AI Brings New Coordination Layer to Streaming Ad Tech

The article describes a fundamental shift in how the ad tech industry operates. Until recently, media planning relied on static spreadsheets and manual processes that could take weeks—publishers had to identify specific content assets, reach out to agencies, and coordinate plans across different channels. AI is collapsing this timeline by enabling planners to ask dynamic questions like "What if supply shifts mid-flight?" and model delivery across live, VOD, and FAST channels simultaneously. The speed advantage is material: Globant's work shows that AI can cut asset identification from weeks down to the time it takes to understand metadata, which now happens automatically as content is ingested.

The industry's adoption curve varies significantly. While 35–40% of publishers are using some form of AI, Jeff Ellin from FreeWheel reports conversations with 18 European broadcasters, some expressing immediate readiness ("Can we start tomorrow?") and others still evaluating. Standardization—specifically through IAB Tech Lab's new AAMP framework—is emerging as critical infrastructure, extending existing protocols like OpenRTB rather than replacing them wholesale. This allows publishers and buyers to connect their own AI systems through Model Context Protocol (MCP), reducing friction and enabling natural-language interaction with ad platforms.

Cost and ROI remain open questions. Bitmovin's per-asset pricing ($30–$35) appears reasonable until multiplied across hundreds of archived assets, which is why publishers are conducting return-on-investment analyses. Notably, clients are not yet trusting agents to execute changes autonomously; instead, they prefer agents to identify underperforming campaigns and deliver recommendations for manual review. This suggests the technology is advancing faster than organizational readiness to delegate decision-making to machines.