Artificial intelligence is moving quickly from experimentation to practical use across the construction industry. Contractors are exploring AI for estimating, preconstruction, administrative work, scheduling, document management, risk analysis, and other processes that traditionally require significant manual effort.
However, adoption is not happening evenly. Recent industry research shows a construction sector that is increasingly interested in AI but still working through questions around skills, data, integration, cost, and return on investment.
The latest construction AI statistics provide a clearer picture of where the industry stands in 2026—and where it may be heading next.
Construction AI Adoption Is Growing, but the Industry Is Still Early
Construction companies are investing more attention and resources in artificial intelligence, but widespread implementation is still relatively limited.
A global RICS study of more than 2,200 construction professionals found that 45% reported no AI implementation at all, while another 34% said their organizations were still in early pilot phases. Just under 12% reported regularly using AI within specific processes, while organization-wide implementation remained below 1%.
These numbers show an important distinction between interest in AI and actual operational adoption.
Many construction businesses are testing tools without fully integrating them into everyday workflows. That creates a significant opportunity for companies that can move beyond isolated experimentation and identify practical applications that generate measurable value.
More recent industry indicators also point toward accelerating adoption. According to the 2026 Construction Hiring and Business Outlook from the Associated General Contractors of America (AGC) and Sage, 61% of respondents said their firms were using artificial intelligence or planned to increase investment in it, up from 44% the previous year. AI was most commonly being applied to office and administrative functions, estimating, and preconstruction.
The direction is clear: AI is moving closer to everyday construction operations.
AI Investment Is Increasing Across Construction
Growing adoption is being accompanied by greater investment.
RICS found that 31% of construction organizations planned a moderate or significant increase in AI investment over the following 12 months. At the same time, 28% reported no plans to invest and 22% were still uncertain about their organization’s investment strategy.
This divide reflects the current state of the industry. Some organizations are actively moving from pilots into implementation, while others are still determining where AI fits within their operations.
The change becomes even clearer when looking at U.S. contractors. AGC and Sage reported that AI was the technology category expected to see the largest increase in investment in their 2025 outlook, with 44% of firms anticipating increased AI investment. By the 2026 outlook, the share of firms either using AI or planning greater investment had risen to 61%.
Rather than treating AI as a distant technology trend, more contractors are beginning to include it in their technology and operational planning.
Where Construction Professionals Expect AI to Create Value
Not every construction process offers the same opportunity for artificial intelligence.
The RICS research asked professionals where they believed AI could have a highly positive impact on construction projects. Progress monitoring and project scheduling ranked highest, both at 36%, followed by resource optimization and reviewing contracts and project documents at 30%. Risk management followed at 29%.
These areas share an important characteristic: they involve processing, organizing, and interpreting large amounts of information.
AI can help teams identify patterns, summarize documents, organize project data, and reduce the manual effort involved in administrative processes.
This aligns with how contractors are already beginning to use the technology. Rather than replacing construction professionals, many of today’s most practical AI applications support the people responsible for keeping projects organized.
From meeting summaries and documentation to estimating support and customer communication, there are already numerous practical AI use cases for construction companies that can reduce repetitive work while keeping human oversight at the center of operations.
Construction Companies Are Still Struggling With AI Readiness
Interest does not automatically translate into readiness.
According to RICS, nearly three-quarters of organizations surveyed had not progressed beyond early discussions or had no meaningful capability or planning activity related to AI. Specifically, 45% reported limited capability and were only exploring implementation, while another 29% had no AI capability or plans in place.
Only around 20% reported engaging in strategic AI planning and proof-of-concept testing.
This suggests that one of the biggest challenges facing construction companies isn’t necessarily access to AI technology. It’s building the operational foundation required to use that technology effectively.
AI tools still need clearly defined processes, reliable information, responsible users, and employees who understand how technology fits within their responsibilities.
For growing contractors, adopting new software without addressing those fundamentals can simply add another layer of complexity to already fragmented operations.
Skills Are the Biggest Barrier to AI Adoption
Technology itself is only one part of AI implementation.
RICS found that 46% of respondents identified a lack of skilled personnel as a primary barrier to adopting AI, making it the most commonly cited obstacle. System integration challenges were another major concern, while poor data quality, implementation costs, and unclear return on investment also limited adoption.
The skills issue is particularly important because AI adoption requires more than technical expertise.
Employees need to understand when AI should be used, how its outputs should be reviewed, what information can safely be provided to different systems, and where human judgment must remain part of the process.
That makes role clarity increasingly important. AI can automate portions of a workflow, but companies still need people who understand who owns the outcome.
Without that accountability, automation can create confusion rather than efficiency.
Early AI Adopters Are Beginning to Report Measurable Returns
Although adoption remains uneven, companies already using AI are beginning to report tangible benefits.
Bluebeam’s 2026 AEC Technology Outlook, based on a survey of more than 1,000 architecture, engineering, and construction professionals, found that only 27% of AEC firms were currently using AI for automation, problem-solving, or decision-making.
Among those adopters, however, the results were significant: 68% reported saving at least $50,000, while 46% said they had saved between 500 and 1,000 hours through AI tools. Additionally, 94% of companies already using AI planned to expand their use or investment during the following year.
These findings help explain why construction AI investment continues to grow even while overall adoption remains relatively low.
Companies do not necessarily need to automate their entire operation to see value. Targeting repetitive, information-heavy processes can create meaningful efficiencies without requiring a complete technological transformation.
Construction Leaders Remain Optimistic About AI
Despite implementation challenges, construction professionals remain largely optimistic about AI’s long-term role.
Autodesk reported in 2026 that 78% of construction leaders believe AI will enhance the industry, while 66% expect it to become essential across the board within two to three years.
At the same time, expectations are becoming more realistic.
Autodesk’s construction research found that only 32% of construction leaders said they had met or were close to meeting their AI goals. That gap between optimism and results suggests companies are beginning to recognize that simply adopting AI tools is not enough.
Successful implementation depends on how those tools fit into existing workflows, teams, and operational structures.
AI may accelerate individual tasks, but it does not automatically coordinate an organization. As we’ve explored in AI Can Automate Tasks — But Not Operations, technology works best when it supports clearly structured processes and people rather than attempting to replace them.
AI Is Also Changing Construction Workforce Expectations
Artificial intelligence is not only changing technology strategies. It is beginning to influence the skills construction companies expect from their workforce.
RICS found that 69% of project managers and 67% of quantity surveying and construction professionals believed AI would help surveyors deliver greater value in the future. At the same time, 44% of project managers expressed concern about AI’s impact on their own role, while 48% said they felt overwhelmed by the speed of technological change in the profession.
This combination of optimism and uncertainty is important.
AI is unlikely to eliminate the need for construction professionals, but it can change how their time is spent. Administrative work that previously required hours may increasingly be supported by automated systems, allowing employees to focus more heavily on coordination, judgment, relationships, and problem-solving.
The construction workforce of the future may therefore be defined less by whether people use AI and more by how effectively they work alongside it.
What Construction AI Statistics Tell Us About 202
Taken together, the latest data reveals an industry at an important transition point.
AI adoption is still far from universal. Many contractors remain in experimentation stages, organizational readiness is limited, and significant barriers around skills and integration remain.
At the same time, investment is increasing, early adopters are reporting measurable efficiencies, and a growing percentage of construction leaders expect AI to become essential to their businesses.
For contractors, the opportunity is not necessarily to adopt every new AI tool available.
The more practical strategy is to identify where repetitive work, fragmented information, or administrative bottlenecks are consuming valuable employee time—and determine whether AI can improve those specific processes.
That approach also requires strong operational foundations. Technology performs best when responsibilities are clear, workflows are documented, and the right people remain accountable for outcomes.
As construction companies continue navigating labor shortages and increasingly complex operations, the combination of technology and well-structured teams may become an increasingly important competitive advantage.
OfficeTwo helps construction companies build dedicated administrative and operational support teams that integrate with existing operations, helping contractors create the structure they need to scale efficiently as technology and industry demands continue to evolve.
FAQ
How many construction companies are using AI?
AI adoption varies depending on the study and how implementation is defined. RICS reported that 45% of construction organizations surveyed had no AI implementation, while 34% were in early pilot stages. A separate Bluebeam study found that 27% of AEC firms were using AI for automation, problem-solving, or decision-making.
What is AI most commonly used for in construction?
Current applications include office and administrative work, estimating, preconstruction, project documentation, scheduling, progress monitoring, risk management, and information analysis. AGC and Sage reported that office and administrative functions, estimating, and preconstruction were among the most common AI use cases among contractors.
Is AI investment increasing in construction?
Yes. AGC and Sage reported that 61% of surveyed construction firms were using AI or planning to increase their investment in 2026, compared with 44% reporting anticipated increased AI investment in the previous year’s outlook.
What is preventing construction companies from adopting AI?
Major barriers include a lack of skilled personnel, integration challenges, poor data quality, implementation costs, and uncertainty around return on investment. RICS identified the skills shortage as the most frequently cited barrier, reported by 46% of respondents.
