AI-powered cameras help QSRs catch service failures

Vision-enabled operations prevent small service issues from escalating into costly brand damage.

Customer service complaints are piling up in the quick-service restaurant (QSR) industry, according to Chatmeter’s 2024 QSR Reputation Ranking. Staff mistakes in reviews rose 6.9%, while complaints about bad staff attitudes jumped 21.8%.

Amidst tighter margins and labor shortages, even minor front-of-house issues can quickly spiral into reputational setbacks and lost sales, said Josh Rudder, Director of International Sales at Solink.

“If we look at what the QSRs are experiencing, it's a higher pressure to deliver sales while reducing labor costs, and so they're trying to do more with less,” he said.

To break the cycle, Rudder believes more QSRs are turning to “vision-enabled operations,” which use existing cameras and AI to identify and address operational breakdowns in real time.

“If you walk into any restaurant, you're going to see cameras everywhere, and typically those are just for loss prevention or for really an insurance policy,” he said. “But that information can really give us a lot, if AI, like Solink provides, can enable those cameras to bubble up the most important issues—tables not ready for customers, queues being abandoned, or things not happening according to policy.”

The system goes beyond basic surveillance. Solink’s vision-enabled operations integrate with other data sources such as point-of-sale systems. This allows the AI to automatically investigate anomalies—for example, a transaction void—by checking what’s happening with customers or staff on camera.

That means corporate teams can monitor trends like cleanliness, customer engagement, and hygiene across all locations—and act quickly when issues arise.

With QSRs under intense cost pressure, Rudder acknowledged that some operators might find adoption daunting. But rapid advances in AI and user-friendly design have significantly lowered barriers in the last year.

“There’s a lot of things out there. AI and language models are relatively new,” he said. “But we've seen a real quantum leap—not just the ability of the AI models, but also the ease of implementation.”