BITAC Luxury 2026: Leveraging AI to Elevate Luxury Brand Performance

By Joe Waskewich | March 6, 2026

When Aimee Marling asked the audience at the recent BITAC Luxury to raise their hands if they had used AI that day, nearly everyone had, whether they realized it or not. They had used AI tools to navigate traffic, clean up email drafts or scroll their social feeds that are quietly shaped by machine learning. 

“AI isn’t coming anymore,” Marling said. “It’s here.”  

For luxury hospitality and design, the issue isn’t whether AI will appear; rather, it’s how professionals will use it without diluting what makes their work special. 

Marling, who is vice president and design director at the luxury design firm Monarch and Maker, was joined by three executives:  

• Sabine Grimes leads Unison Group, a studio focused on luxury hospitality projects and multifamily projects; 

• Alex Kravetz, who is based in London and Venice, leads Alex Kravetz Design, a studio focused on high-end hospitality and residential projects for clients who want homes that operate almost like hotels;  

• and Svetlana Muzaleva of Next Design Studio, a firm with experience in boutique hotels, restaurants and luxury projects, often with tight budgets that demand clever value engineering. 

 As they exchanged experiences and ideas, they painted a picture of an industry that is curious about AI, cautious with shortcuts and determined to keep human experience at the center. 

Luxury Isn’t Just Opulence Anymore 

Marling opened the discussion by pointing out a shift that many hoteliers and designers already feel in their day-to-day work. Luxury hospitality used to be defined by sheer opulence—more marble, more chandeliers, more spectacle.  

Today, guests measure luxury in different ways. They look for individualization: a stay that feels like it was designed around their preferences. They also notice when everything feels effortless, even though the teams behind the scenes know how much hard work goes into providing an exceptional guest experience. 

Although AI can support predictive personalization and operational efficiency, Marling reminded the audience that developing those systems requires data — and consumers are uneasy about how their data is collected and used. She recalled how guests might joke about their phones “listening” to conversations, but then they see eerily targeted ads that make them feel uneasy. They dislike that feeling of intrusion. Even so, guests still expect the room, the service and even the food to “just get them,” she said. That gap between guest expectation and comfort is where luxury brands now operate. It’s also where incorporating AI into workflows becomes both practical and tricky. 

So, how do design professionals in the hospitality space navigate that gap? “How are we staying relevant?” Marling asked the panel. 

‘Leaning into the Human Component’ 

From Grimes’ point of view, AI supports the work; it doesn’t overtake the project. 

“We’re leaning into the human component,” she said. “What we need as human beings are really authentic experiences. And because AI is becoming more prevalent, the need for authenticity and human connection has gotten even greater.” 

As algorithms touch more parts of the guest journey, Grimes says, she sees a stronger need for human-scaled moments in rooms and public spaces. 

“We’ve been trying to figure out how to make these touch points in hotel rooms more tactile, more emotive,” she said.  

If AI and automation become responsible for many of the invisible processes behind a stay, design must work even harder to keep guests feeling engaged in the moment. 

Grimes says she uses AI as a mirror that can identify the best elements from past projects and then present them in new combinations. That’s useful, but she says she and her team also consider what the AI tools might be missing: What doesn’t the software know? Is it accounting for site constraints? Ownership groups? Staff culture? Guest psychology?  

So, from Grimes’ point of view, AI output is raw material that still requires a layer of human judgment. She added that AI doesn’t see the countless human decisions and conflicts that shape every real-life project. AI sees data and images, not the friction behind them. That missing context, she said, creates space where designers still add irreplaceable value. 

What AI Still Can’t Replicate 

Kravetz offered his own counterpoint. In his view, there are several qualities that define high-level design work, and AI has no real foothold in them. He called out three “I’s” that guide his practice: 

• Improvisation – the live, in-the-moment decisions that happen in client meetings, construction walk-throughs and last-minute crises. 

• Intuition – the gut sense built from decades of travel, exposure and project experience that tells a designer when a concept will resonate with a guest or a brand, even before the data catches up. 

• Innovation – the ability to move beyond recombining existing ideas and push toward a genuinely fresh concept. 

Based on his experience, Kravetz says that AI tends to recycle patterns. He says you can tell it to blend the style of two iconic designers and it will produce compelling images. For most guests, that might be enough. For clients seeking ultra-bespoke spaces designed to embody a specific personal or brand “DNA,” a remix isn’t sufficient. 

Kravetz said he sees this tension leading to a split in the market. On one side, developers and operators who care mainly about return on investment and consistent delivery will lean into AI for standardization and speed. On the other side, clients and brands that insist on true individuality will continue to rely heavily on humans who bring improvisation, intuition and innovation to the table. 

The tools will get better, he said. But they won’t acquire lived experience. 

Mixed Feelings: AI in the Studio 

Muzaleva admitted to having “mixed emotions” when describing her relationship with AI. She says she values the speed. She likes being able to generate visual options quickly or explore aesthetic directions before investing in full-blown renderings. Those quick studies can be helpful for clients who have difficulty visualizing a space, she said. 

It’s when AI shifts from tool to shortcut that concerns Muzaleva. Designers can be tempted to rely on a striking AI-generated image that hasn’t been tested against reality. To someone outside the field, the picture looks ready to build, but perhaps there are assemblies that won’t pass code or details that would explode the budget. She argues that the gap between image and real-world constructability is dangerous. Firms need senior people looking at AI output and asking whether it reflects genuine knowledge of how buildings come together.  

“Somebody has to be introducing checks and balances,” she said. “Like, ‘Yeah, that’s unrealistic. That looks pretty, but it’s not going to happen.’ ” 

Intellectual property is also a concern, Muzaleva said. Because AI systems pull from vast pools of images and references, there’s a risk of incorporating another designer’s signature idea into a design without intending to. In luxury hospitality, where brand identity and differentiation matter, that kind of unintentional borrowing can be a serious problem. 

Even with her concerns, Muzaleva says she’s not against AI. She says she hopes AI can help develop workflows where the designer can rely on AI for the tedious parts of the process while staying firmly in charge of the creative core. 

How Designers Are Actually Using AI  

Behind the philosophical debate, all three panelists say they are already weaving AI into daily workflows. 

Muzaleva uses it for research and background gathering. Instead of manually chasing competitive sets and concept precedents, her team can reach a baseline of understanding much faster than they could using conventional search. The information still needs to be filtered, but the starting point moves closer to the goal. 

Grimes turns to AI when she wants to compare new ideas to her firm’s own archives. It helps surface patterns they might not notice otherwise. Once those patterns are visible, her team can lean into them or push away from them, depending on what the project needs. 

Kravetz described his studio as digital from the day he left a large hospitality design firm and started on his own. For him, AI is the latest layer in a long history of adopting technology to compete with bigger companies. Today he runs multiple screens at once, using automated tools for tasks like orientation studies, basic planning analysis and other forms of preliminary research. That allows him to spend more of his time on conversations with clients and refinement of ideas. 

Within many firms, there’s also an informal division of labor. Junior staff often “play” with AI tools, generating a spread of options. Senior designers review those options, flag what’s unrealistic and keep the conversation grounded in client goals, building physics and budget. AI helps widen the field of possibility but doesn’t decide where the project should land. 

A Split Market: Cookie-Cutter and Ultra-Bespoke 

As these tools mature, the panelists expect the industry itself to polarize. 

Muzaleva predicted that some companies will specialize in “across the street” projects — highly replicable concepts that can roll out at scale with significant AI support. At the other end of the spectrum, she sees a healthy future for studios focused on one-of-a-kind properties. These are the hotels, resorts and mixed-use destinations that treat design as an artistic act rather than just a layout problem. For those, AI may handle portions of the process, but the soul of the work still originates in the designer’s accumulated taste, memories, and point of view. 

Kravetz suggested that AI may enable a different staffing model altogether. He referenced the notion that a single person can now operate a company at a scale that once required dozens. He doesn’t expect that to erase the need for designers. He expects it to concentrate influence in fewer hands. The people who can direct those engines effectively — and still bring human improvisation, intuition and innovation to bear — will handle more work, with less support staff, than would have been feasible a decade ago. 

The Limits of Predictability 

During the Q&A, one audience member asked about using large language models (LLMs) to create more predictable outcomes — tracking implications of design decisions from specification through cost and impact. 

Kravetz said the scenario is plausible. In time, designers may be able to feed an entire project into an AI platform, set a target budget and ask it to generate purchase orders and vendor recommendations. But he and Muzaleva both cautioned that even the best system runs into real-world noise. 

Citing political swings and supply chain shocks as examples, Muzaleva explained that these are the types of external forces that no model can forecast perfectly. There’s a possibility, she said, that AI could be used for cross-industry platforms that allow owners, designers and suppliers to efficiently work from the same data, but it would not make the process perfectly reliable. 

Grimes illustrated that point with a real-world example from a hotel project in Toronto. The team had software in place. Not everyone used it correctly. Different sets of information were uploaded. Field teams didn’t always check the latest information. Trades built from outdated sets. The result was a cascade of coordination problems that had nothing to do with the software and everything to do with human behavior. 

Her conclusion was blunt: as advanced as AI becomes, humans remain both the biggest opportunity and the biggest source of risk. Technology can surface the right data and push it to the right place. If no one looks at it, the project still veers off course. 

What Decision-Makers Can Do Now 

For decision-makers in luxury hospitality, the panel’s discussion suggests several moves worth considering. 

First, protect human judgment where it matters most. Use AI to accelerate research, documentation and other low-visibility tasks that eat up billable hours but don’t define the guest story. Reserve human attention for concept definition, narrative and the details guests will remember when they talk about a stay months later. 

Second, build explicit guardrails around AI-generated ideas. Make sure senior designers or experienced operators review concepts and images produced by AI before they reach owners or operators as “solutions.” Someone has to ask whether the design can be built, whether it fits the brand and whether it respects the competitive landscape rather than replicating others’ work. 

Third, plan your portfolio with the future split in mind. Some assets can live comfortably in the standardized, AI-heavy space, where speed and repeatability matter most. Others should be treated as flagships that rely on hand-crafted experience. Being clear about which properties live in which category will help owners and brands set realistic budgets and expectations. 

Finally, invest in experiential knowledge. No model can ingest a full lived experience. Travel, site visits and time spent inside competitive properties still matter. 

From Data to Distinction 

As the session wrapped up, the conversation returned to a theme that had surfaced throughout the discussion: AI is not replacing luxury designers. Instead, it is changing what distinction looks like in a world saturated with data and imagery. 

For design executives, the challenge isn’t whether to adopt the tools, but how to use them without losing the human judgment, storytelling and experience that define luxury hospitality.  

 

Jacqui Barrineau is editor at Hotel Interactive, an online trade publication featuring curated news and exclusive feature stories on developments, trends and thought leaders in the hospitality industry. After 20 years in daily news, she moved into B2B journalism, working with the chemical, glass, paper and healthcare industries before serving as editor-in-chief of an association magazine. 

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