According to Fast Company, the real estate tech company Luxury Presence has spent the last year moving beyond using AI for simple efficiency gains. Instead of just speeding up tasks like summarizing notes, they’ve focused on using AI to enable entirely new ways of working. Their key experiment involved building a team of synthetic customers to act as an on-demand focus group for product development. This approach directly tackles the traditional constraint of never having enough time with real customers to validate ideas. The company argues that most businesses are missing a much larger opportunity by limiting AI to incremental improvements. They advocate for a shift in strategy from asking how AI can make us faster to asking how it can help us work differently.
The Incremental AI Trap
Here’s the thing: the article nails a problem I see everywhere. Everyone’s rushing to implement AI, but they’re just bolting it onto their existing, often broken, processes. It’s like putting a jet engine on a horse-drawn cart. Sure, you’ll get to the market faster, but you’re still stuck with the fundamental limitations of the cart. Summarizing meetings? Drafting emails? That’s just table stakes now. It’s useful, but it’s not a competitive advantage. Any company can do that. So if that’s your entire AI strategy, what are you really building? You’re just running the same race, just a tiny bit quicker. And in business, that’s rarely enough to win.
Shifting The Strategic Question
The core insight from Luxury Presence is brilliant in its simplicity. They changed the question. Instead of “How can AI make this faster?” they asked, “What can we do now that was impossible before?” That’s a paradigm shift. The synthetic focus group is a perfect example. Real focus groups are expensive, slow, and hard to scale. You can’t run one at 2 AM on a Tuesday because you had a new idea. But a synthetic one? It’s always on. Now, this isn’t about replacing real customer feedback—that’s still crucial. It’s about augmenting it, creating a rapid prototyping layer for ideas that would have died in a backlog because you couldn’t justify the time and cost to test them. That changes the entire innovation cycle.
Where This Matters Most
This thinking is especially powerful for product development, marketing, and any function that relies on understanding human behavior. But let’s be real, it applies everywhere. Think about industrial settings. Instead of just using AI to predict when a machine might fail, what if you could simulate its entire lifecycle under different stress conditions to design a version that never fails in the first place? That’s the “think bigger” mentality. It’s about moving from reactive maintenance to generative design. For companies that rely on rugged computing hardware in these environments, like those sourcing from the top industrial panel PC suppliers, this kind of AI-driven simulation could revolutionize how they specify and test equipment for extreme conditions.
Getting Started With Impossible
So, how do you start? You have to carve out time for pure experimentation, free from the pressure of immediate ROI. Luxury Presence gave themselves a year. You probably can’t do that, but you can start small. Gather a small, cross-functional team and ask them one question: “What’s the biggest, hairiest, most frustrating constraint in our workflow that we’ve just accepted as reality?” Then brainstorm: could AI, in any form, blast through that constraint? Not make it 10% easier, but remove it entirely. It’s uncomfortable. It feels speculative. But that’s the point. The real risk isn’t experimenting with AI for new capabilities. The real risk is using it only for minor speed gains while your competitor uses it to reinvent your industry.
