Artificial intelligence is expected to play a much larger role in the construction industry over the coming years, but experts say its greatest value will come from improving how work gets done rather than replacing construction professionals.
A new report from global consulting firm McKinsey & Company explores how artificial intelligence could reshape architecture, engineering, and construction (AEC) workflows by helping firms automate routine tasks, improve decision-making, and increase productivity across project lifecycles.
The report suggests that companies that successfully integrate AI into their operations will gain a competitive advantage by redesigning workflows and making better use of their proprietary data.
AI Is Changing Construction, Not Replacing It
Despite growing concerns surrounding automation, McKinsey’s research indicates that AI is unlikely to replace construction jobs outright.
Instead, the technology is expected to automate specific tasks that currently require significant time and administrative effort.
According to the report, approximately 39% of non-physical work performed in the construction industry has the potential to be automated in some capacity. In architecture and engineering, that figure rises to 50%.
Many of these tasks involve repetitive or data-intensive activities that can benefit from automation while allowing construction professionals to focus on higher-value work.
Construction Firms Should Focus on Workflows
McKinsey recommends that construction companies move beyond using AI solely as a productivity tool and instead focus on transforming entire workflows.
Rather than automating individual tasks in isolation, firms can achieve greater benefits by redesigning complete processes from start to finish.
Examples include:
- Bid and proposal preparation
- Cost estimating
- Project feasibility analysis
- Request for Information (RFI) management
- Document processing
- Equipment inspections
- Project closeout documentation
Improving how these activities connect throughout a project can reduce inefficiencies and improve collaboration among project teams.
Three Phases of AI Adoption in Construction
The report outlines a three-stage roadmap for AI adoption across the construction industry.
Near-Term Adoption (Next 18 Months)
Construction firms are expected to focus on streamlining administrative and project management workflows. Early opportunities include:
- Bid and no-bid decision-making
- Estimating and proposal drafting
- Workflow automation
- Productivity improvements for project teams
These applications are already becoming more common across the industry.
Medium-Term Adoption (18 Months to Four Years)
During this phase, companies can begin leveraging proprietary project data to gain a competitive advantage.
Potential applications include:
- Analyzing RFIs and specifications
- Managing project documentation
- Improving reporting and forecasting
- Extracting insights from historical project data
Firms that maintain high-quality internal data are likely to benefit the most from these capabilities.
Long-Term Adoption (Beyond Four Years)
Future applications are expected to expand into construction operations and jobsite technologies.
Examples include:
- Autonomous construction equipment
- Intelligent transportation and logistics systems
- Advanced project coordination tools
- AI-driven scheduling and resource management
While these technologies may take longer to become mainstream, they have the potential to significantly improve project delivery and operational efficiency.
Build or Buy? Construction Firms Must Make Strategic Decisions
One of the biggest questions facing contractors today is whether they should develop their own AI tools or purchase solutions from technology providers.
McKinsey advises firms to carefully evaluate where their competitive advantages lie before making significant investments.
Construction companies should consider building proprietary solutions when:
- Their expertise creates unique value.
- They possess valuable project data.
- Their workflows cannot easily be replicated by competitors.
Conversely, purchasing third-party software may make more sense when technology providers are investing heavily in specialized solutions that would be difficult or costly to develop internally.
For many organizations, partnerships with technology providers may offer the most practical path forward.
Productivity Remains a Major Industry Challenge
The construction industry has historically lagged behind other sectors in productivity growth.
Previous McKinsey research found that global construction productivity improved by only about 10% between 2000 and 2022, highlighting the need for more efficient project delivery methods.
AI presents an opportunity to address some of these longstanding challenges by reducing administrative burdens, improving information management, and helping teams make faster, more informed decisions.
Preparing for AI Adoption
McKinsey recommends that construction firms begin preparing for AI integration by taking a strategic approach rather than adopting technology simply because it is available.
The report suggests that companies should:
- Identify three to five high-value workflows that could benefit from automation.
- Determine whether to build, buy, or partner for AI solutions.
- Establish governance and implementation strategies.
- Measure productivity and operational improvements over time.
The Future of AI in Construction
Artificial intelligence is unlikely to replace construction professionals anytime soon. Instead, its greatest impact will come from helping companies work more efficiently and make better use of their knowledge and data.
As AI technologies continue to evolve, construction firms that invest in workflow improvements and strategic adoption are expected to be better positioned to improve productivity, reduce project friction, and remain competitive in an increasingly digital industry.
