Five ways AI is growing revenue for property managers
- May 2
- 8 min read
Christopher Dillon of Guesty is blunt about where the AI conversation has now moved in short-term rental property management: "AI is obviously very much here. The real difference now is how you're using it – because some property managers are only saving time, and others are actually growing revenue."
In this Host Planet Bitesize episode – powered by Hostfully – Christopher walks through five practical, revenue-generating ways property managers can put AI to work in 2026, and the one prerequisite that determines whether any of them will actually land.
The prerequisite: the right system underneath the AI
Christopher's opening caveat is the one most AI conversations skip: the tools only compound value if the underlying system can feed them. That means a connected PMS, clean property and availability data, and access to guest communications. Without that, AI is a demo, not an operating layer.
It also means making a deliberate choice about how much autonomy to give the AI. As Christopher puts it later in the conversation, "you really need to understand if the AI is only suggesting replies, or if it has the ability to become an autopilot as well. You need a system where you can choose what level of autopilot you want and which kinds of guest communications you want it to act on."
That distinction – suggestion-mode versus autopilot-mode – runs through all five of the revenue plays that follow.
Tip one: automated accommodation upgrades
The first tip is one most property managers have heard about in theory but rarely automate in practice. When a guest books a smaller unit, the AI can automatically surface a larger one – at a higher nightly rate – before the booking is finalised or shortly after confirmation.
"Your AI can offer guests an upgrade. One of your guests has booked one of your smaller apartments – the AI can send an automation straight to that guest saying, 'Why don't you book this property? It's going to be maybe £30 or £40 more per night.' Even if a small percentage of guests actually book that, your revenue starts to increase with every one."
The power of this play is that it is portfolio-wide and fully hands-off once configured. On any individual booking the uplift is modest – £30 here, £40 there. Across a portfolio of 50 or 100 properties over a full year, the compounding effect is material. And because the AI is sitting on live availability data, the offer is only ever made when there is a larger property available – so the guest never sees a broken or irrelevant suggestion.
Tip two: personalised guest journeys that drive loyalty
Christopher's second play is the one most hosts already associate with AI – but with a subtle reframe.
"AI can automate and personalise the entire guest journey: sending check-in details at the right time, responding instantly to questions, flagging issues mid-stay before they become complaints. The result is a better experience for your guests, more repeat bookings, and stronger long-term revenue."
The reframe is the word personalised. Pre-scripted automations have existed for years. What AI adds is the ability to respond to what the guest actually says, in real time, at any hour – and to escalate intelligently when a situation genuinely needs a human.
"If a guest raises something about the apartment – something's broken – the AI can respond no matter what time of night it is, create a task for you, send the maintenance person over straight away, or flag it to you."
This is where the loyalty effect kicks in. A guest who raises a broken shower at 11pm and gets a coherent, caring response within two minutes remembers that stay differently from a guest who waits until morning for a reply. Over a year, the compounding effect on repeat bookings and organic referrals is hard to model but very real.
Tip three: increasing revenue per booking
If tip two is about retention, tip three is about revenue density – getting more out of each reservation you already have.
"The real margin now is how much extra revenue you can generate from the actual bookings themselves. Maximising every reservation, not just getting more of them."
Christopher's examples are concrete. Dynamic pricing adjustments on high-demand dates. Offered add-ons at the moment a guest is most likely to say yes. Early check-ins as a paid upgrade. Late check-outs offered proactively to family bookings, where the AI already knows that getting small kids out of the door by 10am is a pain point.
"If your AI knows that's a family booking with a lot of kids, it can send a nice personalised message saying, 'Would you like to have a late check-out? We can offer these times – an extra £20.' If you're putting these messages in front of guests at the right time, before they even ask, the likelihood is they'll take it up."
That's the magic of the play: the guest often welcomes the offer because it solves a problem they were about to raise anyway. The booking that would have paid £400 ends up paying £450 or £550 – with no additional effort from the property manager once the automation is set up.
Tip four: improving OTA visibility
The fourth revenue play is the one most hosts under-invest in: using AI to keep listings actively optimised across the major OTAs.
"OTAs respond to how often you're changing things, how often you're updating your listings. The right AI can continuously optimise pricing, response times, even listing content. The AI can run through your system and suggest edits."
Christopher's framing is again flexible. New users can operate in suggestion mode – the AI surfaces recommendations ("these five properties aren't bookable on these nights – if you change your minimum-stay rule, you'll unlock additional bookings") and the property manager decides what to accept. More experienced users can let the AI act directly.
The core mechanic is the same either way: OTAs reward activity. Listings that update their titles, descriptions, pricing, and response time metrics consistently climb the rankings. Listings that go dormant slide. AI is the easiest way to ensure that optimisation happens daily rather than quarterly.
For hosts who aren't natural copywriters, Christopher adds a practical supplementary tip: use a general purpose LLM (ChatGPT, Claude, Gemini) as a copywriting partner. Paste your current listing in and ask for an SEO-optimised title and description. Layer in better photography on top of that – because, as Christopher and James agree in the episode, photography is still the single biggest lever on OTA conversion.
Tip five: generating more – and more recent – five-star reviews
The final play is the one every host knows matters, but few systematise.
"AI tools can identify happy guests and prompt them to leave a review – quicker than you can do it manually, and at the right moment. It's different from automated messages, it's about sentiment. The AI can generate a message like, 'Our first day wasn't a great experience, but we solved the problem. I hope everything went really well after that. Thanks so much for staying' – and it gets sent automatically at the right moment for each guest."
Two things make this play different from a generic "ask for a review" automation. First, sentiment – the AI reads the stay in context and calibrates the tone, including when something went wrong and was resolved. Second, timing – the AI understands when a specific guest is most likely to respond, rather than firing a one-size-fits-all message at checkout.
The recency angle is worth underlining. Modern OTA ranking algorithms weight recent five-star reviews far more heavily than older ones. A property with 10 five-star reviews from the last 90 days will outrank a property with 50 five-star reviews from three years ago. Generating a steady drumbeat of recent reviews isn't optional – it's table stakes for visibility.
Autopilot versus suggestion mode: the real decision
Running through all five tips is a single strategic decision every property manager now has to make: how much autonomy do you give the AI, and where?
Christopher's guidance is measured. Start in suggestion mode. Review what the AI recommends. As your confidence grows – and, importantly, as the AI accumulates context on your properties, your guests, and your brand voice – move more functions to autopilot.
The functions that lend themselves most easily to full autopilot are the simple, repeatable ones: Wi-Fi code requests, check-in instructions, upsell offers against clear inventory rules. The functions that warrant human review for longer are the complex and reputational ones: responding to serious complaints, handling refund requests, managing disputes.
The trap to avoid, Christopher implies, is the all-or-nothing one: either rejecting AI because you don't trust it on the hard cases, or handing it everything and being surprised when it gets something wrong. The right answer is a layered permission system – and a PMS that supports it.
Frequently asked questions about how AI is growing revenue for property managers
How is AI growing revenue for property managers? Christopher Dillon from Guesty identifies five primary revenue levers: automated accommodation upgrades, personalised guest communications that drive loyalty, revenue-per-booking uplift through add-ons and early/late check-in offers, continuous OTA listing optimisation, and targeted prompts for recent five-star reviews.
What is the difference between AI in suggestion mode and AI in autopilot mode? Suggestion mode means the AI proposes actions (edits, messages, pricing changes) and a human reviews and approves each one. Autopilot mode means the AI executes directly within defined rules. A mature PMS lets property managers configure this per function.
Can AI really increase revenue per booking on Airbnb or Vrbo? Yes. By detecting booking patterns – for example, a family booking with children likely to want a late check-out – AI can surface personalised paid upgrades at the right moment. Even modest uptake on £20-£50 add-ons compounds meaningfully across a multi-property portfolio.
Why do OTAs reward property managers who use AI optimisation tools? OTAs such as Airbnb and Booking.com favour listings that are actively maintained – consistent pricing updates, fast response times, up-to-date content. AI makes continuous optimisation feasible where manual effort would be prohibitive.
How does AI help generate five-star reviews? AI can identify guests who had a positive experience, calibrate the tone of the review request based on what happened during the stay, and send the prompt at the optimal moment – often a few hours after check-out, when the positive impression is freshest.
What is the minimum infrastructure needed before AI tools can start generating revenue? A connected property management system, clean property and availability data, integrated OTA listings, and approved access for the AI to communicate with guests and make the changes (or suggestions) you authorise.
The bottom line
Christopher Dillon's takeaway sits in a single line from the conversation: "AI isn't just a toy anymore – it's becoming the engine behind revenue growth in property management."
The shift he's describing is from AI as a time-saver (handling the wifi-code question) to AI as a revenue-grower (handling the upgrade offer, the late-check-out upsell, the mid-stay escalation, the review request). The five plays above are the practical manifestation of that shift – none of them require exotic technology, all of them require a PMS that can support them, and each of them compounds meaningfully across a portfolio over a year.
For property managers still treating AI as a 10% efficiency gain, the message is to reframe. The margin is no longer in cutting the cost per booking. It is in lifting the revenue per booking. AI is the lever.
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