Unrestricted global economic competition drives the increasing adoption of modern digital technologies, including AI, big data, machine learning, deep learning, IoT, and Blockchain. Digital technology as a whole is saving stakeholders across industries by solving difficult issues intelligently. AI, which is associated with intelligence and “smartness,” may be credited with being at the core of the digital era by infusing “mind” into data to find meaning. Despite their potential to improve performance, such systems present transparency and stakeholder participation difficulties for businesses across industries. In terms of development and competition, the sector faces strict overcapacity laws and limited oceanic data that affect its sustainability and efficiency. Most modern technology has not yet been integrated into fisheries research, which seems to contradict this assumption. AI and ML paired with big data systems have transformed natural language processing, computer vision, and signal processing. Even though fishing, conservation, and resource management need novel solutions, the technologies are still being developed. This study discusses how machine learning and AI, paired with large-scale, multidimensional datasets, might change fisheries research. This kind of analysis and modeling of complicated realities helps researchers to understand and reduce data difficulties with the analytical challenge. We demonstrate how these technologies fill gaps, promote sustainability, and usher in a new age of fisheries scientific efficiency via practical applications and case studies.