The month of September 2022 AI/ML Adoption Trends Report from broadcast and media technology delivery industry trade body IABM reflects rapid adoption of these technologies to automate what were previously labor-intensive tasks in a media landscape where data volumes grow exponentially while speed and accuracy are increasingly important in the battle for viewers.
Key findings include:
- AI/ML adoption is growing, reaching 32% in 2022. AI/ML adoption is enabled by growing cloud adoption and accelerated by COVID-19.
- Management and production remain the main areas of deployment of AI/ML technology in the M&E sector.
- Most use cases for AI/ML in content management systems involve automating routine tasks such as metadata markup, image recognition, audio/video recognition, and text-to-speech.
- Data availability increases and the cost of data training decreases with wider technology deployment, resulting in a more predictable return on investment.
- Media companies prefer internal deployment of AI/ML technology, which requires recruiting talent with specific skills, making talent scarcity one of the key challenges for AI/ML adoption.
“The move to the cloud – accelerated during the pandemic – alongside the explosion in data availability, has driven the adoption of AI/ML in broadcast and media as companies increasingly seek tools to give them a competitive edge,” advises Olga Nevinchana, Senior Research Analyst at the IABM. “They are increasingly turning to AI/ML technologies to encompass more and more operations in the management and production segments of the BaM content chain. While major cloud providers now offer a wide range of native AI/ML tools as part of their overall offerings, it’s worth noting that in-house deployment is still preferred by the majority of M&E companies, despite the persistent scarcity of talent in this area. ”
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