Artificial Intelligence (AI) is rapidly changing the way we generate and communicate ideas. For construction companies, AI offers a major opportunity to produce better ideas faster. However, it could also create some level of risk if the technology is trusted when it should not be. The objective of this research is to define various use cases for AI to support decision-making among members of the electrical construction industry who are involved with ELECTRI International.

For this project, researchers recruited electrical construction experts from ELECTRI Council companies to participate in in-depth interview sessions. The primary focus of these interviews was to ask participants to describe AI successes and failures and consider why AI supported or failed to support their needs. Each interview lasted for 30 to 45 minutes.

The research team analyzed and organized responses using an easy-to-understand “stoplight” framework to present findings. In this report, there are two main “stoplight” frameworks:

1. Current AI use cases “stoplight” framework—identifies use cases for AI where current technology is mature enough to provide value (i.e., green light); use cases where AI may offer value, but involves increased risk if used in the wrong ways (i.e., yellow light); and use cases where AI is either not yet mature enough or would introduce too much risk to trust (i.e., red light).

2. Prospective AI use cases “stoplight framework”—explores interviewees’ perspectives on tasks, processes, and workflows where AI can be adopted (i.e., green light), may be adopted with caution (i.e., yellow light), or should not be adopted (i.e., red light)

The report additionally includes one-page descriptions of each of the use cases that interviewees discussed. These one-page summaries include a process map of the use case described, the positive attributes of AI in the context described, and the negative aspects of AI in this context.