Big data has taken every industry by storm, but so far the lodging industry has largely been immune. That’s set to change. Over the last few years, an army of PropTech start-ups have taken aim at the commercial real estate industry, positioning themselves to disrupt how developers buy, sell, and manage property. Commercial real estate is the tip of the spear right now, but the lodging industry’s turn is right around the corner.

For hospitality architects, big data has the potential to help plan more efficient and profitable hotels, streamline the design process, and improve the guest experience. AI-powered tools are de-risking the hotel development process, improving financial and operational performance, and enabling a new future of data-driven design.

Evolving the Standard Design Process 

AI has inaugurated a shift in the practice of architecture, moving from a passive design process to a new, generative approach. In a nutshell, while passive design starts with an idea for a building and then analyzes it, generative design starts with a set of success criteria and generates thousands of ideas for a building that would meet those parameters. In the time a designer could create and validate four design schemes, an AI engine can generate a million, and recommend the optimal configurations based on precedent and proprietary data sets.

The advantages are profound. Rather than spending a little time being creative and a lot of time crunching numbers, generative design allows designers to spend a little time up-front dialing in variables, and more time crafting guest experiences. More importantly, the generative approach creates data-rich architecture in a way passive design doesn’t. Because the digital models that emerge are still attached to the data sets that originate them, designers can continue tweaking parameters and see how it affects performance throughout the design process.


For example, LEO A DALY is working with PropTech startup Parafin to develop software that connects with existing parametric-design tools, tying design directly to financial data. Parafin’s platform accelerates the site-acquisition process by rapidly generating design concepts, budgets, and investment proforma for real-estate developers. Having variables such as height, guestroom count, square-footage, budget, FAR and profit margin all connected in a digital model will help designers make better decisions faster.

A Deeper Layer of Data

Optimizing the form and location of a building is just the beginning. Designers can apply the same precision to variables within the hotel itself. Every municipality, hotel brand, developer, and operator has rules that govern everything from how far the building is from the curb to the sizes of parking spaces, guestrooms, columns, and floor composition. Each variable has a price tag, and at scale, a ripple effect on construction cost.

These variables are important, but they’re not what gets a designer up in the morning. Automating them leaves more time in the design process to integrate meaningful things like sustainability into the model. A variable like window size, for example, has a dramatic effect on building performance. Heat gain, material cost, and energy-efficiency are all affected, not to mention viewshed and natural-light penetration. Oftentimes those variables are determined by brand standards and never second-guessed. With a data-rich neural model, designers can question those assumptions and find balance between performance and cost.

What if changing the window coverage by one percentage point reduces the energy cost by millions of dollars in hard or soft costs? With AI, it’s not just hunch—it’s a question with a verifiable answer. And because it’s happening early in the design process, it’s a change that costs practically nothing to make.

AI automates the tedious elements of design, freeing up time to focus on meaningful aspects like sustainability and the guest experience. Here an algorithm zeroes in on the optimal size shading device for each room to maximize daylight and energy efficiency. (Image: LEO A DALY)
AI automates the tedious elements of design, freeing up time to focus on meaningful aspects like sustainability and the guest experience. Here an algorithm zeroes in on the optimal size shading device for each room to maximize daylight and energy efficiency. (Image: LEO A DALY)
The Feedback Loop

The next step in AI-aided design will be reintegrating real-world performance data from built hotels into design tools. With smart devices tracking use data, hotels will become part of a continuously evolving and improving system. The beginnings of this system are already emerging, with sensors tracking the locations and stocking of housekeeping carts, and in-room sensors tracking use of drawers, phones, and furniture. For operators, insights like these can inform everything from next year’s capex to next week’s staffing. For designers, that data will be valuable in training modeling software to anticipate use trends and design better hotels.

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Ryan Martin, AIA, is vice president, director of design–hospitality with LEO A DALY, a planning, architecture, engineering, and interiors firm. He can be reached at Craig Forneris is digital practice manager in LEO A DALY’s Dallas, Texas, design studio. He can be reached at


  1. Wow, I’ve never heard generative design described so simply and intuitively before. Thanks for this very useful article.

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