Can AI run revenue management for short-term rentals? Beyond CEO Julie Brinkman on the future of STR pricing

Dynamic pricing used to be a tool. Now it's a full revenue management system – and, in some cases, AI is starting to run it.

But how far can you really go? Can you hand your entire pricing strategy to an AI agent and walk away? And if only 15–20% of the world uses dynamic pricing at all, what's holding everyone else back?

On the Host Planet Podcast, powered by Lodgify, James Varley sat down with Julie Brinkman, CEO of Beyond, to answer exactly those questions. What follows are the key takeaways for short-term rental hosts and property managers who want to price smarter, scale faster, and understand what AI can – and can't – do for their business.

Catch the full episode  on YouTube, Spotify, or Apple Podcasts to discover everything you need to know about AI revenue management for short-term rentals.

Beyond Pricing: Why revenue management is more than a nightly rate

Beyond pioneered dynamic pricing in short-term rentals back in 2013. But Julie is quick to point out that pricing, while still the "nexus" of the platform's value, is only one variable in running a successful rental business.

"Price is just one of the variables that go into running a successful rental management business," she explains. Over the past six-and-a-half years, Beyond has pushed itself to think – pun intended – beyond pricing: giving operators fast access to market and competitor data, insight into how their listings are actually viewed by guests, and the ability to execute revenue strategy at scale across thousands of listings.

That last point matters more than ever. As hosts grow rapidly and attract institutional money, what used to be a manual, labour-intensive process now has to be automated, scalable, and intuitive.

Can you actually outsource revenue management to AI?

The short answer, according to Julie: yes.

You can already take action through AI agents – Claude, ChatGPT, Gemini – connected to Beyond through its MCP (Model Context Protocol) server. Think of MCP as an interface: a way to use the AI agent you already know, on your phone or desktop, to access Beyond's data, insights, and recommendations, and even connect them to other tools like your Gmail.

But Beyond is deliberately cautious about how much control it hands over. Rather than letting autonomous agents loose on your account, it's surfacing read-only information first.

"This does actually separate us from some others in the industry," Julie says. "We want to make sure there's guardrails. We want to make sure there's traceability. We want to make sure that there's a big fat undo button."

Her reasoning is simple and human: everyone makes typos. Now imagine an autonomous agent making an uncorrected mistake on the most important part of your business – your pricing. The safeguards exist so operators always know what's happening, have protections in place, and can unwind anything a "rogue agent" might do.

Why AI alone can't set your prices (yet)

Could you just drop your calendar into ChatGPT and ask it to generate 365 days of prices?

Beyond tried exactly that. Claude, GPT, and Gemini all responded the same way: they can generate prices, but they'll caveat it heavily and flag things you should think about. The functionality to run true revenue management doesn't exist inside those general AI tools – and they aren't pushing to own the category.

The magic, Julie argues, happens when you pair a general AI agent with a purpose-built revenue management agent inside Beyond. That's when you can synthesise data, tell stories, spot anomalies, and get out of the mundane daily grind – turning AI into a genuine partner rather than a checklist.

There's a crucial warning, though. Large language models "really want to please you," Julie cautions. Their answers can sound plausible while being wrong. Copy-paste an AI response to an owner and you risk sending something inaccurate.

"It's like a Formula 1 car," she says, "but you're in the passenger seat. You've just got to be careful."

Beyond has spent over a year training its internal revenue management agent – precisely because getting to the right answer, not just a plausible one, takes constant work. Her advice to hosts: if you're sold an "AI is everything" solution, interrogate how the company validates, trains, and iterates on its results.

Only 15–20% of hosts use dynamic pricing – here's why

One of the most striking data points from the conversation: based on Beyond's view of millions of listings worldwide, only around 15–20% of the market uses any form of dynamic pricing. Roughly 30% use static pricing – changing rates just once or twice a year – and the rest use seasonal pricing, adjusting perhaps 10–12 times annually.

So why do so few hosts adopt dynamic pricing? Julie points to three reasons:

1. Hard-won intuition. The industry was built by brave entrepreneurs who know their markets and guests intimately. That instinct is well-earned – but it's not the whole picture. The magic happens when local expertise is married with data and emerging market trends, especially as the traveller and owner landscape shifts across generations.

2. Lack of awareness. Many hosts simply don't realise better options exist – particularly those running one or two listings alongside other jobs.

3. A misunderstanding of what dynamic pricing is. Especially in Europe, dynamic pricing gets wrongly equated with surge pricing.

"Dynamic pricing isn't surge pricing. It's not Uber. It's not just going to cost more," Julie explains. It matches supply with demand – which means dropping prices when demand is soft, not just raising them. Educating the market that it's genuinely dynamic, in both directions, is key to wider adoption.

What the revenue manager's job looks like in a year

Julie's vision for the near future centres on scale and connection.

Today, the best revenue managers handle around 300 listings each. She believes tooling and automation can push that by an order of magnitude or two – towards one manager for 3,000 listings. The path there runs through anomaly detection, precision, and recommendations that build trust over time.

"You build trust with recommendations, and then you can lean into automation," she says. "Once you have that trust, I can now deputise you, agent, to make these decisions – because I know you're going to make the right decisions."

She also sees revenue management breaking out of its silo. In large property management companies, owner acquisition, owner relations, and marketing all depend on revenue management delivering on its promises – yet they rarely work from the same data. Julie predicts far more collaboration between these teams, which means a bigger, more strategic role for revenue managers.

"Instead of coming in, opening my laptop and doing the same 10 things every day – my job has grown, my impact has grown, my skill set has expanded."

How to adopt AI safely: The trust-first path

For operators nervous about handing control to autonomous agents, Julie validates the concern – and lays out a sensible path.

It starts with trust in your data: understanding where it comes from, how it's cleaned, how markets and amenities are clustered. From there, you use data to inform human decisions. Then you begin listening to AI recommendations, giving each one a simple thumbs up or thumbs down. Only once trust is established do you move toward automation – starting with high-effort, low-value tasks before working up the value chain.

"It isn't an overnight switch," she stresses. Agents are "just a combination of skills," and those skills require teaching, tweaking, and iteration – much like training a person.

The advice for new hosts: Don't rely on the channels

Julie's parting advice for hosts just getting started is clear: don't centralise everything into the booking channels.

"The channels have a weird incentive to drive bookings versus making you more money," she notes. Dynamic pricing and revenue management are core technologies worth outsourcing to specialists outside the OTAs.

And where is Beyond headed? Back to where the conversation began: there's far more to revenue than the rental rate. Owner acquisition, owner retention, owner management, marketing automation, profit orchestration – Beyond intends to help operators visualise and automate all of it.

The reason comes down to a truth many hosts overlook: an owner's lifetime value is significantly higher than a guest's. Yet most technology focuses on guest acquisition. For property managers, retaining owners is what determines the longevity – and ultimately the sale value – of the business.

Key takeaways on AI revenue management for short-term rentals for hosts and property managers

• Yes, you can outsource revenue management to AI – but the smartest platforms build in guardrails, traceability, and an "undo button" before letting agents act autonomously.

• General AI tools can't run your pricing alone. They produce plausible-sounding answers that may be inaccurate. The value comes from pairing them with a purpose-built, well-trained revenue management agent.

• Only 15–20% of hosts use dynamic pricing – mostly due to over-reliance on intuition, lack of awareness, and confusing it with surge pricing. It works both ways: it drops prices in soft demand, too.

• Adopt AI trust-first: data → recommendations → automation. Never flip the switch overnight.

• Don't rely on the booking channels for pricing – their incentives don't fully align with your profit.

• Owner lifetime value beats guest lifetime value. The future of revenue management is about acquiring and keeping owners, not just optimising the nightly rate.

  
  

This article is based on Julie Brinkman's conversation with James Varley on the Host Planet Podcast, powered by Lodgify. Listen to the full conversation for the complete discussion on AI, dynamic pricing, and the future of short-term rental revenue management. Catch the full episode on YouTube, Spotify, or Apple Podcasts.

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