Ceramic　art,　deeply　rooted　in　cultural　heritage,　has　long　been　regarded　as　a　symbol　of　craftsmanship　and　historical　significance,　often　commanding　substantial　prices　in　the　art　market.　However,　with　the　rise　of　artificial　intelligence　(AI)　and　its　ability　to　generate　art　that　closely　resembles　human　creations,　distinguishing　between　authentic　and　AI-generated　artworks　has　become　a　critical　challenge.　In　this　research　work,　deep　learning　base　models　including　the　proposed　convolutional　neural　networks　(CNNs)　and　pre-trained　models　are　applied　to　identify　ceramic　arts,　distinguishing　between　human　prepared　artefacts　and　AI-generated　content　(AIGC).　There　is　no　benchmark　data　set　available　to　distinguish　between　real　ceramic　and　AI-generated,　therefore,　the　dataset　has　been　prepared　having　two　classes:　authentic　ceramic　items　(real)　and　AI-generated.　The　results　obtained　the　highest　accuracy　of　98%　by　using　CNN　compared　to　pre-trained　models,　such　as　ResNet,　VGG　and　AlexNet　models.　This　study　may　help　to　identify　the　authenticity　of　digital　artefacts　in　the　digital　era.　©　2025　Inderscience　Enterprises　Ltd.