Thin films of perovskite titanates can be composition-tailored to exhibit ferroelectric, pyroelectric, or piezoelectric properties, in varying degree of combinations, and thereby modulating their response when illuminated with light. This paper reviews the potential applications of photoresponse from lead zirconate titanate thin films. In ferroelectric materials, such as lead zirconate titanate (PZT), for example, the photoresponse shows a clear dependence on remanent polarization. The main highlight of the paper is a review of the concept of optically addressed ferroelectric memory and identification of its high impact applications. Incidence of energetic laser beam pulses gives rise to two different classes of phenomena: first, a thermally triggered piezoelectric/pyroelectric response and second, an optoelectronic response. Optimizing the device geometry and selecting the illumination characteristics, one can easily control the dominating mechanism in a device. The optoelectronic effect emerges at a relatively lower incident beam power (≤2 mW/μm2) and can be as fast as the duration of the pulse (≤10ns), and therefore, is directly relevant as a non-destructive read-out signal from optically addressed ferroelectric memory. The optical NDRO signal offers itself as a unique tool that allows a non-destructive ‘probe’ for the capacitor, without causing any polarization switching in it, the characteristic artifact of the electrical destructive readout (DRO) measurement technique. Furthermore, the polarization dependent photoresponse could also be exploited as a non-destructive evaluation tool for mapping the domains in ferroelectric films, to generate fundamental understanding of the domain dynamics (generation, growth, movement, etc., under applied field, illumination, and/or temperature) in such thin films. In addition, with a high fidelity analog nature of the remanent polarization, the highly parallel, high speed photoresponse output from such optically addressed memories may be ideally suited for high performance computing applications especially involving image processing, high speed communication and parallel processing with architectures, such as large scale artificial neural networks.