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AI Roadmap for Application in Civil Engineering (RACE)

The AI Roadmap for Application in Civil Engineering (AI RACE) provides a framework for how civil engineers can responsibly adopt artificial intelligence across the infrastructure lifecycle while maintaining accountability, professional judgment, and public trust.

Download the roadmap

Why AI RACE?

Artificial intelligence is already transforming civil engineering. The profession faces a choice: react to change or help shape it.

Developed through collaboration across the ASCE community, AI RACE provides a shared vision for how AI can support civil engineers while strengthening public trust, accountability, and professional practice. The roadmap identifies priority areas, critical enablers, and actions needed to responsibly integrate AI into the future of infrastructure.

Human Accountability Remains Essential

The AI RACE roadmap is founded on a simple principle: artificial intelligence can enhance engineering practice, but responsibility for public safety, professional judgment, and responsible decision-making must remain with people.

Five Human Red Lines guide every recommendation in the roadmap.

Accountability Is Never Delegated

AI does not hold responsible charge and cannot sign, seal, or certify engineering work. Responsibility remains with qualified professionals and organizations.

Engineering Judgment Remains Human

Key decisions involving code interpretation, governing assumptions, loads, failure modes, and risk acceptance remain human responsibilities.

Responsible Decisions Remain Human

Questions involving public welfare, community impacts, equity, and legal accountability cannot be delegated to AI systems.

Humans Keep the Override

People establish the limits of AI systems, maintain oversight, and retain the authority to intervene when necessary.

Verify Before Reliance

AI-generated outputs should not be relied upon without verification appropriate to the consequence of error.

EVENT

ASCE AI Summit 2026

A wide range of subject-matter experts convened at the ASCE AI Roadmap Summit, August 31-September 1, 2026, to share information, workshop ideas, and polish AI RACE as it heads toward release.

ASCE AI Summit 2026
Artificial intelligence relies on a growing network of data centers, power systems, and digital infrastructure that must be planned responsibly and sustainably.

ASCE believes civil engineers, public agencies, industry leaders, and communities should all have a seat at the table as decisions about AI infrastructure are made.

To support this effort, the roadmap proposes new standards, guidance, planning resources, and industry partnerships to help shape how AI infrastructure is designed, built, and operated.
AI Summit 2026
Al is a fundamental shift for civil engineering, and it has already arrived. The civil engineering profession faces a choice to adapt or to lead the Al revolution.

Participants worked through two tracks to define critical enablers, priority areas, and a path to action.

AI RACE was built by subject matter experts. Their goal was to build a roadmap that reflects not just one viewpoint but the entire civil engineering profession.
AI Summit 2026
The road ahead is about turning problems into outcomes. Where are dependencies? What stays human? What evidence shows progress?

Responsible Al is enabled by governance, licensure and public trust, workforce education, and professional practice.

Al has potential to increase efficiency, transforming the way civil engineers work. But that doesn't mean we should shortcut learning or responsibility. Keeping a human in the loop is the key to unlocking the full benefits of Al.
Workforce Development
Al is here, and all civil engineers need training, students included. Accountability doesn't fall on the software, so keeping the civil engineering body of knowledge up-to-date is critical.

Workforce development isn't only about technical skills. Communication, creativity, resilience, and other business skills are all important. A higher calling to society also promotes responsible Al adoption.

Strong workforce standards will enable Al priorities, such as transparency, equity, accessibility, and data sovereignty and ownership.

The Roadmap Structure

The roadmap includes a foundational layer and 11 pillars organized across four major domains, with a short-, medium-, and long-term maturity arc from assistive to autonomous AI.

AI RACE Timeline

Short Term

Adopt & Build Foundations

  • AI literacy
  • Governance
  • Data readiness
  • Pilot programs

Medium Term

Integrate & Augment

  • Validated AI workflows
  • Machine-readable standards
  • Digital twins

Long Term

Transform

  • AI-native practice
  • Autonomous systems
  • Continuous optimization
AI driven design

Want the complete roadmap?

Download the AI Roadmap for Application in Civil Engineering (AI RACE) and explore all 11 pillars, implementation horizons, governance recommendations, and appendices.

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