AI in media

AI in Media: Redefining Customer Experience with Immersive Stories

Artificial intelligence has become an important milestone in the digital transformation journey of all sectors, including media and entertainment. With the buzz it has created, it is no surprise that the adoption of AI in media and entertainment is a game-changer for the pioneering and the digitally inclined. It plays an immense role in the way content and experiences are curated and delivered at scale today. 

The next era of the Media industry is defined by customers’ increased demand for immersive, live, and shareable experiences. Consumers now wish to get more engaged, better connected, and closer with the stories they love – both in the digital and physical worlds. Companies have started empowering these experiences through emerging technologies. Big data and artificial intelligence will create the most dramatic change, redefining how the industry can connect with all stakeholders and drive growth.

Modern enterprises are now deploying AI tools and technologies to ensure effective decision-making and agile responsiveness to market changes. While over-the-top players like Netflix have already adopted a data-first approach, many others are still trying to attain AI success. The road to full-fledged AI adoption is not devoid of challenges. AI can be only as good as the data you have. Every effort must be made to efficiently manage different data types, including audience, operational, and content data.

As workflows and processes continue to become AI-enabled, we analyze the media and entertainment landscape to understand the impact of AI adoption.

Customization to optimization – the role of AI in media & entertainment sector

AI plays an important role in enhancing the user experience across all the six segments of the Media and Entertainment (M&E) industry: Films & TV, social media, journalism, gaming, music, and sports.  

Customer-focused experience with content personalization 

AI powers recommendation engines to predict what content should be promoted and when based on customer viewing data, search history, ratings, and even the device customers use. A classic case in point is Netflix’s landing cards1 helping the streaming website customize what you watch through personalized targeting. Images of lead characters are seen while scrolling to understand popular choices based on the cards people click. 

Machine classification algorithms for improved search optimization

AI also plays a significant role in search optimization thanks to machine classification algorithms that help in improving the categorization of movies. Users can search based on categories instead of individual titles to enable quick searches and smooth navigation. Streaming websites have enhanced streaming quality with AI since it helps them predict future demands and position their assets strategically to help users enjoy high-quality streaming even during peak hours.

Music streaming companies like Spotify and Apple Music rely on machine learning algorithms to segment users and songs to offer personalized recommendations and playlists. Natural Processing (NLP) gives them an edge by providing information about songs and artists from the web. AI has also been helping musicians generate lyrics and compose songs.

Enhanced news reporting with robot journalists

AI has a coveted place in social media and journalism too. While social media platforms like Facebook, Instagram, and Snapchat are using it to offer personalized products and services, Forbes and Bloomberg have been using robot journalists Bertie and Cyborg respectively to create storylines based on their parameters and data.

The Washington Post, too, gave us a taste of the future of journalism with its Heliograf2 that covered the Olympics. However, the Chinese news aggregation service Toutiao took it to the next level by creating an AI-enabled reporter Xiaomingbot that churned out a whopping 450 articles during the Rio Olympics in just 15 days.  

Gaming and customer-specific advertising

As the supply of mobile games continues to exceed demand, companies are now using AI to estimate customer lifetime value (CLV) to bid efficiently in advertising for users, focusing only on those who would enthusiastically engage with their products. AI is also helping animators bring exciting characters to life for a multitude of virtual reality games and movies.

 Improved entertainment quotient in sports broadcasting

The perennial popularization of sports brings new fans, players, and subscribers into the sports and gaming fold. AI satiates them with entertaining shots and angles during live telecasts and enhances the experience by broadcasting exclusive footage captured by drones.

Laying deeper data foundations for successful adoption of AI in media

AI has forayed into virtually all functions and areas to add value in a highly competitive market. As competitive pressures intensify, it has become more critical than ever to fast-track your AI initiatives and reap their benefits. But as with every other digitalization endeavor, AI adoption too brings along unique challenges.

Here’s what you can do to overcome them and lay deeper data foundations for successful AI adoption. 

Assess AI maturity 

M&E businesses are now shifting from B2B to B2C business models due to the direct-to-consumer delivery and consumption trends and hence are currently operating on massive amounts of data. In order to make complete sense of this data and drive decisions, data silos need to be removed first. A fragmented approach is not going to work and should be replaced with a data-first approach.

Organizations often get caught up in a quandary, wondering if they should modernize the data architecture first for their AI models to rest upon or build a model and modernize only that part of the required data. However, the right approach would be to invest in a sound strategy for your target data architecture that relies on proven models to avoid pitfalls and rework. Data management should be a top concern for organizations to interpret and get actionable insights.

Focus on people and processes 

Data sources will continue to increase, causing greater challenges for data management and project management. So while building your technology stack, it is equally important to invest in people and processes that would be at the helm of things while progressing up the AI maturity curve.

AI leaders believe in including technologists and data scientists in business teams to give them the visibility to understand business challenges. It is essential that business leaders, values, people, and culture are aligned to enable successful automation and AI adoption. Only then would human employees be able to work alongside robots and AI-powered machines to build capabilities and deliver value.

Adopt a continuous improvement approach

AI is not a one-time endeavor but will continue to evolve with time. To achieve enterprise-wide AI, it needs to be perceived as a transformational initiative that must be implemented across all front-end and back-end processes.

A comprehensive picture of ROI based on revenue and costs for different functions and processes can give organizations the clarity to track value and identify areas that need to improve. M&E companies are integrating established AI processes into finance, HR, and other functions to garner cost and operational efficiencies.

The future of entertainment looks AI-centric

AI is undeniably transforming the media and entertainment sector, empowering them to make informed decisions based on critical data analysis. It will navigate disruption and drive growth in all spheres by addressing data gaps and helping M&E companies become more agile. Clearly, AI is impacting everyday entertainment in a big way, and it’s time organizations harnessed its power to fine-tune their forward-thinking strategies and explore new avenues.

Discover the power of AI with Trigent

The technology experts at Trigent have been offering robust AI-enabled solutions to M&E companies based on data from diverse sources and powerful algorithms to enable a superlative user experience while giving them insights into customer behavior. 

We help build excellent AI capabilities and advanced features to deliver content in the most effective manner. We can help you build high-quality datasets to get the best results in diverse settings and drive impact at scale. 

Call us now for a business consultation

References

  1. https://www.wired.co.uk/article/netflix-data-personalisation-watching
  2. https://futurism.com/the-future-of-writing-chinas-ai-reporter-published-450-articles-during-rio-olympics 

Author

  • Anjana Sadanandan works as Manager - Web Content at Trigent. She has a strong marketing communication background and has worked with several multinational organizations.

Published by

Anjana Sadanandan

Anjana Sadanandan works as Manager - Web Content at Trigent. She has a strong marketing communication background and has worked with several multinational organizations. View all posts by Anjana Sadanandan

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