Advancing Asset Management in Public Works with AI—Agency Case Study

Dive into the evolving world of artificial intelligence (AI) with the speakers as they explore its broad-ranging impacts on asset management within public agencies. This presentation takes a comprehensive look at how AI is redefining how we monitor and maintain our urban infrastructure, from pavements to traffic signs, and its role in creating safer, more efficient public spaces. The speakers will shed light on the practical aspects of applying AI in the public sector, detailing how these techlogies are being integrated into existing systems to streamline operations. The focus isn’t merely on the potential of AI but on the realities of its implementation: the success stories, the obstacles encountered, and the measurable outcomes achieved. A centerpiece of this session will be insights from a public agency at the forefront of AI adoption for infrastructure asset management. The narrative will be a broader view of the changes, challenges, and direct benefits they’ve experienced. This presentation is designed for a diverse audience, from tech aficionados to leaders of public agencies of any size considering AI solutions. It will illuminate the countless ways AI can influence and improve asset management. Participants will gain a clear perspective on AI’s capabilities, equipping them with the insight and confidence needed to navigate the world of AI in public works.
At the conclusion of this session participants will be better able to:
• Identify the breadth of artificial intelligence (AI)’s capabilities in public asset management, including where it excels and areas where it may t yet meet industry standards, emphasizing the need for ongoing development and refinement.
• Discuss the iterative journey of AI adoption, from initial trials to full-scale deployment, stressing the importance of continuous learning, adjustment, and collaboration between AI firms and public agencies.
• Manage their agency’s expectations when integrating AI into infrastructure projects, recognizing the value of gradual improvements and aligning AI performance with industry benchmarks over time.