AI innovations in media and communication

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On my last blog, I talked about AI innovations in healthcare, and this one will share some perspectives on new developments in this industry.

According to Business Wire, Artificial Intelligence (AI) spending in the media and entertainment industry is expected to increase by a record CAGR of 28.1% over the forecast period in the United States (2019-2025), and up from $ 329 million in In 2019 to $ 1,860.9 million by 2025.

Some of the most important areas of application in this sector are: gaming, fake story detection, plagiarism detection, personalization, production planning and management, sales and marketing, and talent identification.

One of the areas that is very exciting is understanding how AI is used in news. AI has great implications in aggregating massive data analysis of conversations on the World Wide Web and classifying them into topics in order to assess globally trending topics or even identify increasing terrorism risks or even health risks like a pandemic.

Other technologies, such as narrative science, rely on AI bots to write the majority of messages over the next fifteen years. One example of this is Automated Insights, which help bring professional sports to our TV screens. Covering over 13 baseball leagues and over 140 affiliated baseball teams, this technology translates narrative into natural language processing and AI linguistic analysis methods. This consolidated news coverage saves journalists research time and, in the future, even saving journalism articles with richer facts and content for a journalist to review and publish.

Content personalization with AI is a gold rush for advertisers as AI enables microsegmentation of customers to deliver the relevant content in support of a perfectly relevant marketing campaign.

Companies like LeadSift in Canada even analyze all of your searches on the World Wide Web in order to gain relevance for targeting the right buyer with the right interests for your products and services. This is an area known as the propensity to purchase signal detection. These solutions help ensure that you are targeting customers with some interest in what your company does. Of course, the timing of the purchase remains a holy grail, but the frequency of consistent search patterns will surely give you some insight into the strength of the area of ​​interest from high slope to low slope.

Another company, Pesado, for example, analyzed over 18 million messages from 180 brands in 2019 to identify words that really resonated with customers. These insights can help to get closer to a psychographic profile of a buyer profile in order to increase the likelihood of an interaction.

According to Rainer Kellerhals, Microsoft’s media and entertainment industry for the EMEA region, AI will affect all parts of the media value chain, help content creators be more creative, help content editors be more productive, and help content consumers create the content to find something that suits your interests and your current situation.

He sees what I see is the increased creativity and navigational skills that AI will enable for the entire media supply chain.

Today, many of the AI ​​techniques used are used in areas such as image recognition, speech-to-text transcription, metadata tagging to increase the need for content monetization. We’re seeing more and more innovations in the media industry where AI tools will be able to predict resource needs or early interruptions in the supply chain while meeting deadlines, in order to detect even large savings in advance to improve profitability margins.

We all know the incredible success that Netflix has driven into our everyday lives – where our preferences are understood and personalization is best.

There are so many use cases of AI in the media and entertainment industry that to learn further, take a look at my new book, The AI ​​Dilemma, which has a large chapter on this industry segment.

We truly live in a society that is full of entertainment, and as our outside and inside worlds continue to mingle with data insights, we create deeper patterns for our needs and wants. As a result of this growth dynamic, ethical questions are increasingly emerging on many stakeholder fronts, asking questions such as: How far can we get with AI innovations before we need more protection barriers for data protection, or what should we do with AI in the media sectors compared to what should we avoid?

Continued dialogue between government, industry and citizens is needed to ensure that AI is being developed for good or for harm. Fake news is an area where more scrutiny is needed.

Note: For more information on the media industry, see The AI ​​Dilemma.


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