Objectives:　Diabetes　remains　a　major　global　health　challenge　in　China.　Artificial　intelligence　(AI)　has　demonstrated　considerable　potential　in　improving　diabetes　management.　This　study　aimed　to　assess　healthcare　providers’　perceptions　regarding　AI　in　diabetes　care　across　China.　Methods:　A　cross-sectional　survey　was　conducted　using　snowball　sampling　from　November　12　to　November　24,　2024.　We　selected　514　physicians　and　nurses　by　a　snowball　sampling　method　from　healthcare　providers　across　30　cities　or　provinces　in　China.　The　self-developed　questionnaire　comprised　five　sections　with　19　questions　assessing　medical　workers’　demographic　characteristics,　AI-related　experience　and　interest,　awareness,　attitudes,　and　concerns　regarding　AI　in　diabetes　care.　Statistical　analysis　was　performed　using　t-test,　analysis　of　variance　(ANOVA),　and　linear　regression.　Results:　Among　them,　20.0　%　and　48.1　%　of　respondents　had　participated　in　AI-related　research　and　training,　while　85.4　%　expressed　moderate　to　high　interest　in　AI　training　for　diabetes　care.　Most　respondents　reported　partial　awareness　of　AI　in　diabetes　care,　and　only　12.6　%　exhibited　a　comprehensive　or　substantial　understanding.　Attitudes　toward　AI　in　diabetes　care　were　generally　positive,　with　a　mean　score　of　24.50　±　3.38.　Nurses　demonstrated　significantly　higher　scores　than　physicians　(P　＜　0.05).　Greater　awareness,　prior　AI　training　experience,　and　higher　interest　in　AI　training　in　diabetes　care　were　strongly　associated　with　more　positive　attitudes　(P　＜　0.05).　Key　concerns　regarding　AI　included　trust　issues　from　AI-clinician　inconsistencies　(77.2　%),　increased　workload　and　clinical　workflow　disruptions　(63.4　%),　and　incomplete　legal　and　regulatory　frameworks　(60.3　%).　Only　34.2　%　of　respondents　expressed　concerns　about　job　displacement,　indicating　general　confidence　in　their　professional　roles.　Conclusions:　While　Chinese　healthcare　providers　show　moderate　awareness　of　AI　in　diabetes　care,　their　attitudes　are　generally　positive,　and　they　are　considerably　interested　in　future　training.　Tailored,　role-specific　AI　training　is　essential　for　equitable　and　effective　integration　into　clinical　practice.　Additionally,　transparent,　reliable,　ethical　AI　models　must　be　prioritized　to　alleviate　practitioners’　concerns.　©　2025　The　Authors