5 formas en que la IA generativa está revolucionando la ingeniería estructural y el diseño

Introduction

The rise of generative AI marks a new era in structural engineering—one where algorithms, data, and human expertise converge to unlock new frontiers of efficiency, creativity, and sustainability. No longer limited to traditional tools and manual iteration, engineers can now harness generative AI to explore vast design possibilities, optimize structures, and make more informed decisions. Here are five ways generative AI is revolutionizing the practice of structural engineering and design.

1. Automated Optimization for Performance and Material Efficiency

Generative AI algorithms can rapidly generate and evaluate thousands of structural configurations, optimizing for criteria such as strength, stability, material usage, and cost. Instead of manually testing different options, engineers set objectives and constraints, letting AI search the design space for solutions that maximize performance and minimize waste.

• Benefits:

  • Reduced material costs and embodied carbon

  • Faster design cycles and fewer manual iterations

  • More efficient, sustainable structures

2. Accelerating the Conceptual Design Phase

Generative AI tools allow engineers to explore a multitude of design alternatives in minutes, rather than weeks. By adjusting parameters—such as span, load, or geometry—AI can instantly visualize a range of viable concepts.

• Impact:

  • Increases creativity and innovation

  • Enables data-driven decision-making early in the project

  • Frees up engineers’ time for critical analysis and client engagement

3. Improving Collaboration and Communication

Generative AI platforms often integrate with BIM and visualization tools, providing clear, data-rich models that can be shared with architects, contractors, and stakeholders.

• Advantages:

  • Enhances interdisciplinary collaboration

  • Streamlines coordination and reduces misunderstandings

  • Facilitates scenario comparison and informed stakeholder input

4. Enabling Design for Resilience and Sustainability

AI-driven analysis can evaluate structural performance under a range of scenarios, including wind, seismic, and climate change impacts. Generative AI helps create designs that are not only efficient, but resilient and future-proof.

• Features:

  • Simulate performance under extreme conditions

  • Integrate lifecycle and sustainability metrics

  • Optimize for energy use, carbon footprint, and adaptability

5. Transforming the Role of the Engineer

Rather than replacing engineers, generative AI augments their capabilities, allowing them to focus on higher-value tasks such as validation, creative problem-solving, and strategic planning.

• Shift:

  • From repetitive calculations to design curation and optimization

  • Increased emphasis on interpreting results, ethics, and client value

  • Ongoing learning and adaptation as technology evolves

Conclusion

Generative AI is reshaping structural engineering—driving efficiency, expanding creative horizons, and enabling data-informed decision-making. By embracing these technologies, structural engineers can deliver more optimized, sustainable, and resilient designs—meeting the demands of a rapidly changing built environment.

References

• American Society of Civil Engineers (ASCE), 2024. AI in Structural Engineering: Trends and Opportunities

• Structural Engineers Association, 2024. The Future of Engineering Practice

• Autodesk, 2024. Generative Design for Structural Engineering