28 January 2025 Seminars

• Exploring the construction landscape: Contrasting scenarios with and without AI integration
• Implications of AI absence: Potential pitfalls and missed opportunities in modern construction
• Case studies: Real-world examples of successful AI implementation in construction projects
• Future outlook: Envisioning the AI-driven construction site of tomorrow

• Assessing the current data landscape and aligning it with the organizational vision
• Building a robust data platform: From data lakes to warehouses
• Establishing trusted operational reporting and ensuring data quality
• Implementing predictive analytics and creating an experimentation platform
• Integrating AI solutions into existing systems and processes

• Strategies for identifying and breaking down data silos in construction organizations
• Harmonizing data from multiple sources (e.g., BIM, ERP, project management tools) for improved collaboration and decision-making
• Best practices for implementing data standardization and normalization to ensure consistent and accurate analysis
• Balancing data integration with maintaining security and integrity
• Streamlining communication with stakeholders through unified data platforms and AI-driven insights
• Case study on how AI-driven compliance reports empowered teams to save time and improve operational efficiency in construction projects

• Prioritize and Organize Data: Focus on identifying the most critical project data, examine it in bulk, and address any data integrity issues.Develop an Analytics Strategy: Create a clear strategy for analyzing data at both the project and operational levels, including the purpose (why) and methods (how) of analysis.
• Implement Data Controls: Establish robust controls to ensure future data collected is accurate, relevant, and of the highest quality.
• Enhance Analytics Visibility: Present analytics in a meaningful way across all organizational levels, making it a central point of discussions and decision-making.
• Leverage AI and Stay Persistent: Use AI to automate, deepen, and streamline analytics processes, while adopting a long-term approach to continuous improvement

• What is the reality vs the hype of AI?
• What is available vs what is possible
• How to build an AI strategy for long term success
• AI rollout for construction companies

The construction industry is traditionally slow to adopt new technologies. However, they now face the urgent need to embrace AI and data-driven decision-making.
This panel brings together key stakeholders from across the value chain to address the challenges of implementing AI in a fragmented and often paper-based industry. Industry
leaders will explore how a comprehensive data ecosystem can serve as the foundation for AI adoption, driving productivity, reducing costs, and enhancing project outcomes.

• Current state of AI and data utilization in construction: Successes, challenges, and opportunities
• Strategies for overcoming industry fragmentation and fostering data collaboration across project stakeholders
• Developing a unified data ecosystem: Integrating diverse sources from design to project management
• Leveraging AI for predictive analytics in risk management, resource allocation, and scheduling
• Addressing data privacy, security, and ownership concerns in collaborative environments
• Workforce development: Cultivating data literacy and AI skills across construction organizations
• Future outlook: How AI and data-driven decision-making will reshape construction in the next 5-10 years