AI can help media teams sort, tag and find video, but many organisations struggle to turn that promise into measurable results. Veritone CEO Ryan Steelberg argues that the sticking points are often the unglamorous work around the tools: data, legacy systems, governance and staff readiness.
Watch Desk analysis
What happened
In a Forbes Technology Council article published on 12 October, Steelberg says video operations face familiar AI adoption problems with extra integration work: fragmented archives and older systems can make data preparation and custom connections costly. He recommends assessing data and integration needs before implementation, choosing a focused business problem for a pilot, and measuring outcomes such as time saved, labour costs and metadata quality.
His further proposals include audit trails and permission-based access, clearer data-handling logs, connectors for common media systems, staff training and early involvement from legal and compliance teams. Steelberg also cites research on costs and skills gaps, though the excerpt does not provide enough detail to assess those figures independently.
Why it matters
A media team cannot get much value from automated tagging if its archive is disorganised, its systems cannot exchange data or nobody has agreed what success looks like. Those are practical hurdles, not a shortage of AI enthusiasm. The article gives organisations a useful checklist for testing whether a project is ready to scale, rather than judging it by a polished demo.
Our read
Start with one real workflow and a measurable result, not an enterprise-wide promise. Before a pilot begins, map the data, integration work, permissions and people who will use the system. AI may speed up the task; it will not tidy decades of media infrastructure by wishful thinking.
What to watch
- Whether media AI pilots set clear measures for time, cost and metadata quality.
- Whether vendors make data preparation and integration costs clearer before deployment.
- Whether governance and staff training are built into projects from the outset.
Discussion spark: When media companies struggle to get value from AI, should vendors be responsible for making integration and costs clearer, or should buyers do more preparation before purchasing?
Sources and evidence
- Why Organizations Still Struggle To Adopt AI For Video Operations – Forbes (12 October 2026, 11:45 UTC)
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