At present, the employment of artificial intelligence has been greatly promising for several real-time applications. Recently, memristor has evolved as the most widely used electronic component for artificial synaptic applications. To further enhance the memristive controllability, this work proposes memristive synaptic updates through switch-free pulse width modulation-based memristive programming (SFPWMBMP), and switch-free pulse train-based memristive programming (SFPTBMP) techniques implemented through the aid of artificial intelligence (AI). The above programming is possible since the memristor facilitates simultaneous read and write operations, eliminating the need to switch between these two functions; thus, both write and read signals were superimposed and applied simultaneously. Interestingly, these techniques were employed in hotel management applications where a single memristor was engaged to follow the number of parcels ordered by a given customer. Furthermore, the proposed idea was extended to monitor all the customers through memristive crossbar architecture. Importantly, the circuits proposed in this work demonstrated a 49.57% improvement in circuit complexity and a 59.63% reduction in delay. Most importantly, employing AI was an easy process and resulted in an 88.8% reduction in code complexity.