Some of the major challenges facing the construction industry — declining productivity, fragmented project delivery, limited technology investment and persistent pressure from rising costs and labor shortages — can be solved, at least in part, through artificial intelligence, reported “Construction in the Age of AI, a study from builder Suffolk in partnership with the MIT Center for Real Estate and MIT Media Lab City Science Group.
The study examines how artificial intelligence (AI) is reshaping construction performance and productivity, and where it can deliver the most meaningful gains in processes, scheduling and project feasibility.
Long approval timelines, siloed data and disconnected workflows have made it difficult 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.
“Construction is at an inflection point,” said John Fish, chairman and CEO of Suffolk. “AI presents a real opportunity to transform the way we build. The most meaningful progress will come when the entire ecosystem aligns around better data, smarter workflows and shared accountability. Fully realizing this opportunity will require us to rethink how projects are planned, coordinated and delivered, enabling us to build with greater speed, efficiency and precision. The companies and teams that act now will help define the future of construction.”
Drawing on academic literature, case studies, expert interviews, survey input and an industry roundtable, the project involved over 50 industry leaders in the review and identified six 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 levers could create 17% to 20% total cost savings and 22% to 25% total schedule savings. These improvements have the potential to improve project predictability and feasibility, even in markets where modest changes in cost and timing can determine whether a project moves forward.
“This study is important because it starts to connect academic research with practical industry evidence,” said James Scott, co-lead, MIT Center for Real Estate. “The next step is to keep building the data foundation needed to understand where AI has the strongest impact, where the limits still are and how those findings can be translated into better decision-making across real projects. That kind of evidence base is essential if the industry wants to move from promising examples to durable, repeatable progress.”
The study points to a broader shift in how the construction industry will operate in the years ahead, suggesting that AI will have the greatest impact not as a single tool, but as a connected system of capabilities that improves project planning, delivery and performance across the full lifecycle. As the industry continues to test, measure and scale these approaches, the next phase will depend on collaboration, better data and a willingness to rethink long-standing processes in service of better outcomes.
“When data, systems and field operations are connected, teams can make better decisions faster and remove a lot of the manual friction that slows projects down,” said Jit Kee Chin, executive vice president and chief technology officer at Suffolk. “The opportunity now is to move from isolated AI use cases to integrated workflows that create measurable value across design, procurement, scheduling and execution. That is where AI starts to become operational, not theoretical.”
