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There is no doubt that the media industry is undergoing a radical shift thanks to a series of revolutionary changes. Some of the factors include the proliferation of new distribution channels, lack of visibility of end-to-end workflow system and changing customer expectations across content consumption. These factors have motivated media companies to digitize their media supply chain and deploy cognitive services.

From content production to content delivery and audience engagement, cognitive services unearths tremendous opportunities to achieve significant improvements in business outcomes with a direct impact on RoI. A report by MarketsandMarkets (1) forecasts the global cognitive media market size to grow from USD 551.4 million in 2018 to USD 1,839.1 million by 2023, at a compound annual growth rate (CAGR) of 27.2%.

Cognitive computing technologies include a set of Artificial Intelligence (AI) techniques, Deep Learning, and Machine Learning (ML) algorithms that offer APIs to enable natural and contextual interaction within different systems. Cognitive AI is the next stage in automation technology where cognitive supplements human decision-making power capabilities, while gradually acquiring the ability to take some decision-based tasks independently emulating human beings.

Processes such as content creation, content captioning, metadata creation, music-controlling voices, and speech-to-text conversion have the potential to maximize cognitive solutions like Computer Vision, Speech Recognition, Natural Language Processing (NLP), Natural Language Understanding (NLU) and Natural Language Generation (NLG). Such tech-enabled processes can help media companies achieve much higher levels of efficiencies and operational scale.

Some sample use-cases for cognitive services in the media industry include -

  • Marketing and Advertising: Companies are adopting newer AI techniques and machine learning algorithms to help in developing film trailers and design advertisements.
  • Recommendations and Hyper-personalization: Content providers are using cognitive services to recommend and provide hyper-personalized content to their viewers based on data collected from user activity and behavior.
  • Search Optimization: Media content producers are using techniques like NLP, AI and ML algorithms to improve the speed and efficiency of their media supply chain and the overall ability to organize video assets.

Interactive Bots

Another important application of cognitive solutions is the use of interactive bots.

Consider a situation where a customer is contemplating watching a movie on Netflix. However, he is confused about the choice to make due to the overwhelming size of the film library. If Netflix were to recommend movies based on his mood, imagine the delight of the customer.

Cognitive-AI can completely take charge of such a situation and help elevate satisfaction, build loyalty, increase engagement and reduce churn among the audience. Smart cognitive AI-driven interactive bots can augment the user experience by reducing the time-to-resolution. The round-the-clock available cognitive AI bot can interactively speak to a customer as a real human does. By understanding the user profile and past viewership patterns, the interactive bot will decipher what users want to watch consequently allowing it to recommend relevant content and enabling a more personalized experience.

By the year 2020, Gartner2 predicts that AI bots rather than humans will manage almost 85% of customer interactions. As media companies grapple with the challenge of getting personalized content to the customer at the right time, companies that proactively invest in these advanced technologies will gain a critical first-mover advantage.

Going beyond interaction

Few AI techniques and ML algorithms delve deep into a content asset to examine tone, personality, sounds/words, and language taxonomy. These techniques perform word-by-word and frame-by-frame examination of every aspect of the content. They auto-generate finely-grained metadata with details like emotions, personas, tones, along with descriptors like genres, actors and durations. Using NLU object recognition and other application program interfaces (APIs), it becomes possible for cognitive computing technologies to identify the minute details around semantics, visual cues and surrounding context that occur within every scene thereby creating a detailed understanding of the content.

Using cognitive AI to deliver personalized ads and content monetization

Various software (like Pippa) are available that allow pod-casters to attach personalized ads to a podcast. These companies are planning to invest more in AI and ML platforms to perform audio search and personalize ads based on a podcast’s content. With this new avenue, AI could boost podcast monetization and make it a more profitable venture.

Cognitive is here to stay

The key characteristic of Cognitive Services is to understand, learn and re-learn. The technologies within cognitive AI have the potential to revolutionize businesses and the respective operating and business models in the media industry.

Mindtree is at the forefront of implementing these technology services across industry segments, especially in Media . From the vast experience of working with a multitude of clients, vendors and AI/ML researchers, Mindtree's expertise led platform-based approach can help media businesses to address the burning needs of technology and business transformation powered by Cognitive Services.

Interested in incorporating Cognitive Services for your business? Let us assist you!


  1. Cognitive Media Market by Technology (Deep Learning & Machine Learning, NLP), Application (Content Management, Network Optimization, Predictive Analysis), Component (Solutions, Services), Deployment, Enterprise Size, and Region - Global Forecast to 2023

About the Author

Priya Pariyani
Solution Consultant, Mindtree

Priya Pariyani is a Solution Consultant at Mindtree. She is responsible for designing customer-centric, automated and intelligent solutions in Media and Entertainment ISG. She has 7+ years of presales, business analysis, project management and agile experience handling complex and high-worth projects across BFSI, Media and Manufacturing domains. She is also a budding developer in IoT and Analytics.

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