How AI Agents are Changing Construction

By

Julia Tell

and Ian Siegel

Last Updated Jan 22, 2026

By

Julia Tell

and Ian Siegel

As the adoption of AI increases, construction leaders need to understand how AI agents for construction can be used to efficiently build today’s complex projects.

This article will explore how AI agents are changing the construction industry by automating and optimizing various processes, including the most common types of AI agents used, their key features, and practical applications.

What is an AI agent?

AI agents are intelligent software systems designed to autonomously process information, make decisions and perform actions to achieve specific objectives.

These systems are also able to leverage advanced learning and reasoning capabilities.

In construction, AI agents increase efficiency and safety by automating tasks such as project management, safety monitoring, cost estimation, quality control and supply chain coordination.

AI agents for construction processes are increasingly assisting teams in managing workflows, monitoring budgets and performing routine tasks, allowing AEC professionals to focus on issues that require expert judgment.

What Sets AI Agents Apart

Agentic AI adds a third tier to the two-tier model of AI that has already revolutionized commerce and daily life.

1. Tier One: Large Language Model Chatbots

   In the popular imagination, AI involves LLM-based systems such as ChatGPT or Gemini. Typically, they are intelligent chatbots trained to scrape a globe’s worth of information from the internet and use it to answer queries. It’s helpful, perhaps, for suggesting a new car that fits the user’s criteria — but risky for use in the fast-paced, tightly constrained world of construction.

2. Tier Two: AI Assistants

   Standard LLMs are also behind AI assistants. This level of AI answers questions in more pointed fashion by relying only on data collected in a company’s closed-loop system. In construction, assistive AI can retrieve needed information without delay, instantly revealing actionable metrics such as the number of open RFIs or the overdue tasks assigned to a specific contractor.  

3. Tier Three: AI Agents

   AI agents go the last mile. They are focused tools built to execute a specific task with reasoning and the authority to act. Like a simple bot that assigns information to its proper cubbyhole, AI agents can execute specific tasks but also apply the higher-order thinking and reasoning deployed by LLMs.

Within parameters set by the user, AI agents can think through the contingencies of a situation and produce a reasoned response. For construction, AI agents offer the prescriptive power to build out solutions customized to the needs of a stakeholder, entity, or jobsite.

Agentic AI can combine reasoning plus its power of data capture to support and streamline the jobsite superintendent’s daily log duties. Pulling from the superintendent’s stream of data entries, including photos, agentic AI assures a complete report by asking about important entries -- who visited the site, which tasks are complete, whether certain contractors are on schedule.

Near day’s end, agentic AI could notice that superintendents haven’t submitted their daily observations and issue a nudge, asking if it can automatically send them or present them for review.

Ian Siegel

Strategic Solutions Engineer

Procore Technologies

Types of AI Agents in Construction

While AI agents can execute tasks to achieve a specified outcome or goal, they can also use information from various software platforms within the construction tech stack, potentially bridging the gaps between ERP and project management or other related systems.

Construction AI agents offer diverse functionalities, each tailored to specific aspects of the industry, streamlining workflows and operating within user-defined parameters.

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  Project Management Agents

  These agents assist with planning, scheduling, and resource allocation, helping projects stay on track and within budget.

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  Documentation and Permitting Agents

  Used to automate the management and organization of construction documents and permits, these agents maintain accurate and up-to-date records throughout the project lifecycle.

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  Safety Monitoring Agents

  Utilizing sensors and data analysis, these agents identify potential hazards, improving on-site safety and reducing accidents.

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  Bidding and Estimation Agents

  They automate cost estimation and bid preparation, streamlining the bidding process and improving accuracy.

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  Quality Control and Compliance Agents

  By analyzing construction plans and on-site data, these agents confirm that quality standards and regulatory requirements are met throughout the project.

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  Supply Chain Agents

  These agents coordinate logistics and manage inventory, optimizing the supply chain to prevent delays and reduce costs.

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  Budget Oversight Agents

  By monitoring expenditures and financial data, these agents help projects adhere to budget constraints, providing alerts and insights to prevent overspending.

Key Features of AI Agents in Construction

AI in construction is capable of using multiple types of information, including visual, verbal, quantitative and contextual, to provide data for different AI agents. These agents offer a wide range of features that can be combined to enhance and optimize processes. Here are some of the key features.

• Predictive Analysis

  AI agents utilize historical data and machine learning to anticipate future project challenges and resource requirements, enabling proactive risk management and improving time and budget efficiency.

• Data Collection

  AI agents can gather and process large volumes of data from various sources, providing insights that inform decision-making and project optimization.

• Computer Vision

  Agents can use computer vision to analyze real-time images and videos from construction sites, identifying issues such as safety hazards or quality defects.

• Automation of Tasks and Reports

  By automating routine tasks and generating reports, AI construction agents free up human resources for more strategic activities, enhancing productivity and accuracy.

• Natural Language Processing (NLP)

  AI agents equipped with NLP can interpret and respond to human language, facilitating communication and documentation through voice commands and text analysis.

• Workflow Optimization

  AI agents streamline processes and eliminate bottlenecks, ensuring smooth project execution and coordination among teams.

• Decision Support

  AI can offer data-driven insights and recommendations to assist project managers in making informed decisions.

• Learning and Adaptation

  AI agents continuously learn from new data and experiences, adapting to changing conditions and improving their performance over time.

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Practical Roles to Implement AI Agents in Construction Workflows

There are numerous use cases for AI agents to enhance the efficiency of core construction activities, with more applications being developed all the time. AI agent support monitoring, flagging and coordination across teams and tools. Here are some practical applications:

Document Management

AI agents can automatically classify, tag and route project documents. For example, incoming RFIs (Requests for Information) can be assigned to the appropriate project manager based on topic, trade, or schedule phase, preventing inbox backlogs and misplaced forms.

Design Analysis and Optimization

Utilizing Building Information Modeling (BIM), AI agents can evaluate design plans to identify potential improvements and efficiencies. They perform clash detection and simulate various scenarios to optimize layouts, materials, and structural elements, ensuring cost-effective and sustainable construction solutions.

Cost and Budget Oversight

Integrated with project financials, AI agents can detect anomalies in subcontractor invoices, automate initial approvals within set thresholds, and cross-reference purchase orders with actual deliveries, ensuring financial accuracy and efficiency.

Schedule Coordination

AI construction agents can analyze calendar data, crew schedules, and equipment availability to suggest adjustments. If an inspection is delayed, the agent can flag conflicts and recommend the next best slot based on project dependencies, ensuring seamless scheduling.

Compliance Monitoring

These agents track safety documentation, lien waivers, and insurance renewals. They send out alerts or pause tasks when something is about to expire or go out of compliance, maintaining adherence to regulations and safety standards.

Supply Chain and Procurement Optimization

AI agents can optimize procurement by predicting material needs, automating order placements and tracking deliveries. They can order supplies just in time, reducing inventory costs and even preventing project delays.

Equipment Maintenance

AI agents monitor equipment health through sensors and predictive analytics, scheduling maintenance before failures occur. This proactive approach minimizes downtime and extends the lifespan of machinery.

Internal Task Management

AI agents can assign and track internal tasks, ensuring that team members are aware of their responsibilities and deadlines. They can prioritize tasks based on project urgency and dependencies, facilitating better workflow management and productivity.

The Next Steps: Model Context Protocols

Already, AI agents are evolving into model context protocols (MCPs) that share contextual understanding across enterprise systems.

It’s an industry shift from the API-driven systems sharing information from, for example, construction management software to enterprise resource planning software.

MCPs wrap information from multiple systems in context, enabling enterprise-wide AI agents to analyze business operations holistically. For instance, a slowdown in accounts payable doesn’t just materialize as a standalone problem for accounting to fix but a challenge that is slowing scheduling and subcontractor payments.

How AI Agents are Shaping the Construction Industry

AI technologies are revolutionizing traditional building and project management on a large scale. They're changing the game across the industry by managing complex data, facilitating better decision-making, enhancing safety, and streamlining operations wherever possible.

As AI continues to penetrate the construction industry, new applications for agents are emerging: Neural Networks, using machine learning and data analytics, will deliver customizable solutions and intuitive problem-solving, enabling faster work.

AI agents will better integrate offices with worksites, enhancing oversight and automation. Leaders who invest in AI and stay ahead of advancements will be able to secure projects and boost profits in the increasingly complex construction industry.

Written by

Julia Tell

Contributing Writer | Procore Technologies

71 articles

Julia Tell is a freelance writer covering education, construction, healthcare, and digital transformation. She holds a Ph.D. in Media & Communications and has written for publications including Business Insider, GoodRx, and EdSurge, as well as nonprofits, international businesses, and educational institutions.

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Ian Siegel

Strategic Solutions Engineer | Procore Technologies

Ian Siegel focuses on helping owners and builders of large, complex infrastructure and capital asset portfolios leverage digital tools and workflows to address the unique needs of their construction projects. He prides himself on delivering solutions that ensure the projects he supports are delivered on time, on budget, and built using the highest quality standards. During his career, Ian has occupied a variety of critical roles over the course of his career with each adding to his formidable skill set, aiding in his ascent to becoming a leading voice in the construction industry.

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