for the best. In its initial phase, your AI models needs oversight and training like any other valuable employee. It needs to be taught, calibrated, and monitored by someone or a team of people in the organization– we call this a “human in the loop”. This individual or group ensures the algorithm is processing your data correctly and that it is set up to produce the insight you’re looking for.

4. Be prepared to take action on your intelligence

The goal of an AI program is not solely to have an AI program. After all the time and effort you put into piloting a project, then tuning and teaching these algorithms, you will see answers and insight into questions and opportunities you didn't know existed. Be prepared and ready to take action on those insights and build objectives around them. Sometimes these findings will allow you to ask better questions of the AI program and to target aspects of your data in more creative ways. Sometimes they will reveal uncomfortable truths about the way your business or project is running. In either scenario, the investment you make is only as good as the action you take.

5. Work with a partner to manage this process

Sure, we’re biased at Briq because we believe in the power of building better technology to help those that build our world. Our AI programs are built specifically for the construction process, and many of our modules are already taught and tuned to listen for construction-specific issues. Every company, despite the state of your data history, can benefit in some capacity from our platform. Getting a quick win early into the process will make the path for AI in your company that much easier, and bring long term value to every project you touch.

Ellis Talton