MIT and Suffolk release study on how AI is reshaping construction productivity
Suffolk, along with the MIT Center for Real Estate and MIT Media Lab City Science group, released a study examining how AI is reshaping construction performance and productivity.
“Construction in the Age of AI,” looks at where AI can deliver the most meaningful gains in processes, scheduling, and project feasibility. Pulling from academic research and industry input, the report identifies six areas where AI is improving construction performance across the project lifecycle.
The construction industry continues to face declining productivity, fragmented project delivery, limited technology investment and persistent pressure from rising costs and labor shortages, according to a news release.
Long approval timelines, siloed data, and disconnected workflows have made it hard for owners, builders, designers and regulators to improve performance at scale. AI has the potential to solve these challenges, helping teams process information faster, coordinate work earlier, and make better decisions across a project's lifecycle.
The study identified priority domains where AI shows the greatest near-term potential:
- Design automation: Evaluate design options earlier, balancing cost, constructability, performance and code requirements
- Offsite manufacturing: Support prefabricated and modular construction by connecting design, production, and delivery
- Permitting: Interpret building codes and support more efficient compliance and permit reviews
- Scheduling: Create more responsive schedules that identify risk and coordinate sequencing, labor, and materials as conditions change
- Skilled labor and subcontracting: Reduce administrative work and help field teams and trade partners access the information, materials, and approvals they need when they need them
- Supply chain and procurement: Connect design decisions to available products, helping teams plan around what can be sourced, manufactured, and delivered
In one sample multifamily project, Suffolk's model suggests the combined application of the six AI-enabled areas of improvement could create 17% to 20% total cost savings and 22% to 25% total schedule savings.
