How to Automate Building Design: Adapting to Local Codes
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Earlier work carried out within a tier-one property and construction company focused on exploring how to automate complex building design processes. The industry insights shared here are drawn from that experience, and they continue to shape how Exelsiv approaches design automation in Architecture, Engineering and Construction (AEC).
Read Part 1: How to Automate Building Design: A Case Study
Read Part 2: How to Automate Building Design: Product-Informed Digitization
The Problem
Automating building design is not only a technical challenge but also a contextual one. Every region applies its own construction codes, certification pathways, and approval frameworks. A design that satisfies one jurisdiction may be rejected in another, not because it performs poorly, but because it fails to meet the local interpretation of compliance.
These differences extend through every layer of a project: from fire resistance and structural performance, to acoustic, thermal, and energy efficiency standards, to how evidence of compliance must be documented. A clause that changes a single number or reference standard can shift an entire outcome.
Digital design systems depend on structured, repeatable rules. Compliance relies on human interpretation and local nuance. Bringing these two worlds together is what makes scaling automation across geographies so difficult.
The question is not whether design automation can be achieved, but whether it can remain reliable, trusted, and compliant once it meets the diversity of local regulation.
The Approach
Research in this area highlights that automation for compliance in design improves both efficiency and accuracy but faces challenges due to the inherent subjectivity and variability in how regulations are interpreted across contexts. As noted by studies focused on automation in healthcare project design, these nuances mean that trusted automation requires a hybrid approach that combines machine logic with professional judgment [1].
Therefore, to make automation context-aware, we began by unpacking the structure of regional codes. Instead of treating each document as a static reference, every clause was examined for how it could be represented as a condition, parameter, or relationship.
1. Breaking down the code.
Each requirement was translated into explicit logic. Where a rule specified a measurable performance outcome, it was expressed as a parameter range. Where it referred to a particular test or certification, it became a conditional rule linked to supporting evidence. Clauses that required professional judgement were noted as decision points, marking where human review remained necessary.
2. Revealing inter-dependencies
Codes rarely exist in isolation. Requirements in one section often depend on another. Making these links visible allowed design systems to apply rules in context rather than as isolated checks.
3. Layering the logic
Universal engineering and design principles such as geometry or load paths formed the base. Regional rules were added as overlays that adjusted parameters according to local conditions.
This structure allowed the same automation logic to operate globally while interpreting results locally.
Translating Code into System Logic
The most difficult step involved turning human interpretation into computer logic without distorting the intent.
In practice, translating codes into digital systems is rarely a straightforward process. Clauses often rely on implicit reasoning that engineers absorb through experience rather than documentation. For example, mass timber flooring in a building in Australia typically does not require a cement topping, while the same system in the United States often does [2]. Both outcomes are technically sound, but they arise from different testing standards, approval pathways, and interpretations of risk.
Our approach focused on identifying these contextual differences and mapping where the logic could be generalized versus where it depended on local convention or professional judgement. The goal was not to reduce decision-making to a binary flowchart but to expose the underlying relationships between requirements, interpretations, and the data that supported them.
Through this analysis, it became clear that some aspects of compliance could be codified precisely, while others would always rely on professional judgement. Those areas were intentionally left open for manual verification, creating a hybrid workflow that combined automation with engineering expertise.
The Outcome
The work demonstrated that regulatory logic could be structured in a way that adapts intelligently to different environments, maintaining consistency while responding to local requirements.
Early iterations showed the potential for meaningful improvement in how compliance is managed and verified.
Scalability → A single logic base could be extended across markets, with regional overlays introduced as needed.
Traceability → Each rule carried a clear link to its governing clause, enabling transparency for verification and certification.
Consistency → A structured decision process helped reduce compliance gaps and improve coordination between disciplines.
Efficiency → Engineers could direct more attention to higher-value analysis, relying on automation for routine interpretation.
The approach revealed how localization could become a manageable, repeatable process rather than a barrier to scaling automation. It provided a foundation for future systems capable of connecting regulatory intent with digital design logic in a consistent and transparent way.
So What?
Localization is often the biggest obstacle to scaling digital design. Converting regulatory complexity into structured, traceable logic makes it possible to build systems that understand context instead of breaking because of it.
This shift transforms automation from a technical demonstration into a practical standard that can be trusted across jurisdictions. It enables design processes that are faster, more accurate, and inherently more transparent.
As the industry moves toward integrated digital delivery, localization will determine whether automation remains confined to pilot projects or becomes an operational norm across markets.
The Role of AI Today
The work described above began in 2020, before artificial intelligence became part of mainstream digital workflows. At the time, automation was largely rule-based, relying on explicit logic rather than generative reasoning. The focus was on building clarity, structure, and transparency rather than speed.
Industry experts emphasize that AI-powered code compliance is revolutionizing design and construction efficiency by automating complex analyses, but the success of these technologies hinges on the clarity, transparency, and traceability of the underlying rule-based systems that govern compliance logic [3].
Today, AI has expanded what is possible. Large language models can interpret text-based regulations, group related clauses, and suggest logical relationships across jurisdictions. Machine learning can identify equivalencies and discrepancies between regional standards far faster than manual analysis ever could.
Yet these tools still depend on what was built first: a clear, systematized foundation. AI can accelerate interpretation, but it cannot replace the structure or reasoning that make the logic meaningful. The groundwork established in those early years remains essential. It showed that before intelligence can be artificial, it must first be made explicit.
Exelsiv Insight
The lessons from this work continue to inform how Exelsiv helps organizations today. We apply the same principles: mapping regulatory logic, embedding local compliance pathways, structuring data for traceability, and connecting design processes with real-world codes and approvals.
The result is the same ambition: greater certainty, smarter systems, and more productive ways of building, regardless of geography.
As design practices expand globally and governments pursue digital transformation, the ability to adapt automation to local context will become critical. Localization will shape how digital systems mature and how trust in automated design is built.
If your organisation is exploring how to make regionally compliant design automation part of its future, Exelsiv can help chart the path forward. Get in touch with us today.
Resources:
[1] Soliman-Junior, J., Tzortzopoulos, P., & Kagioglou, M. (2022). Designers’ perspective on the use of automation to support regulatory compliance in healthcare building projects. Construction Management and Economics, 40(2), 123-141.
[2] WoodWorks. (2025, June 29). Design considerations for poured toppings on mass timber floor panels. WoodWorks | Wood Products Council.
[3] NOVEDGE. (2024, November 13). AI-Powered Code Compliance: Revolutionizing Design and Construction Efficiency. NOVEDGE Blog. https://novedge.com/blogs/design-news/ai-powered-code-compliance-revolutionizing-design-and-construction-efficiency
