ABI Research predicts that spending in Artificial Intelligence (AI) and machine learning (ML) in the media and entertainment (M&E) to reach US$16.5 billion by 2026. Click here for top use cases for AI in M&E.
Influence AI/ML adoption
The M&E industry is undergoing a transformative process, adapting to changes in consumer behaviour 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 the need for deeper levels of personalization – all while remaining compliant to regulations and customers’ needs.
All these changes are making AI/ML increasingly essential to automating many media processes, including content personalization, content management, media workflows, customer relations, and digital advertising (and ad tech).
Role of AI/ML
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 a very personalized way.
Michael Inouye, principal analyst, next-gen content technologies at ABI Research, says AI is helping make ads 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,” he continued.
Ecosystem benefiting from AI/ML
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, 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.
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.
Inouye says the growing ecosystem 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.
He added that 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 concluded.
