How I used AI to cut a $1,310 stay to $460

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I recently booked two nights at an Omni hotel with my family. Priceline and HotelSlash both had lower rates than The Edit by Chase Travel, so on paper the choice looked obvious. I booked through The Edit anyway and paid about $460 after credits, versus roughly $1,060 on Priceline with no breakfast.

The hotel was also on Amex Fine Hotels + Resorts, some rates had possible Rakuten or Capital One Shopping cash back, and I had card credits to factor in. Instead of building the comparison myself, I dumped screenshots of every option into ChatGPT.

On ChatGPT’s advice, I booked through The Edit and used my $250 Sapphire Reserve credit for Edit stays. On the same booking, I used the separate $250 Sapphire Reserve credit for select Chase Travel hotels, which includes Omni. Then I submitted a price-match claim with Chase using the lower Priceline rate. That got me about $250 back, and I still kept the Edit benefits, including breakfast and a $100 property credit. Here’s how it shook out:

• Starting price: $1,310
• Minus the $250 select-hotels credit
• Minus the $250 Edit credit
• Minus a roughly $250 Chase price match
• Minus the $100 property credit
• Effective cost: $460

For comparison, the same stay through Fine Hotels + Resorts would have come to about $885 after my $300 Amex Platinum credit and this hotel’s $125 property credit.

A few caveats if you try this. The select-hotels credit runs through December 31st, 2026, and like the Edit credit, it requires a prepaid stay of at least two nights booked through Chase Travel. Chase’s price match isn’t available to every cardholder, and claims have to be filed within 24 hours of booking.

This is why I’d rather ask AI for the true net cost than ask, “Which hotel rate is cheapest?” The cheapest rate on the screen wasn’t the cheapest way to book, and once you add cash back, cancellation terms, and kids-eat-free policies, it gets hard to keep straight.

I told ChatGPT who was traveling, the ages of my kids, which credit cards and benefits I had, and what I realistically expected to spend at the hotel. Then I used a prompt like this:

Compare these hotel booking options and calculate the true net cost of each one. There are [NUMBER] adults and [NUMBER] children traveling, ages [AGES].

Use the screenshots I attached to compare room rates, taxes, mandatory fees, parking, cancellation terms, room categories, and included benefits. Check the hotel’s current prices for included perks like breakfast and parking, and look for family policies such as kids eating free.

I expect to spend about [AMOUNT] on [BREAKFAST / RESTAURANT / SPA / PARKING]. Value credits based on what I’ll realistically use, not face value. If I’d skip the spa anyway, a $100 spa credit isn’t worth $100.

Include my card statement credits, hotel credits, and expected cash back. Here are the card-linked offers on my accounts: [PASTE OFFERS].

Flag anything that can’t be stacked, including any discount, portal, or price match that could cancel out another benefit. Don’t assume an Edit or Fine Hotels + Resorts booking is the better deal just because it includes more perks.

Check whether any booking qualifies for a price match or best-rate guarantee, including which rates qualify, whether room type and cancellation terms must match, and the claim deadline.

For each option, show the booking price with taxes and fees, minus statement credits, minus credits I’ll realistically use, minus expected cash back, minus any confirmed price-match adjustment, to get my effective out-of-pocket cost. Rank the options from lowest to highest.

Separately list perks that matter but shouldn’t get a cash value, like upgrades, late checkout, and elite-night credit. End with a short “verify before booking” checklist of every assumption that depends on current terms.

This is one of the better uses I’ve found for AI in travel planning because the underlying task is mostly tedious comparison and arithmetic.

I’d still verify the important terms before booking, especially cancellation rules, cash-back exclusions, and price-match requirements. But having AI do the first pass makes a messy decision much easier to see.