eMediaMonitor’s proprietary AI monitoring solutions deliver efficiency and cost savings
Organisations using broadcast monitoring platforms without advanced Artificial Intelligence (AI) automation could be incurring tens of thousands of dollars per year in hidden labour costs, according to new analysis by eMediaMonitor.
eMediaMonitor evaluated the operational workload required to manually process broadcast content after capture, including filtering, summarisation, deduplication, and report preparation. Importantly, this also includes translation from around 90 languages.
These tasks instead have to be carried out by data analysts, increasing the total cost of ownership.
Michelle Harold, eMediaMonitor’s VP of Global Partnerships, said, “Organisations that overlook AI tools for monitoring, collating and analysing broadcast media are not just paying more for their monitoring. They are getting less from it.”
Non-AI monitoring workflows can require hundreds of analyst hours per month, potentially accounting for the time of several full-time analysts. These labour costs are typically excluded when organisations compare monitoring vendors based only on subscription price.
Every organisation has different clip volumes, team structures, language needs and advertising exposure. eMediaMonitor’s cost calculator model’s the true total cost of monitoring based on usage, clearly demonstrating how and where AI can reduce the burden.
Michelle said organisations should evaluate monitoring solutions using total operational cost and output quality, not fees alone.
“When organisations review their broadcast monitoring setup, the conversation almost always starts with subscription price. But when you look more closely, you find the in-house analyst team doing manual tasks that can be automated. That is when it becomes clear that the platform chosen to save money is often one of the most expensive decisions,” said Michelle Harold.
She continued, “AI delivers both efficiency and precision. Automated sentiment analysis, real-time multilingual summaries, intelligent deduplication: these do not simply save time. They produce higher-quality, more consistent insight than manual processing ever could. And in seconds, not hours.”
AI-enabled broadcast monitoring platforms automate tasks that otherwise require manual analyst time, including:
The analysis concludes that the broadcast monitoring industry is transitioning from raw content delivery toward automated intelligence generation.
“The traditional model is that value comes from access to content,” Michelle Harold said. “But AI changes this. The future is automated processing and structuring of content into usable insights. The combination of AI data processing and human intelligence ultimately means improved decision-making.”
AI automation also enables:
The analysis identifies common limitations in non-AI broadcast monitoring systems that create manual workloads:
eMediaMonitor is an independent, privately held broadcast monitoring and media intelligence company headquartered in Vienna, Austria. The platform captures, processes, and analyses broadcast and online media content across television, radio, podcasts, YouTube, TikTok, web TV, and digital channels worldwide.
It provides automated monitoring and insight delivery to PR agencies, marketing organisations, government institutions, and corporate communications teams.
Media contact:
Charlie Pryor
Charlie.pryor@leidar.com
+44 7958 975 667