Based on their construction or working principles, biosensors, biomimetic sensors, and bioapplicable sensors may have been understood differently, but everyone acknowledges their commonality of sensing in fields that require knowledge of biochemical science and engineering. In the era of big data and industry 4.0, the amalgamation of artificial intelligence (AI) technology and the Internet of Things (IoT) with the applied science of sensing is seen as a way forward to achieve unprecedented growth in the design and development of novel and robust biochemistry-related sensors. The integration of AI with sensing technology makes it possible to produce sensors that can rapidly detect targets while maintaining high sensitivity, accuracy, and precision, all at a cost-effective price point. This work reviews recent literature on the applications of AI tools to accelerate the advancement of intelligent biosensors. Also, it projects how novel AI tools such as digital twins, machine vision, robotics, natural language processing, and text mining will transform the design and broaden the applicability of biosensors, bio-inspired sensors, and bioapplicable sensors.