The advent of computer-aided concepts and cognitive algorithms, along with fuzzy sets and fuzzy logic thoughts, supported the idea of ‘making computers think like people’ (Lotfi A. Zadeh, IEEE Spectrum, 21 (26–32), 1984). Such a school of thought enabled the sophistication of mission-oriented development of biomaterials and biosystems with the aid of ‘Artificial Intelligence’ (AI). Since polysaccharides (PSA) are medically safe and rely on stimuli-responsiveness, we herein highlight the importance of using AI-based algorithms in PSA-based biomedical engineering. Since manufacturing PSA-based biomaterials by AI experiences a very early stage of maturity, pattern recognition and behavior visualization by ‘Machine Learning’ (ML) models are not stressed herein. Nevertheless, exceptional chemical features of PSA such as surface modification and high adaptability facilitate ML-aided innovations. PSA-based biomaterials reveal diverse biomedical properties; therefore, summarizing, sorting, and recalling the best scenarios and optimization of the performance features of PSA still seems far from reach. We just highlight herein PSA-based biomedical engineering by the aid of AI to establish an agenda for the future. Herein, the outlook of targeted drug delivery vehicles, skin tissue engineering templates, wound healing systems, cancer treatment platforms, biosensors, personalized detection complexes, and particularly AI-aided bioprinting are generally covered.