Introduction　Inadequate　primary　care　infrastructure　and　training　in　China　and　misconceptions　about　aging　lead　to　high　mis-/under-diagnoses　and　serious　time　delays　for　dementia　patients,　imposing　significant　burdens　on　family　members　and　medical　carers.Main　body　A　flowchart　integrating　rural　and　urban　areas　of　China　dementia　care　pathway　is　proposed,　especially　spotting　the　obstacles　of　mis/under-diagnoses　and　time　delays　that　can　be　alleviated　by　data-driven　computational　strategies.　Artificial　intelligence　(AI)　and　machine　learning　models　built　on　dementia　data　are　succinctly　reviewed　in　terms　of　the　roadmap　of　dementia　care　from　home,　community　to　hospital　settings.　Challenges　and　corresponding　recommendations　to　clinical　transformation　are　then　reported　from　the　viewpoint　of　diverse　dementia　data　integrity　and　accessibility,　as　well　as　models＇　interpretability,　reliability,　and　transparency.Discussion　Dementia　cohort　study　along　with　developing　a　center-crossed　dementia　data　platform　in　China　should　be　strongly　encouraged,　also　data　should　be　publicly　accessible　where　appropriate.　Only　be　doing　so　can　the　challenges　be　overcome　and　can　AI-enabled　dementia　research　be　enhanced,　leading　to　an　optimized　pathway　of　dementia　care　in　China.　Future　policy-guided　cooperation　between　researchers　and　multi-stakeholders　are　urgently　called　for　dementia　4E　(early-screening,　early-assessment,　early-diagnosis,　and　early-intervention).