Marketers have spent years getting better at deciding who to message. AI should make us better at deciding who not to message.

That may sound counterintuitive in an industry obsessed with personalization. But the more a brand knows about a guest, the more selective it should become about when it earns the right to interrupt them. Consumers do not have an attention shortage because brands lack ways to reach them. They have an attention shortage because everyone can reach them all the time. Push notifications, texts, emails, promotions, app alerts and reminders are all competing for the same finite amount of attention. Knowing someone’s favorite menu item might make a message more relevant. It doesn’t automatically make that message worth receiving.

As AI takes on more of the decision-making inside loyalty programs, that distinction becomes critical.

We come at this from different sides of the industry. One of us has spent years building marketing strategies for enterprise restaurant brands. The other has built the technology and infrastructure those strategies depend on. We’ve both landed in roughly the same place: the real opportunity with AI is helping brands make better decisions about when to act, when to reward and when to leave the guest alone.

The smartest message might be no message at all

There’s an understandable instinct in marketing that if we know more about someone, we should do more with that information.

They visited three times this month? Send something.

They usually order on Fridays? Send something.

They redeemed a reward? Send something.

But if a guest is already doing exactly what you want them to do, constantly finding another reason to interrupt them starts to feel less like personalization and more like pressure.

The financial stakes make that restraint especially important. DoorDash’s 2026 Restaurant Industry Trends Report found that repeat diners spend 27% more per transaction than first-time, anonymous guests. PAR’s 2026 QSR Operational Index also found that registered loyalty members outspent anonymous guests for the first time. These are valuable guests. Brands should be especially thoughtful about how often they ask for their attention.

A generic offer with no connection to a guest’s actual behavior still feels generic, no matter how sophisticated the targeting behind it. And guests are already telling us they want something more meaningful. Seventy percent of consumers favor tiered loyalty programs over one-size-fits-all approaches. They want their relationship with a brand to reflect how they actually engage with it.

Sometimes the best response to a loyal guest is simply to treat them like one. Give them faster progress, access, status, an unexpected perk, or an experience that actually reflects the relationship they’ve built with the brand. And sometimes the right response is nothing.

Suppression is just as valuable as targeting. Not enough marketers think about it that way yet.

Consumers want the benefit of AI. They don’t need to experience AI.

Marketers are dramatically overestimating how much consumers want to experience AI. What they care about is how AI makes their experience with your brand better.

In PAR’s consumer research, we asked 1,000 U.S. adults how they would feel about a restaurant predicting their usual order. Only 24% said they would be excited. Another 27% were neutral, 27% liked the idea but worried about accuracy, and more than one in five said they would avoid a restaurant that tried it. That should give marketers some pause.

Consumers aren’t necessarily waiting for restaurants to show them more AI features. They want the experience to get better because the technology exists. Trust matters here, too. In the same research, 43% ranked transparency about how AI is used as their top trust factor, nearly three times any other consideration. And when we asked what would actually improve their loyalty experience, smarter rewards based on visit frequency was one of the top responses.

The signal is pretty clear. Guests aren’t asking brands to hide the technology. They’re asking brands not to make the technology the point of the interaction.

Be transparent about how data is being used. Then let the experience speak for itself.

The guest doesn’t need to know how many signals were evaluated before a reward appeared. They care that the reward makes sense, arrives at the right moment and feels connected to what they actually did.

Personalization should be a filter, not a megaphone

For years, the industry has treated personalization primarily as a content problem. The better we know you, the more specifically we can tailor the message. That thinking needs to expand.

The better we know someone, the better we should become at deciding whether there should be a message at all. Imagine one guest has already visited twice this week and redeemed a reward yesterday. Another hasn’t visited in six weeks. A third is one visit away from reaching a new loyalty tier. Those are three completely different moments in three completely different relationships.

Yet when the restaurant engagement platform responsible for messaging, transactions, loyalty, promotions and operations cannot read those signals together, all three guests can easily end up on the same campaign calendar. Tuesday is still double points. Thursday is still the promotional push. August still needs a campaign. The calendar wins because the context never made it into the decision.

This is where an agentic approach to loyalty gets interesting.

A system that can understand guest behavior alongside transaction history, promotional timing and operational signals can make a much better decision about what should happen next. That decision could be to send a message, offer a reward, wait until a better moment or do nothing at all.

AI gives brands the ability to evaluate more context than a marketer could reasonably process manually across millions of guests. The value comes from using that context to exercise better judgment at scale.

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

The reward should make sense without an explanation

You can see this same principle in how consumers respond to rewards. In PAR’s consumer research, 52% of consumers said they would trust a loyalty program more if it delivered immediate perks tied to their actual spending, such as a surprise free item after a larger order.

We love this example because the guest doesn’t need a lesson in how the system works. They did something. The brand recognized it. The reward showed up. The connection between behavior and benefit is obvious.

Compare that with a generic promotion arriving three days later because it happened to be scheduled for Thursday. One reflects what the guest just did. The other reflects the marketing calendar.

Doing this consistently across every location, daypart and guest segment requires more than a team manually building campaign rules for every possible scenario. The systems making those decisions need enough context to understand the moment.

And those moments add up. Guests actively manage no more than a handful of loyalty programs. Every interaction is making a case for why your program deserves to remain one of them. Sometimes that case is made by sending the perfect message. Sometimes it’s an unexpected reward at exactly the right moment. And sometimes it’s having enough context to know the guest doesn’t need anything from you right now.

AI should make loyalty feel less like marketing

Every major technology shift creates a temptation to start with what the technology can do. We think the more useful question is: What should the guest experience feel like when the technology is working?

It should feel like the brand pays attention.

The reward makes sense. The timing makes sense. The message is useful when it arrives. The program recognizes the relationship instead of treating every member like another name on a campaign list.

That level of consistency requires connected signals and systems capable of acting on them together. It requires understanding enough about the guest and the business to make the right decision in the moment, including when the right decision is to wait. That is where we see the real promise of an agentic approach to loyalty. Better context. Better judgment. More restraint.

The best loyalty AI may ultimately be the AI guests barely notice, because all they experience is a brand that seems to get it right.

About the Authors:

About Diane Le

Diane Le is VP of Marketing, Restaurants, at PAR Technology Corporation, where she leads marketing for PAR’s restaurant technology portfolio, including PAR Punchh.

About Olga Lopategui

Olga Berkovich Lopategui is a leading expert in restaurant loyalty and rewards programs. After a 15-year career in various marketing roles at global giants like Pizza Hut, KFC, and TGI Fridays, Olga founded Restaurant Loyalty Specialists (RLS). Her boutique consulting firm helps restaurant chains, ranging from 20 to over 800 locations, build high-impact loyalty programs.

About PAR Technology Corporation

PAR Technology Corporation (NYSE: PAR) is the agentic OS for multi-unit operators, helping restaurant, retail, and high-volume commerce brands drive better performance across every location.

About Restaurant Loyalty Specialists (RLS)

RLS provides strategic solutions for restaurants using any loyalty platform, such as Salesforce, Session M, Cheetah Digital, Epsilon, and more. exclusively on the platforms targeted for the restaurant industry: Punchh, Paytronix, Personica (Fishbowl).

Marketing Technology News: How MarTech Is Enabling Autonomous Brand Engagement Across Channels?