How AI in Structural Engineering Is Redefining the Future of AEC

Key Concepts:

• AI transformation in structural engineering
• NCSEA Foundation's AI strategic plan
• Misconceptions about AI (fad, just chatbots)
• Implementing AI effectively in firms (leadership, strategy)
• Build vs. buy AI solutions
• Practical ways for small/mid-size firms to start with AI
• Evaluating new AI tools
• Essential industry data for AI impact
• Standardizing/sharing data
• Evolving role of human judgment/creativity
• Changing expectations for AEC professionals at different levels
• Skills for AEC professionals in an AI-driven future

1. The Unchanging Core of Structural Engineering:

• Structural engineers will continue to design structures to resist various forces (gravity, wind, earthquakes, etc.) and ensure safety and resilience.
• "Structural engineers as a profession, we design structures to resist gravity forces, vertical and horizontal forces...and really put a focus and emphasis on making sure that we provide designs that are safe." - John Michael
• This fundamental responsibility will not change in the next 5-10 years.

2. Shifting Project Delivery Methods:

• The way projects are delivered will undergo significant transformation due to AI.
• This shift is outlined in the NCSEA Foundation's AI strategic plan, which includes stages of learning, strategy development, application development, and evaluation.
• The industry faces pressure to shorten construction timelines and handle increasingly complex design work.
• AI can help manage the growing library of past projects and existing built environment challenges.

3. Redefining Value and Contribution:

• Engineers should focus on their core value of providing safe and resilient designs.
• AI should be used to automate workflows and handle data, allowing engineers to focus on design work, review, human collaboration, and client interaction.
• Analogy to radiology: AI enhances the field, allowing professionals to focus on patient care rather than managing diagnostic data.
• AI will enable engineers to "practice at the top of our license."

4. Addressing Misconceptions about AI:

• AI is not a fad but a transformative wave of digital technology.
• AI is much more than just large language models (LLMs) and chatbots.
• AI encompasses tasks requiring human intelligence, such as computer vision, speech recognition, and real-time translation.
• AI can be a computer's ability to "speak English," breaking down communication barriers.

5. Implementing AI Effectively: Leadership and Strategy:

• Leadership advocacy and encouragement are crucial for AI adoption within firms.
• A well-defined AI policy is essential to address security concerns and data restrictions.
• User groups and internal support systems can help employees learn and share AI applications.
• Firms should align their AI strategy with their core technology strategy and 5-year strategic plans.
• Focus on how AI can affect downstream partners and improve the overall quality of services, not just internal efficiency.

6. Build vs. Buy: Navigating AI Solutions:

• Even small firms may need some development function to connect their data to AI tools.
• While many software solutions promise easy integration, customization is often required.
• Consider consulting services that use AI to add value, such as Generate for mass timber consulting.
• Encourage coding as part of the standard workflow and provide training for employees.
• Developing true AI solutions in-house can be expensive, especially with the challenge of obtaining clean, reliable data.

7. Practical Steps for Small and Mid-Size Firms:

• Start by defining an AI policy to securely provide employees with access to AI chatbots like ChatGPT.
• Enable employees to use AI tools for work-related tasks, not just personal projects.
• Focus on concrete ideas that can impact internal workflows, rather than vague concepts.
• Develop prototypes (POCs) using AI tools to assess their value before investing in full-scale development.
• Attend demo days to find startups and tools that can solve specific problems.

8. Evaluating New AI Tools and Startups:

• Talk to the technical founder or consultant for a live demo, rather than relying on sales representatives.
• Identify a specific problem that the tool can solve end-to-end.
• Assess the future capabilities of the product and its roadmap, considering dependencies on LLMs or hardware.

9. The Importance of Data in AI:

• Machine learning relies on vast amounts of data for training.
• Data sharing is a significant challenge due to concerns about intellectual property and vertical silos in the delivery chain.
• Architects, general contractors, and owners possess large amounts of data but may not be leveraging it effectively.
• The industry needs digital-first codes and standards that are easily readable by computers.

10. Evolving Roles and Expectations:

• Entry-level staff should focus on learning through AI tools, rather than just completing tasks blindly.
• Coding skills are becoming increasingly important for entry-level engineers.
• Project managers should drive AI adoption and innovation within their teams.
• Adaptability is crucial for project managers, who should be open to new tools and processes.

11. Essential Skills for AEC Professionals:

• The ability to utilize AI tools effectively for learning and coding.
• Focus on continuous learning and staying updated with the latest advancements.
• Adaptability and an open mindset.
• Strong communication skills to convey the value of engineering services to stakeholders.

12. Final Advice: Be Human:

• Focus on the core value of solving human problems and improving communities.
• Ask the right questions about what's important and what's holding the industry back.
• Use AI to break down barriers and deliver projects in the best possible way.
• Structural engineers who use AI will likely replace those who don't.
• "If you want to stay ahead in the age of AI...the most important thing to do is to be human." - John Michael

13. NCSEA Summit:

• NCSEA Annual Summit: October 14-17 in New York City.
• Pre-conference workshop on AI with tracks for consumers and developers.
• Keynote speakers on how small teams can have an outsized impact using AI.
• Interactive Q&A sessions with the AI grant team.

Synthesis/Conclusion:

AI is poised to transform structural engineering, not by replacing engineers, but by augmenting their capabilities and shifting their focus towards higher-value tasks. The key lies in strategic implementation, continuous learning, and a focus on the human aspects of the profession. By embracing AI and adapting to its evolving landscape, AEC professionals can enhance their value, improve project delivery, and contribute to a safer, more resilient built environment. The NCSEA Foundation's resources and upcoming summit provide valuable guidance and opportunities for professionals to navigate this transformation effectively.