Report | AI Engineering: A Strategic Research Framework to Benefit Society

The strategic convergence of artificial intelligence (AI) and engineering, envisioned as AI Engineering, represents a generational opportunity to supercharge engineering for the benefit of society through enhancements to national competitiveness, national security, and overall economic growth. AI Engineering is a nascent field arising from this convergence and synthesis that will advance our nation’s interests by leveraging the traditional strengths of engineering disciplines with breakthrough developments in the field. AI Engineering will be bidirectional and reciprocal: it evokes a future vision in which an engineering approach makes for better AI while AI makes for better-engineered systems. AI Engineering is based on the firm commitment of engineering processes and culture to ethics of safety, health, and public welfare and is a principal term used throughout this report.

The U.S. engineering enterprise is positioned to lead in the research and education necessary for the creation and development of AI Engineering, thereby enhancing U.S. leadership in AI and engineering technologies. Engineering researchers must assist with defining future AI systems through the evolution of existing and new systems, even as they employ existing AI systems to help drive the future of engineering.

Research into the following three overarching areas should generate rapid, sustained innovation in AI Engineering:

• Design: 
  • Design safe, secure, reliable, and trustworthy AI systems.
  • Transform manufacturing quality, efficiency, cost, and time-to-market through AI Engineering.
  • Build and operate AI-engineered systems with cradle-to-grave state awareness.
  • Overcome scaling challenges in engineering.
• AI Engineering for Humans and Society:
  • Construct engineered systems for safe, reliable, and productive human-AI team collaboration.
  • Mitigate rare event consequences via AI.
  • Incorporate ethics in all facets of AI Engineering.
• National Initiatives for AI Engineering
  • Enable collection, curation, and sharing of datasets to advance AI Engineering.
  • Ensure equitable access to computational resources for AI Engineering.
  • Develop engineering domain-specific foundation models.
  • Establish dedicated research institutes for AI Engineering.
  • Create new education and training programs for AI Engineering.

AI Engineering has the potential to impact each of the 14 grand challenges articulated by the National Academy of Engineering. To define AI Engineering, develop key strategies and initiatives, and identify innovative lines of research, a group of researchers, industry leaders, policymakers, and other stakeholders were brought together on Nov. 7- 8, 2023, at a visioning event convened by the Engineering Research Visioning Alliance (ERVA). During the two-day event, 28 participants generated and refined critical grand challenges at the intersection of engineering and AI that face engineering researchers now and in the next decade.