Introduction
Artificial Intelligence (AI) is revolutionizing the media and entertainment industries, unlocking new possibilities and transforming the way content is created, distributed, and consumed. From personalized content recommendations to AI-driven special effects, the integration of AI technologies is reshaping every aspect of the industry. According to Grand View Research, “The global AI in media & entertainment market size was estimated at USD 14.81 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of 26% from 2023 to 2030. Artificial intelligence’s use in gameplay, fake story recognition, plagiarized detection, production planning and management, personalization, sales and marketing, talent finding, and other fields is propelling the rise of global AI in the media & entertainment sector.” AI is enabling more engaging and immersive experiences for audiences, streamlining production processes, and even creating entirely new forms of media. The following list explores the diverse and impactful use cases of AI within media and entertainment, highlighting how these innovations are driving the industry forward into a new era of creativity and efficiency.
Use Cases
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1. Subtitle generation
AI voice recognition technology is used to automatically generate, translate, and insert subtitles into movies and videos, enhancing accessibility and understanding for diverse audiences.
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2. Optimize media production process
Media content producers leverage AI software to enhance the efficiency and speed of the media production process. This includes organizing visual assets such as movies and TV shows, making the workflow more streamlined and manageable.
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3. Detect inappropriate content
AI systems are employed to detect and flag inappropriate content, including nudity, violence, drug abuse, objectionable language, and visible brands. These systems can then modify or censor the flagged content to ensure it meets regulatory and audience standards.
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4. Analyze human expressions
AI technology analyzes expressions, human reactions, and body language to understand their meanings. This information is then used to create “real-time” packages for sports or other events, enhancing the viewer’s experience by providing more context and engagement.
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5. Generate video summaries from text
AI and Natural Language Processing (NLP) technologies are used to create informative video summaries from text articles. Additionally, AI systems such as GPTs and Large Language Models (LLMs) can automatically generate articles on data-centric topics, including corporate earnings reports or sports game summaries, providing timely and accurate information.
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6. Identify trends and generate articles
AI technology scans and analyzes thousands of recent posts to identify trends and common themes. This helps in pinpointing the most frequently discussed topics, which can then be used to generate new and relevant articles.
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7. Generate personalized headlines
News agencies utilize AI to generate the latest headlines tailored to users’ interests and search history. This personalization ensures that users receive news that is most relevant to them, enhancing their engagement and satisfaction.
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8. Location-targeted mobile advertising
IoT and AI technologies are combined to create location-targeted mobile advertisements. These ads are designed to reach specific groups or consumers who are near a particular point of interest, increasing the relevance and effectiveness of the advertising.
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9. Fake news detection
AI systems are employed to detect fake news by evaluating the content of posts. This involves comparing the text or headlines with the actual content of the shared article and examining similar articles to identify any differing facts, ensuring the accuracy and reliability of the information.
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10. Plagiarism detection
AI technology analyzes an author’s writing patterns to determine if another piece of content is written by the same person. This capability is crucial for plagiarism detection, ensuring the originality and authenticity of written works.
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11. Facial expression detection
Facial recognition and Computer Vision technologies analyze subtle differences in facial expressions. This information is used to better understand and cater to the viewer’s interests, enhancing their overall experience.
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12. Social media post-generation
Natural Language Processing (NLP) technology gathers real-time data on trending topics and generates human-like social media posts. These posts are designed to engage followers effectively, increasing interaction and engagement on social media platforms.
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13. Analyze online social conversations
Natural Language Processing (NLP) technology analyzes online social conversations to understand the deeper context related to specific topics, brands, or themes. This analysis helps in gaining insights into public sentiment and trends.
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14. Gather data on consumer preferences
Data on consumer preferences is collected and mapped to product affinities. This information is used to make informed decisions about which advertisements to show to customers, ensuring higher relevance and effectiveness.
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15. Generate customized advertisements
Machine Learning technology analyzes audience data to create customized advertisements tailored to different audience groups. This personalization enhances the effectiveness of advertising campaigns.
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16. Create contextual advertisements
AI technology is used to create contextual advertisements by automatically cataloging content and providing relevant keywords at the most opportune moments. This approach ensures that ads are highly relevant and timely.
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17. Generate personalized challenges in games
AI technology generates personalized scenarios and spontaneous challenges within games. Developers focus on building the gaming environment and mechanics, allowing AI to create dynamic and unique gameplay experiences without relying on pre-programmed or scripted plots.
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18. Optimize game logic
AI technology is utilized in game development to optimize game logic. This includes generating procedural content and preventing deadlock scenarios, such as in a dungeon-exploring game, ensuring smooth and engaging gameplay.
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19. Predict survival strategies in games
AI technology allows in-game enemies to observe player maneuvers and environmental conditions. This information is used to predict and adapt their survival strategies, making the gameplay more challenging and realistic.
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20. Customize game settings and difficulty levels
IoT devices worn by users capture their reaction times, and AI uses this data to tailor game settings and balance difficulty levels. For example, AI can adjust the speed of opponents in the game to match the player’s skill level, providing a more personalized and engaging experience.
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21. Analyze real-time data from wearables
Wearable devices such as wristbands can function as entry tickets, secure IDs, payment methods, and location trackers in theme parks. AI analyzes the real-time data collected from these wearables to optimize internal park logistics and offer personalized experiences and services to visitors.
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22. Animal protection
Motion sensor-based imaging and AI technologies are used to recognize, distinguish, and track animals. This helps in increasing protection from poachers by providing real-time monitoring and alerts.
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23. Meal selection
AI technology assists consumers in selecting meals that align with their eating preferences. This can include dietary restrictions, nutritional goals, and personal tastes, ensuring a more personalized dining experience.
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24. Customer service at restaurants
Chatbots are currently used to answer customer questions, handle reservations, and provide menu details with photos through chat interfaces. In the near future, AI and Natural Language Processing (NLP) systems may replace or complement human staff in taking orders at restaurants, including drive-throughs, enhancing efficiency and customer service.
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25. Improve food preparation and delivery
AI and robots are employed to boost the efficiency and speed of food preparation and delivery processes. By leveraging Computer Vision and other AI technologies, restaurants can offer 3D food menus that allow customers to visualize their meals, leading to an improved ordering experience.
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26. Product development and promotion
AI systems analyze customer behavior patterns to help businesses develop more appealing products and effective promotional strategies. This understanding aids in attracting new clients and retaining existing ones by catering to their preferences and needs.
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27. Personalized browsing
AI technologies enable personalized browsing and searching experiences by analyzing customer activities and preferences. This allows businesses to present tailored product choices, enhancing the shopping experience and increasing the likelihood of purchases.
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28. Support human security guards
AI and robots are designed to support human security guards by recording and livestreaming video footage, enhancing security measures. Additionally, aisle-analytics software equipped with infrared sensors monitors customer behavior to optimize store layouts, improving the shopping experience and store efficiency.
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29. Image search of products
AI-powered visual search technology enables users to take a photo of a product and instantly search for it online. This feature simplifies the shopping process by allowing customers to find and purchase products with ease, based on visual recognition.
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30. Cashier-less checkout technology
Sensors and AI technologies monitor the items that customers pick up and place in their baskets. Upon exiting the store, the system automatically charges the customers’ accounts, providing a seamless and efficient checkout experience without the need for traditional cashier interactions.
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31. Assess customer reactions
Computer Vision technology tracks shoppers’ facial expressions and hand gestures to gauge their reactions to products. This data helps retailers understand which items are popular and make informed decisions about inventory and marketing strategies.
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32. Audio descriptions of labels and captions
Object recognition and AI-enabled readers provide audio descriptions of labels and captions for artworks in museums, catering to vision-impaired visitors. This technology enhances accessibility, allowing all visitors to fully experience and appreciate the exhibits.
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33. Personalized content recommendation
AI systems in museums and exhibitions recommend personalized content to visitors based on their activity and behavior. The data collected helps improve both online and offline experiences by analyzing how much time visitors spend in different locations. Museums use this information to enhance visitor experiences and predict future attendance and engagement trends.
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34. Interactively explore artworks
Augmented reality and AI systems, such as Generative Adversarial Networks or Diffusion Models, enable visitors to use their smartphones to interactively learn more about artworks. By placing a smartphone or tablet over an ancient statue, visitors can see visual reconstructions of missing parts, providing a glimpse of the statue’s original appearance and enhancing their understanding and appreciation of the art.
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35. Develop optimal strategies for athletes
AI systems assist coaches and teams in accurately analyzing common mistakes and developing optimal strategies for both attacking and defending. Additionally, AI-generated advice helps athletes improve their techniques, such as boxing moves or golf swings, by utilizing data collected from wearables or video analysis, leading to enhanced performance and reduced errors.
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36. Identify malfunctions in races
Computer Vision and Deep Learning Networks are employed to swiftly identify and address cars experiencing malfunctions during races. This technology enhances safety in car racing by allowing for rapid detection and intervention, reducing the risk of accidents and ensuring the well-being of drivers.
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37. Re-render photographic images
AI systems analyze and abstract visual patterns from various artworks and then creatively apply these patterns to re-render photographic images. This process results in new images that incorporate the distinctive features of the original artwork, offering a unique blend of artistic styles and enhancing the visual appeal of the photographs.