Revenue management has never been under more pressure. Rising operational costs, economic uncertainty, and shifting guest expectations are forcing property managers to optimize every dollar. At the same time, AI promises to revolutionize how we approach pricing, but the industry remains split on whether that promise is real or premature.
At this year’s GuestyVal, one panel tackled these tensions head-on. Shay Many, Guesty’s Senior Director of Product Management, assembled three experts with wildly different perspectives on the future of revenue management: AJ Brooks, CEO of AXL House, Daniel Zammata, Senior Solutions Consultant at PriceLabs, and Sean Rakidzich, founder of the mentorship program Million Dollar Renter.
What unfolded was a healthy debate that revealed the industry’s current liminal state when it comes to pricing and technology.
You can watch the full session here.
The foundation: getting revenue management right
Before diving into AI’s role, the panel tackled a more fundamental question: why so many property managers still struggle with basic revenue management discipline.
AJ Brook’s advice for operators just starting out: Education first, automation second. “Information is free,” Brooks said. “Talk to property managers who are where you want to be. Learn really quickly that you need to automate, get a pricing tool, and understand market-specific factors — even things like how Taylor Swift affects your pricing.”
Even after setup and implementation work, the learning never stops. “I don’t feel comfortable yet,” Brooks said. “As soon as I started to think I got the hang of it, AI became important.”
The set and forget myth
Daniel Zammata tackled one of the industry’s most dangerous misconceptions: that dynamic pricing tools are a set-and-forget solution.
“We are not at the point where we can just set up a tool and trust the algorithm entirely,” Zammata said. His recommendation? Think user-guided strategy combined with algorithm automation. The technology does the heavy lifting, but human oversight remains essential.
Zammata also challenged focusing purely on occupancy. “Sometimes we measure ourselves thinking that success is just getting high levels of occupancy,” he said. “Really, revenue management has different dimensions. Success is more about predictable profit with owner satisfaction.”
Pricing as your last line of defense
“Your rate doesn’t matter if no one opens your listing,” Rakidzich said. “Everything you did to get to that point, your hero photo, the way you describe your listing, how you signal trust, the way you fill your photos with personality… all those factors cascade down to that final moment where somebody makes a decision.”
Rakidzich described the current market environment where guests are increasingly skeptical. They can spot properties that lack personality, and they’re looking for what he calls “perception of effort”, signals that the host actually cares.
Rakidzich urges revenue managers to think about their role starting long before they touch the pricing dial. “Your listing is one of four tabs open against three other competitors. Over thousands of impressions, guests have a price tolerance. You might get less conversion if you raise rates, but you won’t flatline to zero because you raised your rate ten dollars.”
The AI divide: Cautious optimism vs. healthy skepticism
Zammata sees a future where AI eventually handles everything, even the qualitative aspects of revenue management. “Right now AI is not capable of really reading your story, your brand meaning,” he said. “That’s going to take longer to develop. But eventually, we’re going to get there.”
Zammata also acknowledged the evolution in his own thinking. Today, set-and-forget is a misconception. But with generative AI advancing, that could change. Eventually, technology may do the work better than humans can.
Brooks landed somewhere in between, excited to test AI but believing it will always require human partnership. “AI has a partner, and it’s always human intelligence,” she said. “You can’t have one without the other in revenue management.”
Brooks is already experimenting with AI on properties she owns, viewing her role as mediating between technology and owners who need to build confidence in it. “It’s not life or death, it’s vacation,” she said. “You can make mistakes, adjust quickly, and undo them.”
“I would not go so far as to say that I hate AI, but I’ve got a big distrust for it,” Rakidzich said. His concern was that AI gives people just enough competence to be dangerous. “The more I know about a topic, the more I tend to disagree with AI,” he said. “It lacks nuance, depth of thought. It’ll give an unintelligent person 30% of a solution, but give them 100% confidence.”
His prediction was pointed: “Everybody’s going to use it and I’m going to whoop their ass because they’ll get halfway done with something and I’ll take it the rest of the way.”
Rakidzich illustrated the risk with a scenario: a property manager using AI for pricing who doesn’t understand the fundamentals. When a black swan event hits, they have no experience to fall back on. “The kid using it has no clue how price works,” he said, “and he ends up running negative on his rent roll with no idea how to solve his problem.”
His advice for the next three years is to use AI for research and data processing, but maintain human expertise for strategy. “I’d let it do something that would take me 40 hours, but I would still need real comprehension of what it’s doing. I don’t think I can trust it otherwise.”
What this means for property managers
The panel revealed a truth that’s both challenging and encouraging: there’s no single right answer yet.
If you’re just starting with revenue management:
- Educate yourself first (resources are everywhere)
- Implement a dynamic pricing tool, but don’t expect set-and-forget
- Plan to invest time in oversight and optimization
- Focus on predictable profit and owner satisfaction, not just occupancy
If you’re considering AI:
- Test cautiously on properties where you can afford to experiment
- Maintain a deep understanding of pricing fundamentals
- Use AI for data processing and research, not a blind strategy
- Remember that your competitive advantage may come from knowing AI’s limitations
Regardless of where you land:
- Understand that revenue management starts with your listing quality and guest trust
- Price comes after you’ve built trust and opened the tab
- The technology landscape will look dramatically different in the coming years
- Human oversight remains valuable for now
It’s natural that some operators today fully believe in AI’s value for revenue management, while others see no real value at all. After all, we’re in the messy middle of a genuine transformation, where healthy skepticism and bold experimentation can coexist. The right answer for your portfolio depends on your size, your market, your expertise, and your risk tolerance.
The winners won’t necessarily be the first to adopt AI or the last to resist it. They’ll be the operators who understand both the technology’s capabilities and its limitations, who know when to trust the algorithm and when to trust their experience.