With the increasing number of digital platforms available, consumers now have more options than ever before.
The success of media companies lies in the quality of their content. As it should exceed customer expectations.
This means that media companies need to produce high-quality content that can capture and retain audience attention. This puts pressure on content producers to create more engaging, compelling, and relevant content that resonates with the target audience.
This is where AI can play a critical role by automating tasks such as content curation, distribution, and analysis. By leveraging AI, media companies can free up valuable resources and focus on creating high-quality content that resonates with their target audience.
Forecasting what kind of content consumers want to consume, where and when, is crucial in the pre-production phase.
AI-driven forecasting can unlock multiple sources of value in the media industry, such as predicting revenue and identifying future problems in the content supply chain.
AI-powered tools can help content producers make data-driven decisions about what content to create, how to tailor it to the target audience, and what channels to distribute it on. AI can also assist with audience segmentation, helping content producers understand their target audience’s preferences, interests, and behaviors.
However, AI models require adequate and reliable data, which is not always available.
Nevertheless, AI-driven forecasting in a content pre-production phase can help content producers make more informed decisions to maximize engagement and achieve better business outcomes.
Production and post-production phase
In the production and post-production phases, AI can be used to automate operations such as plot identification, scene selection, and scripting. YouTube and Netflix are already using AI in video creation and distribution, while computer-generated imagery enhances the appearance of video content.
AI also offers new possibilities in content manipulation, such as generating fake faces or editing content automatically. However, these advances also pose new challenges to anti-fake-face solutions and multimedia forensics.
Overall, AI in content production and post-production phases can significantly improve the efficiency and quality of the content creation process. By automating certain tasks and providing valuable insights, AI can help media companies create better content and stay ahead of the competition.
The best time to start using AI is now!
To stay relevant in the current media landscape, media companies must also keep up with the latest trends and technologies.
Media companies that embrace these new technologies are better positioned to reach a wider audience and grow their businesses.
AI has the potential to improve the predictive and budgeting power of media companies and automate several aspects of content creation and distribution. However, reliable data and ethical considerations must be taken into account when adopting AI in the media industry.
As the CEO of Media Tailor, Markus Paul brings over a decade of experience in leadership roles within the media industry and technology companies. With his extensive knowledge and expertise, Markus recently completed an MBA research project on artificial intelligence in the media industry. In this blog series Markus shares his insights from his research.