Introduces a proactive intelligence model for media operations, shifting AI from reactive tools to active contributors across the supply chain
TMT Insights, a leader in professional services and software development for the media and entertainment (M&E) industry, today announced the launch of TMT AI at NAB 2026, introducing a new model for how artificial intelligence operates within media supply chains.
TMT AI moves beyond reactive models by embedding proactive operational intelligence directly into workflows. Designed to orchestrate the business of media, it functions as a persistent intelligence layer that continuously observes, learns, and acts across systems, jobs, and assets—enabling teams to prioritize effectively, maintain operational flow, and resolve issues before they disrupt the business.
“AI should not wait to be told what to do,” said Brett Beers, Chief of Architecture and Innovation of TMT Insights. “With TMT AI, we are embedding intelligence directly into the fabric of media operations. It anticipates needs, corrects issues automatically, and continuously monitors workflows to improve efficiency across the supply chain. This is AI proactive by design and built to act, not just respond.”
At its core, TMT AI delivers resolution before disruption by proactively identifying risks, maintaining system health, and reducing manual intervention. This intelligence is delivered through three core capabilities:
Anticipate Requests
TMT AI uses operational data and user behavior to surface next-best actions before users engage, reducing repetitive tasks and accelerating execution.
Smart Corrections
TMT AI identifies profile specification conflicts and inconsistencies in real time, resolving issues such as order placement errors, metadata mismatches, and rights violations before they escalate.
Self-Healing Workflows
TMT AI continuously monitors system activity to detect and resolve issues, including stalled jobs and processing anomalies, applying automated fixes to maintain operational continuity.
TMT AI delivers continuous, compounding impact across media operations. Every prevented error reduces downstream disruption, every automated correction lowers operational burden, and every proactive insight accelerates execution. As the system learns and improves with each interaction, it enables organizations to move beyond experimentation and operationalize AI at scale, bringing order to complexity and empowering teams to conduct with confidence.
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