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Major AI Advances in Media and Publishing Industry

Abhishek Anand by Abhishek Anand
June 23, 2019
in Artificial Intelligence
Reading Time: 5min read
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Fueled by a profusion of digitized data and the latest computational processing power, AI is disrupting every industry. The technology’s ability to detect patterns among billions of unrelated data points is revolutionizing the manner in which humans work, communicate, study, and entertain themselves.

Like many other industry segments, Artificial Intelligence is taking the media and publishing industry by storm. In fact, a report by McKinsey Analytics reveals that AI is expected to add a projected value of USD 450 billion to this domain.

Major AI Advances in Media and Publishing Industry 2
Source :: https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-executives-ai-playbook?page=industries/media-entertainment/

Take Netflix, for instance. The organization has significantly reduced its customer churn and boosted subscriptions by applying AI-powered machine-learning algorithms that personalize the viewing experience. In a recent report, the company boasts of more than 148 million global members streaming more than 250 million hours of TV shows and movies per day.

Similarly, in the publishing domain, the major challenge is to bring data from a heterogeneous and incompatible system, such as KPIs, reviews, subscriptions, terminations, metadata, etc. AI visualizes the various data streams and monitors it, making it manageable for scholars and publishers.

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AI holds a lot of promise for the fields of media and publishing. No wonder, firms in this domain are preparing to ride the waves of disruption by investing in AI. In a survey conducted by IABM, over 56 percent of the survey participants shared that they are willing to invest in AI. Thus, AI is making significant strides in the media and publishing world.

Read on to learn what this disruptive technology has in store for this domain.

1. Automated Journalism

AI applications are playing a central role in revolutionizing journalism. Mainstream publishers, media houses, and newsrooms are using AI to automate news reporting and improve the quality of the news media. Believe it or not, the Washington Post uses its automated reporter, Heliograf that published 850 articles within the first year of implementation. These articles hold high-quality and relevant content, generating more than five hundred thousand clicks.

AI is helping newsrooms streamline their media workflow, automate mundane tasks, dig and crunch quality data, eliminate fake news, identify frauds, and generate intelligent stories.

Facebook, for instance, is using AI-powered psychometric profiling to extract data from social media profiles and scan word and image patterns to identify and filter fake news. Reuter’s News Tracer uses AI to determine whether the trending topics are newsworthy, allowing journalists to focus on high-productivity activities and innovation.

2. Content Personalization

AI applications are disrupting the media experience for consumers. The technology is empowering media companies to proactively offer the most relevant content based on an individual’s passion and interests. Features like speaking apps and chatbots are allowing viewers to communicate and engage with content and enabling media and publishing companies to improve customer experience.

Further, AI allows publishers to understand their audience at a deeper level. AI-powered machine or deep learning can synthesize content that connects with people at the appropriate time and in the right context. For instance, content read on weekends is different from other days of the week. AI can help media companies take cues from such reading habits and preferences and deliver relevant content to their audience, giving them a serious competitive edge over others.

3. Natural Language Processing

Besides detecting fake news and plagiarism, AI capabilities like Natural Language Processing (NLP) can automate the workflow for authors, scholars, and publishers, boosting the efficiency of the process.  NLP combines grammar analysis with machine learning to help the system recognize the structure of sentences and discern their meaning.

Thus, with the NLP technology publishers can automate critical yet tedious tasks like editing and formatting, allowing them to focus on creating quality content and make more journal submissions. Data companies like Synapsify use machine learning and NLP technology to analyze unstructured data from surveys, social media, and customer reviews and direct marketers.

4.Advanced Analytics

AI can effectively organize and analyze current and historical data using complex methods and algorithms. Further, AI-powered automated data forecasting can be used to make predictions on future consumer behavior and shape the firm’s monetization strategy. The New York Times, for instance, employs AI-powered data science and deep learning to boost their subscription-based revenue.

In this new age of data, AI can help the media and entertainment sectors to get real-time insights about their target audience. This advanced analytics can help them in better ad targeting, optimized media scheduling, and targeted content generation.

5.Automated Image Recognition

Untagged and poorly-organized image archives are difficult to navigate and lose their monetary value over a period of time. AI-powered image-recognizing tools, namely Google Reverse Image search and API Cloud Vision, Amazon Rekognition, and Clarifai recognize physical objects, faces, and landmarks and add them as tags to the file’s metadata. This saves the time and effort spent by publishing and news firms in searching and streamlining image archives.

Thus, automated image recognition and classification allows media and publishing houses to fine tune the categorization of their visual assets.

Final Thoughts

The media and publishing domain has been buzzing about the disruptive applications of Artificial Intelligence. In the years to come, the capabilities of AI are expected to evolve, enabling media and publishing houses to proactively offer the most relevant content to their audience. Further, integrating AI and machine learning into their platforms can help these firms boost their operational efficiency.

Consequently, media and publishing firms should proactively invest in AI to boost customer experience and stay ahead of the curve. The information shared above will help firms in this domain appreciate the latest AI advances and their role in taking their business to the next level.

Tags: AI researchAI ServicesDeep Learningimage recognitionNatural language processingPredictive analytics
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Abhishek Anand

Abhishek Anand

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