The media and entertainment (M&E) industry continues to undergo a transformative process, adapting to changes in consumer behavior and preferences, new technologies, and regulations. Direct to Consumer (DTC), emphasis on privacy, omnichannel marketing, and cord-cutting are creating numerous challenges for M&E service providers. These include handling the high volumes of data generated, complexities in audience targeting and identity resolution, and need for deeper levels of personalization - all while remaining compliant to regulations and customers’ needs. All these changes are making artificial intelligence and machine learning (AI/ML) increasingly essential to automating many media processes, including content personalization, content management, media workflows, customer relations, and digital advertising (and ad tech). According to global technology intelligence firm ABI Research, the market potential for AI/ML in M&E will reach US$16.5 billion by 2026.
Personalization is becoming more nuanced and intelligent away from simple suggestions of multimedia programs to watch or product recommendations. AI/ML solutions available today enable M&E companies to tailor their services in line with the rich metadata they extract from their subscribers, which drills down into sub-genres and incorporates more information about the user’s history, tastes, and preferences in very personalized way. “Also, thanks to AI/ML, Ads are becoming more contextualized, leveraging a wealth of data around environmental factors like weather and local store inventories. This data is being used to offer more targeted, contextually appropriate, and timely ads – for example a pharmacy could market allergy medicine to individuals within a high pollen count area and highlight nearby stores with available inventory,” explains Michael Inouye, Principal Analyst, Next-Gen Content Technologies at ABI Research.
Within the M&E vendor space, particularly ad tech, there is a wide breadth of companies leveraging AI/ML to underpin their personalization and media workflow solutions. From the public cloud companies, of which AWS stands out with its media solutions and support for companies at various levels of AI/ML expertise and a growing partner ecosystem, to more specialized players who target specific applications and media workflows. Some notable companies among these specialized players include: Conviva (QoE and viewer insights), ThinkAnalytics (personalization), IRIS TV (content contextualization), Clinch (deep levels of ad targeting), and Pixability (brand suitability and targeting for YouTube and CTV).
There has been a dramatic shift from the M&E industry that once prized end-to-end platforms and turn-key solutions to modularity and flexibility. “This speaks to the ongoing changes in the industry but also the increased diversity among service operators and customers, who bring in their own levels of expertise and preferred partners,” Inouye says. Openness and flexibility will be key as we move further into the future when mixed reality (XR) becomes more mainstream and new opportunities, like shoppable TV, will become a reality. Today, companies like TheTake are powering shoppable content in TVs and mobile devices, which will dramatically change with the availability of smart glasses. “Throughout all these market changes, AI/ML will play a critical role in moving the M&E industry forward to adapt and take advantage of any new market opportunities,” Inouye concludes.
These findings are from ABI Research’s AI/ML in Media and Entertainment application analysis report. This report is part of the company’s Next-Gen Content Technologies research service, which includes research, data, and ABI Insights. Based on extensive primary interviews, Application Analysis reports present in-depth analysis on key market trends and factors for a specific application, which could focus on an individual market or geography.
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