The SMPTE ST 2110 suite of standards has revolutionized broadcast production by enabling IP-based transport of video, audio, and ancillary data, offering flexibility and high quality. However, challenges such as manual metadata tracking, static queue buffer management for high-bandwidth streams (e.g., 4K/8K), and errorprone device configurations persist, hindering operational efficiency. The integration of Artificial Intelligence (AI) and Machine Learning (ML) in media production, as outlined in SMPTE ER 1010:2023, presents opportunities to automate these processes. This paper proposes a novel multi-agent AI system to address these issues within ST 2110 infrastructures, leveraging recent advancements in AI coordination frameworks to enhance broadcast automation and compliance.