The odds are stacked against pets that go missing. It happens to roughly 10 million each year in the U.S., according to the Animal Humane Society—about one in every three pets over a lifetime. For many, the trail goes cold. The likelihood of a reunion hovers below a quarter, leaving millions of families suspended between hope and dread.
In the worst cases, the outcome is far more final. Animals that are never identified or reclaimed can end up in the nation’s overburdened shelter system, where capacity constraints force difficult decisions. According to the American Society for the Prevention of Cruelty to Animals, about 5.8 million dogs and cats entered shelters in 2024. While 4.2 million were adopted and more than 900,000 were returned to their owners, roughly 607,000 were euthanized. The numbers have improved in recent years, but the gap between loss and reunion remains wide.
Into that gap, AI is increasingly making a difference.
At the center of the shift is Petco Love Lost, a national database that uses AI-powered image recognition to match lost and found pets. Since 2021, the platform has helped reunite more than 200,000 animals with their families. Roughly 3,000 shelters across the country now feed into the system, creating a network effect that grows stronger with every upload.
A pet owner uploads a photo of a missing animal. On the other end, shelters and anyone who finds a wandering pet can snap a photo of the animal and submit it to Petco Love Lost. The system scans for visual matches across its database, comparing features such as fur patterns, facial structure, and markings.
Historically, searching for a lost pet meant flyers stapled to telephone poles, calls to local shelters, and posts in fragmented online groups. Each effort existed in isolation. AI, by contrast, aggregates and cross-references those efforts in real time. The result is a shift from passive hope to active detection.
A dog named Ziggy disappeared while traveling with his owner more than 300 miles from home. For months, there were no leads. But after his owner uploaded a photo to Petco Love Lost, the system began generating potential matches from shelters across the region. Five months later, one of those matches proved correct. Ziggy had been found and taken to a shelter far from where he vanished. Ziggy’s close-cropped curly white coat had grown out quite a bit during the dog’s odyssey, to the point that he looked more like a ball of dingy yarn.
A quicker reunion was had by Banger, who ran off after being startled. His owner launched a frantic search that included flyers and a reward. It was a neighbor who made the connection—uploading a photo to Petco Love Lost after taking the dog in. The system bridged the gap between them. The next day, Banger was home.
The technology is not limited to databases. It is also being embedded into neighborhoods.
Ring, the doorbell camera company owned by Amazon, has introduced an AI-powered feature called Search Party that turns home security cameras into a distributed search network. When a user reports a missing dog, nearby cameras begin scanning for animals that match its appearance. If a potential match is detected, the camera owner receives an alert and can choose whether to share the footage.
“Pets are family, but every year, 10 million go missing, and the way we look for them hasn’t changed in years—until now,” said Jamie Siminoff, Ring’s founder and chief inventor. “One post of a dog’s photo and the Ring app starts the outdoor camera search looking for a match.”
Since its launch, the feature has helped reunite more than one dog per day with its owner. One user in Kansas was reunited with her dog just 15 minutes after a neighbor’s camera captured footage and shared it through the app.
“Before Search Party, the best you could do was drive up and down the neighborhood, shouting your dog’s name,” Siminoff said. “Now, pet owners can mobilize the whole community—and communities are empowered to help—to find lost pets more effectively than ever before.”
The underlying concept is similar to Petco Love Lost, but the data source is different. Instead of relying on user-submitted photos alone, Ring taps into a continuous stream of real-world video.
Together, these systems represent a broader evolution in how AI is applied as a force multiplier. Even the most advanced tools cannot replace safeguards like ID tags and microchips. Experts emphasize that microchipping remains one of the most reliable ways to identify a pet once it enters a shelter or veterinary system.
Another technology, drones, is also being applied to help find lost pets. Drones equipped with thermal imaging cameras, for example, are being used in certain cases to locate animals in hard-to-access terrain. These systems can detect heat signatures and cover large areas quickly, though their effectiveness varies depending on conditions such as weather, vegetation and the animal’s behavior.
