A method for a computer system to perform quality-aware continuous learning for radiotherapy treatment planning, wherein the method comprises: obtaining an artificial intelligence, "Al", engine (320, 420, 720, 820) that is trained to perform a radiotherapy treatment planning task; and based on input data (330, 430, 730, 830) associated with a patient, performing the radiotherapy treatment planning task using the Al engine (320, 420, 720, 820) to generate output data (340, 440, 740, 841-844) associated with the patient; characterized by: obtaining modified output data (350, 450, 750, 850) that includes one or more modifications made by a treatment planner (355, 455, 755, 855) to the output data (340, 440, 740, 841-844); performing quality evaluation based on at least one of (a) first quality indicator data (361, 461, 761, 861) associated with the modified output data (350, 450, 750, 850), and (b) second quality indicator data (362, 462, 762, 862) associated with the treatment planner (355, 455, 755, 855); and in response to a decision to accept the modified output data (350, 450, 750, 850) based on the quality evaluation, generating a modified Al engine (390, 490, 790, 890) by re-training the Al engine (320, 420, 720, 820) based on the modified output data (350, 450, 750, 850). obtaining an artificial intelligence, "Al", engine (320, 420, 720, 820) that is trained to perform a radiotherapy treatment planning task; and based on input data (330, 430, 730, 830) associated with a patient, performing the radiotherapy treatment planning task using the Al engine (320, 420, 720, 820) to generate output data (340, 440, 740, 841-844) associated with the patient; characterized by: obtaining modified output data (350, 450, 750, 850) that includes one or more modifications made by a treatment planner (355, 455, 755, 855) to the output data (340, 440, 740, 841-844); performing quality evaluation based on at least one of (a) first quality indicator data (361, 461, 761, 861) associated with the modified output data (350, 450, 750, 850), and (b) second quality indicator data (362, 462, 762, 862) associated with the treatment planner (355, 455, 755, 855); and in response to a decision to accept the modified output data (350, 450, 750, 850) based on the quality evaluation, generating a modified Al engine (390, 490, 790, 890) by re-training the Al engine (320, 420, 720, 820) based on the modified output data (350, 450, 750, 850). obtaining modified output data (350, 450, 750, 850) that includes one or more modifications made by a treatment planner (355, 455, 755, 855) to the output data (340, 440, 740, 841-844); performing quality evaluation based on at least one of (a) first quality indicator data (361, 461, 761, 861) associated with the modified output data (350, 450, 750, 850), and (b) second quality indicator data (362, 462, 762, 862) associated with the treatment planner (355, 455, 755, 855); and in response to a decision to accept the modified output data (350, 450, 750, 850) based on the quality evaluation, generating a modified Al engine (390, 490, 790, 890) by re-training the Al engine (320, 420, 720, 820) based on the modified output data (350, 450, 750, 850).