To empower quality consultants and professionals with the knowledge and tools to integrate artificial intelligence (AI) technologies into quality systems, enhancing efficiency, risk reduction, and innovation in infrastructure project delivery.
Integrating Artificial Intelligence with Quality Systems in Infrastructure Projects
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Cairo
15 June 2025
19 June 2025
Dubai
25 May 2025
29 May 2025
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Details
This course explores the fusion of AI technologies with quality systems in infrastructure projects. Participants will gain a solid understanding of how AI can be applied to quality assurance, predictive analytics, project management, and decision-making, ultimately enabling smart, data-driven infrastructure development.
Target Group
Target Group:
Quality Consultants and Engineers
Project Managers and Engineers in Infrastructure Sectors
Quality Assurance / Quality Control Professionals
Government and Private Sector Infrastructure Authorities
Innovation and Digital Transformation Officers in Construction
Goals
Understand the fundamentals of AI and its impact on quality systems.
Compare AI with traditional quality management approaches.
Apply AI tools for monitoring and evaluating project quality.
Use AI-driven data to make proactive quality-related decisions.
Integrate AI into project management processes and resource planning.
Identify challenges and opportunities in adopting AI for infrastructure quality control.
Target Competencies
Target Competencies:
Quality Management with Emerging Technologies
AI Application in Engineering Projects
Strategic Thinking and Risk Assessment
Data Analysis and Predictive Modeling
Sustainable and Smart Infrastructure Planning
Outlines
Introduction to AI and Quality Systems
Defining AI and its role in modern quality management.
AI vs. traditional methods in quality assurance.
Importance of AI in infrastructure quality control.
Overview of AI technologies relevant to construction and engineering.
Case discussion: The evolving role of AI in project QA/QC.
AI Tools for Monitoring and Analyzing Project Quality
Using Big Data analytics to forecast quality trends.
Applying Machine Learning to detect issues before escalation.
Role of IoT in real-time site quality monitoring.
Integrating AI with quality management systems (QMS).
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