Artificial intelligence is rapidly reshaping the construction industry, and George Brown Institute of Technology is working to prepare students in construction and related programs for the transition.
Toronto educational institutions have expanded both AI-focused education and AI-enabled training tools across construction, manufacturing and clean technology services as employers increasingly seek workers who can perform in digital and data-driven environments.
Employers increasingly expect their workers to understand technologies such as Microsoft Copilot, ChatGPT, robotics, automation, and applied AI. At the same time, builders are adopting BIM, digital twins, predictive analytics, automation systems, and smart building technologies.
Through construction management programs, continuing education courses, a professional AI graduate certificate, and an innovative solar energy training curriculum, George Brown University students are exposed to technology that plays an increasingly important role in the field and in the office.
Although the Angelo Del Zotto School of Construction Management does not offer a dedicated degree in AI, students are increasingly encountering technologies that rely on AI, machine learning, predictive analytics, and digital twin concepts.
Nolan Quinn, Minister of Universities, Research Excellence and Security, recently said the school’s Construction Management Master’s program “will ensure Ontario students gain the practical skills needed to lead large-scale construction projects in communities across Ontario, ensuring our province can continue to move forward and grow no matter what we face.”
The school offers a number of programs including the Bachelor of Honors (Construction Management), Postgraduate Construction Management Programme, Residential Construction Management Programme, and Postgraduate Building Information Modeling (BIM) Management Programme.
School officials said the program was developed in collaboration with industry partners and reflects current techniques being adopted across the construction industry. This technology includes BIM platforms and digital project management systems, which increasingly incorporate AI-driven capabilities for scheduling, cost forecasting, risk assessment, and project optimization.
As contractors and developers adopt smarter software tools, they say students entering the industry need to understand how data can be used to improve decision-making and project outcomes.
For students who want a deeper exposure to AI, George Brown has created several pathways through its continuing education department and specialized graduate studies.
One of the university’s options is the Graduate Certificate in Applied AI Solution Development, which combines AI, machine learning, deep learning, data analytics, mathematics, computer science, and business analytics. Students will learn how to build machine learning and deep learning models, interpret data, and communicate results through dashboards and visualization tools.
Although this program is not specific to construction, the skills are transferable across the architectural field. For example, machine learning can be used to predict project schedules, analyze productivity, improve job site safety, optimize building performance, and support digital twin applications.
George Brown also launched a smart manufacturing program for construction professionals who want to understand the technology driving the industry. This program teaches students how to program and operate robotics, automation systems, and additive manufacturing technologies while learning how AI interacts with the Industrial Internet of Things (IIoT).
Students configure smart sensors, build IIoT networks, and work with digital twins that simulate real-world production systems. You will also learn how to use AI tools to analyze operational data, apply cybersecurity principles, and explore sustainability strategies that reduce energy consumption, material use, and waste generation. The curriculum consists of courses on smart, data-driven manufacturing, IIoT, and advanced manufacturing practices.
Independent courses in Machine Learning and Large-Scale Language Models are also offered by the university.
The 6-week Machine Learning 1 course introduces students to the fundamentals of AI and machine learning. Learn the basics of Python programming and data structures before moving on to core machine learning algorithms such as linear regression, logistic regression, and clustering. Students will learn how machine learning techniques can be applied to real-world problems.
The AI and Language Models in Business Development course focuses on conversational AI and large-scale language models such as ChatGPT. Students will learn how AI-powered language models are built, how they integrate with business platforms, and how organizations can use them to automate workflows, improve customer engagement, and improve operational efficiency. The course uses labs, demonstrations, and case studies, and successful students earn micro-certifications.
The Solar Energy Technician and Solar Panel Installer program uses adaptive learning technology, simulation software, and AI-enabled tools to personalize instruction and accelerate skill development.
Algorithms assess students’ strengths and weaknesses, allowing the learning platform to tailor content to individual needs. Rather than relying solely on physical equipment, students can work in simulated environments that replicate the operation of solar panels, inverters, battery energy storage systems, microgrids, and electrical circuits.
Learners can use software such as 3DLab and CircuitLogix to troubleshoot electrical systems, model solar installations, test different configurations, and analyze system performance under different conditions. They can investigate how weather affects solar power generation, design grid-connected and off-grid systems, and practice solving complex technical problems.
The AI-powered Solar Energy Technician program covers solar power systems, battery storage, commercial solar installations, photovoltaic facilities, microgrids, and system sizing, maintenance, troubleshooting, and safety procedures. Graduates are prepared for careers in areas such as residential and commercial solar power projects, solar installations, and solar power system design.
