How can I use AI for structural engineering?
1. Introduction
In 2025, the structural engineering sector is on the cusp of a transformation as Artificial Intelligence (AI) progresses from an emerging concept to a day-to-day reality. No longer confined to the realm of theory, AI is already being harnessed by industry leaders—firms like Arcadis, ARUP, and WSP—to streamline processes and unlock new levels of efficiency.
AI is fast becoming a cornerstone of modern engineering practice and a leverage which early AI adopting consultants are using to position themselves for an edge over consultants not investing in learning about or utilising the technology.
At its core, AI matters in structural engineering because it unlocks efficiency gains (e.g. more optioneering) and risk reduction (e.g highlighting issues we might have overlooked). By analyzing information faster than we can, AI can ‘Augment’ engineers with information for better decision-making—an invaluable advantage amid rising project complexities and ever-tightening timelines with fewer skilled staff available in the industry. With the support of AI used in the right places, engineering teams can innovate more confidently, reduce costly errors, and ultimately create safer, more resilient structures.
Here at Civils.ai, our mission is to make these AI-driven benefits accessible to every construction team, regardless of technical background. Through no-code automation solutions, we aim to eliminate uncertainty and reduce risks on any project. By bridging cutting-edge AI without the need for the steep learning curve faced with programming languages, we’re empowering structural engineers to automate manual processes using visual programming and natural language, paving the way for a future where AI is an essential and straightforward to understand part of every engineering toolkit.
2. Understanding AI in Structural Engineering
Very quick AI basics
Artificial Intelligence in structural engineering can be viewed as a set of technologies, ranging from data processing and handling, through to machine learning and automation, but in essence all enhance human expertise. Rather than relying solely on deterministic formulas or manual interpretation, AI-driven approaches learn from historical data, identify patterns, and can be adjusted to suit new emerging data. This contrasts with traditional analysis methods, which are often linear, hard coded and fixed in scope. Used in the right places, AI can offer something deterministic formulas cannot.
But what are the key benefits of Adopting AI
- Speed: AI-powered tools dramatically cut down the time required for repetitive tasks, such as optioneering multiple design scenarios, allowing engineers to focus on creative and critical problem-solving, on ‘higher level thinking’.
- Accuracy: Machine learning algorithms can minimize human error by applying data-driven checks and validations, improving the overall quality of designs and plans.
- Insight: Robust data analytics can reveal hidden correlations parameters, leading to new or more refined solutions which previously were not possible.
AI Tools Overview
Embracing AI doesn’t have to mean diving into complex coding or advanced programming languages. Thanks to no-code solutions, such as Civils.ai’s visual programming platform, engineers can harness the power of AI by simply dragging and dropping “prompts” or modules into a workflow. This intuitive approach makes it easy to:
- Automate tasks like searching building codes, comparing design ideas against specifications, or generating compliance reports.
- Integrate seamlessly with popular formats and tools you already use, including Word and Excel for documentation, as well as Power BI for interactive dashboards and analytics.
By streamlining the transition from raw data to actionable insights, these AI tools empower structural engineers to optimize workflows, increase productivity, and maintain a competitive edge in an evolving industry.
3. Practical Applications of AI in Structural Engineering
Artificial Intelligence is already transforming the daily routines of structural engineers, from automating tedious code lookups to generating optimized designs in record time. Below are three major areas where AI—particularly through no-code platforms—has proven to be a game-changer.
3.1 Specification Searches for Tolerances and Limits
Challenges in Manual Searching Construction Specifications
- Time-Consuming Cross-Referencing: Engineers often spend hours flipping through project specifications and design manuals to ensure all tolerance requirements are met.
- Risk of Overlooking Critical Limits: Manual checks can result in missing or misinterpreting crucial information, leading to compliance issues or costly rework.
How does it work?
- Instant Code Searches: AI-powered platforms can scan through all the project tender specs (e.g. material specifications, structural steelwork specifications, general specifications) so that you can be aware of all the requirements for your particular design element, finding any conflicting requirements, saving you time in meetings with the client later (once all these issues get raised to the surface).
- Automated Clause Extraction: Using natural language processing, the system identifies and highlights relevant clauses or thresholds, such as specific loading limits or material tolerances and can compare your proposals to specifications directly to highlight items which may not be compliant.
Benefits
- Consistent Application of Standards: By using AI to help retrieve all related pertinent clauses to the building element being considered, engineers reduce the likelihood of rework or issues being discovered later in the project.
- Reduced Risk of Non-Compliance: Immediate, automated flagging of overlooked limits ensures that critical details aren’t lost in the shuffle.
3.2 Design Optimization (not currently being done by Civils.ai)
Traditional vs. AI-Enhanced Design
- Generative Design Algorithms: Traditional design often follows a single recommended path based on standard methods. AI-driven generative design explores multiple possibilities—varying geometry, materials, and structural forms—far more rapidly.
- Balancing Complex Trade-Offs: AI tools help navigate nuanced decisions that weigh cost, sustainability, and structural integrity, providing optimal solutions in real time.
How does it work?
- Automated “What-If” Scenarios: AI can automatically adjust input parameters (e.g., material strength, loading conditions) to assess how variations impact outcomes.
- Optimal Solutions Under Constraints: Once the model runs through potential scenarios, it pinpoints the combination of parameters that best meets project goals.
Real-World Examples
- Material Reduction: Some projects see significant cuts in material use—leading to lower costs and environmental impact—when AI-guided optimization is employed.
- Faster Iteration Cycles: Engineers can test and refine multiple designs in hours instead of weeks, dramatically speeding up the design phase.
3.3 Compliance Checking Against Building Codes
Importance of Code Compliance
- Legal & Safety Requirements: From local building regulations to international standards, adherence is non-negotiable for structural integrity and public safety.
- Consequences of Non-Compliance: Fines, legal actions, and potential structural failures can all stem from oversight in code adherence.
Automated Querying & Checking Processes
- Instant answers from Building Codes: AI, especially Retrival Augmented Generation (RAG) based systems can help to find quick and accurate answers to code based questions. Building codes tend to be 100’s or even 1000’s of pages long, freeing up Engineering hours from flicking through these documents and instead having AI surface all the relevant clauses.
- AI-Based Parameter Comparison: Systems read and interpret design documents—comparing details (like beam sizes, reinforcement, or load assumptions) to relevant codes and flagging where non-compliances or non-standard items are found.
Advantages
- Significant Time Savings: Repetitive compliance checks once done manually are handled almost instantly.
- Standardized Reporting & Audit Trails: Automated documentation of checks ensures accountability and easy retrieval during audits or peer reviews.
4. How Civils.ai Empowers Engineers
No-Code AI Automations
At the heart of Civils.ai is a powerful yet intuitive visual programming language that eliminates the need for traditional coding skills. Instead of learning Python or complex scripting, engineers can simply drag and drop “prompts” to construct custom AI workflows. These prompts can pull data from multiple sources—such as PDF documents, Excel sheets, or design reports—and perform real-time checks against project parameters or industry standards.
- Connect Data Sources: Centralize and compare design, specifications, and codes without juggling multiple software tools.
- Near-Instant Outputs: Upload a project file and the workflow is selected and run the analysis begins, delivering feedback in seconds on potential issues or optimization opportunities.
Integration with Industry Tools
Civils.ai is designed to fit seamlessly into the workflows engineers already use. Outputs can be exported directly into Word or Excel, and information can be pulled from Autodesk Construction Cloud or Sharepoint, dashboards can also be linked in Power BI for visual analytics. This integration saves teams from manual re-entry of data, reduces errors, and promotes transparent communication across project stakeholders.
- Word & Excel Compatibility: Automatically populate reports, compliance checklists, or cost analyses in widely used Office formats.
- Power BI Dashboards: Monitor project progress or design comparisons in interactive, shareable dashboards for better decision-making and collaboration.
Success Stories from Leading Consultants
Several industry giants—including Arcadis, ARUP, and WSP—have adopted Civils.ai to streamline their design and modelling workflows. By automating tasks that previously consumed hours of manual effort, these firms are seeing faster turnaround times and improved quality assurance. Although each firm’s journey is unique, a common thread is the tangible value gained through reduced risk, increased efficiency, and data-driven insights.
Free “AI in Construction Certification”
Recognizing that many professionals are eager to harness AI but unsure where to begin, Civils.ai offers a 7-hour “AI in Construction Certification” course—completely free, online and open to anyone. Participants gain a foundational understanding of AI concepts, explore real-world case studies, and learn to build their own no-code AI automations. This community-supported program ensures that even those without a formal computing background can confidently integrate AI into their projects, driving innovation across the entire construction industry.
5. Getting Started: Steps for Engineers and Firms
Identify the Right Use Case
When introducing AI into your structural engineering processes, start with a single, high-impact application—such as automated specification searches, basic design comparisons, or code compliance checks. Choosing a well-defined use case not only keeps the scope manageable but also allows you to demonstrate quick wins. As the team sees tangible value and grows comfortable with the technology, you can gradually scale to more complex scenarios or additional projects.
Assemble the Right Team
Successful AI integration is a collaborative effort that combines domain expertise with automation capabilities. Engineers, architects, and project managers should work closely with AI tools to align technology with real-world requirements. At the same time, it’s crucial to focus on upskilling—encourage your team to explore training resources (including free courses like Civils.ai’s “AI in Construction Certification”) to build a baseline understanding of how AI can augment their existing workflows.
Pilot and Iterate
Rather than rolling out AI capabilities across an entire organization at once, begin with small pilot projects where you can closely monitor outcomes. Gather feedback from users, identify bottlenecks, and refine processes before scaling to larger or more complex initiatives. This iterative approach helps establish best practices, minimize risks, and ensure that the new technology is effectively integrated into everyday engineering tasks.
6. The Future of AI in Civil & Structural Engineering
Emerging Technologies
The horizon of civil and structural engineering is expanding rapidly, with AI merging seamlessly into other advanced technologies. IoT sensors can feed real-time data from within structures—such as load, stress, and environmental conditions—directly into AI algorithms for immediate analysis. Meanwhile, robotics and AR/VR are poised to streamline on-site construction tasks, improve project visualization, and reduce manual labor. Over time, these advancements pave the way for fully automated construction sites and the widespread adoption of digital twins, where virtual replicas of structures are continuously updated with live data to enhance decision-making and predictive maintenance.
Shifting Industry Landscape
As AI matures, data-driven decision-making will become the norm at every stage of engineering projects—from early feasibility studies to final inspections. Engineers, contractors, and project owners will increasingly collaborate through shared digital platforms, reducing silos and accelerating project timelines. This shift also encourages the development of standardized data formats, enabling better integration between AI tools, BIM software, and traditional engineering workflows.
Opportunities for Continuous Improvement
Looking ahead, sustainability and efficiency stand out as major growth areas for AI. Optimization algorithms can guide engineers toward net-zero carbon design strategies, identifying greener materials and construction methods without compromising performance or safety. Real-time project management dashboards, powered by AI analytics, will offer stakeholders ongoing insights into cost overruns, schedule delays, and resource allocation—allowing for swift interventions and continuous refinement. By capitalizing on these opportunities, the industry can foster a culture of innovation that delivers enduring, high-quality structures for generations to come.
7. Conclusion
Throughout this guide, we’ve examined how AI can streamline specification searches, optimize design processes, and automate compliance checks—three practical areas that showcase the technology’s transformative potential in structural engineering. By adopting AI-driven workflows, engineering teams stand to gain increased efficiency, reduced errors, and the ability to adapt quickly in a rapidly evolving industry. However, realizing these benefits requires a willingness to upskill and embrace new tools—an investment that will pay significant dividends as construction projects grow in complexity.
If you’re eager to explore AI’s possibilities further, we invite you to enroll in our free “AI in Construction Certification.” This 7-hour course provides a solid foundation in AI concepts and showcases real-world examples, all without requiring any coding background. By walking you through no-code AI solutions on the Civils.ai platform, we’ll show you just how easy it is to get started, regardless of your technical expertise.
As a final thought, remember that AI is an ally—it augments your engineering expertise rather than replacing it, taking over repetitive tasks and enabling you to focus on creative problem-solving and high-level decision-making. Looking ahead, embracing AI not only promises safer, more efficient, and sustainable structures, but also positions your team at the forefront of an industry-wide transformation.