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This paper presents a watermarking assessment in the context of the emerging JPEG Trust Part 3: Media Asset Watermarking (ISO/IEC 21617-3). The specification complements the JPEG Trust family of standards by enabling a robust content–metadata binding through watermarking, while remaining algorithm-agnostic via explicit signalling of watermark presence, identification of the embedding/extraction technique, and references to external repositories that store Trust Records. It further describes a recommended payload structure and a benchmarking methodology covering imperceptibility and robustness, including modern attacks such as advanced compression (e.g., JPEG XL, JPEG AI) and AI-driven object manipulation. Four state-of-the-art methods from industry and academia (InvisMark, Watermark Anything, TrustMark, and VINE-R) are then evaluated on COCO dataset, highlighting strengths on classical perturbations and persistent vulnerabilities to emerging AI-based attacks, underscoring the need for standard and effective evaluation.