The nuclear proliferation biomarker Ki67 plays potential prognostic and predictive roles in breast cancer treatment. However, lack of inter-pathologist consistency in Ki67 assessment limits the clinical use of Ki67. This paper reports a solution utilizing an artificial intelligence (AI)-empowered microscope to improve Ki67 scoring concordance. We developed an AI empowered microscope where the conventional microscope was equipped with AI algorithms and AI results were provided to pathologists in real time through augmented reality. We recruited 30 pathologists with various experience levels from 5 institutes to assess Ki67 label index on 100 Ki67 stained slides for invasive breast cancer patients. In the first round, pathologists conducted visual assessment on a conventional microscope; in the second round, they were assisted with reference cards; and in the third round, they were assisted with an AI-empowered microscope. Experienced pathologists had better reproducibility and accuracy (ICC = 0.864, mean error = 8.25%) than inexperienced pathologists (ICC = 0.807, mean error = 11.0%) in visual assessment. Moreover, with reference cards, inexperienced (ICC = 0.836, mean error = 10.7%) and experienced pathologists (ICC = 0.875, mean error = 7.56%) improved their reproducibility and accuracy. Finally, both experienced (ICC = 0.937, mean error = 4.36%) and inexperienced pathologists (ICC = 0.923, mean error = 4.71%) improved the reproducibility and accuracy significantly with the AI-empowered microscope. AI-empowered microscope allows seamless integration of the AI solution into the clinical workflow and helps pathologists to obtain a higher consistency and accuracy for the Ki67 assessment. This article is protected by copyright. All rights reserved.