INTELLIGENT WORKFLOW AUTOMATION IN PRINT MEDIA MANAGEMENT - Rathod, Sunil Damodar; Harshini R; Suryavanshi, Jyotsna; Manhas, Rashmi; Sharma, Shreesha; Kulkarni, Haripriya H. (ShodhKosh: Journal of Visual and Performing Arts, 2026)
The print media is ever getting pressurized to produce output of high quality, customized output, shorter turn-around time, low operation cost and enhanced sustainability. The customary procedures of print media management, which are manualized in coordinating, fixed scheduling as well as fragmented data disclosures are progressively insufficient to the requirements. The given paper explores the implementation of intelligent workflow automation in the management of print media using the combination of artificial intelligence, machine learning, Internet of Things (IoT), and digital twin technologies. A perception-cognition-action-based paradigm is suggested to be the structured AI-driven workflow architecture to allow the adaptive data-driven orchestration between pre-press, printing, post-press, and distribution stages. Predictive quality control, dynamic scheduling, anomaly detection, and resource optimization are performed with the help of machine learning and decision-support models, whereas real-time physical-virtual synchronization and scenario-based planning is performed with the help of digital twins. The quantitative assessment indicates that there are great improvements in turnaround time, schedule compliance, machine use, quality rework, downtime, material waste, and energy usage. The findings reveal that intelligent workflow automation has multidimensional benefits of efficient operations, cost-saving, and sustainability, and maintains human controls by providing supervisory decision-support interfaces. The research paper finds that intelligent workflow automation is a strategic asset in the production workflow of contemporary print media organizations that aim to have resilient, efficient, and sustainable production systems.