By Mo Elsayed, Justin Shultz, and Jill Kurtz
A new era of design is emerging where building performance and creativity are evaluated in real time, offering benefits to the planet and to the designers shaping it. Imagine if an architect could test dozens of building design ideas before lunch, instantly assessing each for energy efficiency and carbon impact with early-stage performance insight. This scenario highlights a pivotal moment for architecture and engineering as research and technological advancements combine to create performance-focused, sustainable buildings that benefit people and communities. Buildings are considerable contributors to energy use and emissions, prompting tighter regulations and standards, so balancing innovative design with strict sustainability goals is more important than ever. Traditional workflows that often involve late-stage energy analysis can come too late in the design process or slow decision-making. To meet climate targets, the industry needs a more integrated, iterative approach to energy modeling throughout the design process.
Now, with the advent of generative AI, Stantec is reshaping the design process, allowing for rapid iteration with real-time feedback on building performance through an AI-driven framework for accelerated energy modeling. Detailed energy modeling is too slow and specialized to keep pace with design deadlines, with some models requiring up to 80 hours and specialized knowledge. As a result, early energy analysis has often been seen as a luxury or a roadblock when traditional building energy modeling (BEM) workflows struggle to match the accelerated pace of modern design development driven by computational design tools and value-engineering pressures.
The need for speed in building design
Contemporary architects and engineers face a dual challenge: create innovative, visually appealing spaces while also meeting increasingly strict sustainability and energy goals. Buildings account for a significant portion of global energy consumption, about 37% of CO₂ worldwide.
In response, building energy codes and green standards are becoming stricter, requiring project teams to improve insulation, glazing, and HVAC systems to reduce energy use and carbon footprint. Climate action is now integral to design decisions, which must be considered from the start. However, traditional workflows haven’t made this easy. BEM, which uses software to simulate a building’s energy performance, has historically been time-consuming and requires specialized knowledge.
Conventional design can be siloed, with architects planning form and features first, and engineers conducting energy analysis later, sometimes only to meet minimum energy code requirements. This separation limits opportunities for synergy, as small decisions such as window sizing and HVAC layout, can affect energy efficiency. When performance is evaluated only at the end of the process, improvements are often too costly or impractical because of long lead times. The industry recognizes that an integrative design approach creates right-sized systems and reduces both upfront and operational costs. More importantly, these tools and workflows used to support this approach need to evolve.
To achieve performance by design, project teams must iterate and test design options and evaluate their performance results throughout the design process, not just at the end. The American Institute of Architects (AIA) now recommends “performing iterative energy modeling throughout the design process” as a key strategy for reaching efficiency and zero-carbon goals. Ideally, every major design decision, such as shifting a building’s orientation, increasing window size, or modifying materials, would be immediately followed by a building performance analysis to inform that choice. As Mo Elsayed, senior building performance manager from Stantec, explains, “Solutions for the future require rapid, smart iteration of building design, and the energy performance feedback loop needs to move just as fast.”
Generative AI: A new creative partner for sustainable design
Generative AI refers to artificial intelligence—often powered by advanced machine learning models like large language models (LLMs)—that can do a variety of tasks. It is quickly transforming the architecture, engineering, and construction (AEC) industry. Tools like Stable Diffusion, Midjourney, and other AI image-generation models now give designers the opportunity to translate simple prompts or rough sketches into rich architectural renderings, massing ideas, or mood boards in seconds. This has opened new possibilities for creative exploration, allowing architects to iterate visually more efficiently. A designer can now type in “A sleek, futuristic office building with glass façades” and receive multiple design interpretations instantly, something that would have taken hours or days using traditional tools.
" }Rendering showcases Stantec’s AI framework, which quickly generates a multitude of designs from a single sketch or prompt. If a sketch or prompt is loaded in the morning, around 200 new designs are generated by lunchtime, thanks to the AI's ability to operate at low frame sizes, allowing rapid iterations within minutes.
While this new wave of AI tools has simplified the aesthetic aspects of iteration, a critical piece has often been overlooked: performance. Visual outputs can spark bold ideas, but they don’t show how a building will perform—its energy use, daylight penetration, or performance against climate goals. Recognizing this gap, Stantec developed an AI framework that extends the power of generative tools beyond form-finding. Instead of just creating renderings, this innovation integrates building performance into the design process. As Mo Elsayed explains, “This method embeds performance in the first sketch instead of treating it as an afterthought.”
In a peer-reviewed study published in 2025, Stantec unveiled an AI-driven framework for rapid energy modeling. The AI is integrated with parametric design tools (such as the Honeybee/Ladybug toolkit popular in architectural modeling), so that architects don’t have to stop their design process and wait; the iterations can happen in parallel with creative exploration. The results of this approach are encouraging. In their tests, the Stantec team reported a 100% convergence rate in automatically generating functional energy models from a variety of text and image prompts. This shift means that while others use generative AI to explore what a building might look like, Stantec’s approach helps teams understand how that building will perform without breaking the creative flow. By integrating AI with parametric design tools, performance feedback is delivered in real time alongside form exploration. The outcome is more than a beautiful concept; it’s also a smart one.
Supporting “performance by design” in practice
What does this AI-enhanced iterative design look like in practice? This AI-enhanced iterative design process helps visualize a typical early design scenario, such as an architect modeling a new building in a 3D software environment, exploring different massing options or façade configurations. Traditionally, assessing energy performance on each option would require interrupting the workflow, getting a specialist involved, and waiting for results, by which time the design might have progressed. Now, with an embedded AI assistant, the architect can describe adjustments in natural language or feed in a quick sketch, and receive immediate feedback like, “Option A is projected to use 15% less energy annually than Option B, mainly due to better daylight usage and a smaller cooling load.” This quick insight guides further iterations, fostering a unified loop of design and analysis that boosts creativity and performance accountability. Automating the routine tasks gives professionals more time to focus on refining strategies and interpreting results, rather than drawing geometry or transcribing data. Because it’s automated, this approach scales easily, from a single building to hundreds, allowing for analysis at an urban scale or testing many design alternatives in a fraction of the usual time. In short, generative AI helps expand what is possible for sustainable design: more ideas tested, more insights gained, quicker and faster. The core theme is “rapid iteration without incurring time penalties,” reducing the historical trade-off between designing freely and rigorous analysis.
This breakthrough aligns with the shared responsibility and collaboration in the building industry. High-performance, low-carbon design is no longer the domain of specialized consultants or energy engineers; it’s becoming part of everyone’s role. Industry guidelines emphasize that everyone on the team should understand a project’s energy benchmark and goals from the outset. That includes architects, clients, engineers, contractors, and other stakeholders. Stantec’s integrative approach embodies this, making energy modeling user-friendly and accessible. As Mo Elsayed points out, “When a tool is easy and fast, people are far more likely to use it.” Generative AI allows more team members to engage directly with performance data, transforming energy and carbon considerations into creative parameters alongside cost, aesthetics, or program needs, which designers can manage in real time.
" }Rendering showcases Stantec’s AI framework, which quickly generates a multitude of designs from a single sketch or prompt. If a sketch or prompt is loaded in the morning, around 200 new designs are generated by lunchtime, thanks to the AI's ability to operate at low frame sizes, allowing rapid iterations within minutes.
AI is democratizing building performance analysis, fostering an integrative design culture where owners, architects, and engineers collaboratively set performance targets from the outset. These tools result in a more informed design process where sustainability is baked in by design, not applied as an afterthought. Crucially, AI doesn’t replace human ingenuity or the need for technical oversight; instead, it enhances the team’s capabilities. Designers are still needed to define high-performance goals, such as energy efficiency, daylight access, or net-zero carbon, and interpret the results in context. Energy specialists are still vital for advanced analysis and checking for accuracy. Rather than replacing technical knowledge, AI allows them to focus on higher-level analysis and innovation. It’s like having a super-fast calculator that reduces grunt work. It won’t design the building for the designers, but it gives the team time to focus and prioritize creative problem-solving.
The introduction of generative AI into Stantec’s design workflow transforms a previous challenge (slow, complex energy modeling) into an opportunity to innovate. AI is now the catalyst for faster, smarter iterations that integrate sustainability at every step. Stantec’s pioneering research paper, “User-friendly AI-driven automation for rapid building energy model generation,” shows this isn’t a distant dream but a current reality backed by data. By pre-training an AI on building science knowledge and coupling it with design software, the team showed that even complex tasks like EnergyPlus simulations and Radiance daylight analyses can be streamlined instantaneously into part of the design cycle. This advancement comes at a critical time for the AEC industry. With climate goals on the horizon (2030 and 2050 benchmarks for emissions reductions), the outdated paradigm where performance analysis is too slow or optional is no longer feasible. Generative AI offers a way to meet that demand by collapsing the timeline between idea and feedback. It transforms energy modeling from a bottleneck into a source of inspiration, another dimension in which to innovate. Architects can ask “What if?” and actually get feedback while the idea is fresh.
Stantec's approach builds on its history of combining design with technical rigor. Today, this dedication continues through the use of advanced tools, including AI, which can improve the understanding of how design choices influence performance outcomes from the earliest design stages. This evolution demonstrates how technology, such as generative AI, informs and supports the developing framework for sustainable and efficient building design, where creating a building is not just about form and function, but about integrating performance considerations from the earliest sketches.
A version of this blog was originally published by Page, now Stantec.
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