The September 2022 AI/ML Adoption Trends report from broadcast and media technology supply industry trade body IABM reflects the rapid uptake of these technologies to automate what were previously labour-intensive tasks in a media landscape where data volumes are growing exponentially while speed and accuracy are ever more important in the battle for viewers.
Key findings include:
- AI/ML adoption is growing, reaching 32 per cent in 2022. AI/ML adoption is enabled by the growing cloud adoption and accelerated by COVID-19.
- Manage and Produce remain the main deployment areas for AI/ML technology in the M&E industry.
- Most AI/ML use cases in content management systems are to automate routine tasks such as metadata tagging, image recognition, audio/video recognition, and speech-to-text.
- Data availability is growing, and the cost of data training is declining with wider technology deployment, resulting in more predictable ROI.
- Media businesses prefer internal deployment of AI/ML technology, which requires recruiting talent with specific skills, making talent scarcity one of the main challenges for AI/ML adoption.
“The move to the cloud – accelerated during the pandemic – alongside the explosion in data availability, has driven adoption of AI/ML in Broadcast and Media as companies increasingly look for tools to give them a competitive advantage,” advises Olga Nevinchana, Senior Research Analyst at IABM. “They are increasingly turning to AI/ML technologies to encompass more and more operations in the Manage and Produce segments of the BaM Content Chain. While the major cloud providers now offer a wide range of native AI/ML tools as part of their overall offerings, it’s interesting to note that internal deployment is still preferred by the majority of M&E companies, despite the ongoing scarcity of talent in this area.”