In an increasingly competitive media landscape, personalization is a key competitive differentiator. To maintain viewer engagement and adapt to the evolving preferences of diverse audiences, media companies are leveraging artificial intelligence (AI) to hyper-personalize content, elevating the customer experience.
However, these opportunities come with risks, from AI hallucinations to data breaches. Media companies will need to proactively mitigate these risks to make the most of their AI investments.
By understanding both the potential benefits of AI, and the risks it poses, media companies can set themselves apart from the competition and secure customer engagement and loyalty.
Key Applications in Media
1. Enhancing Content Recommendations
Enhancing content recommendations is among the most common applications of AI in media. Major streaming platforms are setting the standard by using AI algorithms to analyze user behavior and preferences to offer tailored content suggestions. By providing users with a more personalized menu of the platform’s content, AI-enhanced recommendations can help media companies retain existing customers and attract new ones.
2. Hyper-Personalization through Data Analysis
AI’s ability to analyze vast amounts of data enables media companies to hyper-personalize their offerings, tailoring content to individual preferences on a more granular level than was previously possible. AI can refine and adapt content based on real-time feedback and biometric data, creating a more immersive and engaging experience for users. Data-backed hyper-personalization can be particularly effective in global campaigns, where AI can help content resonate with diverse audiences by factoring in cultural and linguistic nuances.
3. Transcreation and Localization
AI tools can also assist with transcreation — adapting content to different languages and cultural contexts without changing the original meaning of the content. This capability is crucial for global media companies aiming to reach diverse audiences. AI can also facilitate versioning, allowing media companies to create multiple versions of the same content that cater to different audience segments.
4. Content Remastering and Regeneration
AI can play a key role in the revitalization historical content. Remastering old movies or album recordings has become a common practice and offers media companies more ways to monetize artistic intellectual property (IP). With AI, media companies can go beyond restoration by regenerating old content with the goal of making it more relevant for modern-day audiences. Imagine an adaptation of a fan-favorite classic movie set in the modern era, or a series reboot that takes place in a different geography. These are just some simple examples of how AI can refresh content and create new revenue streams in the process.
5. Real-Time Content Adaptation and Segmentation
One of the most valuable uses of AI for media companies is real-time content adaptation. By leveraging biometric data and real-time feedback, AI can adjust content in the moment to maximize user engagement. For example, a horror movie could become more or less intense based on the viewer’s heart rate. Just as a comedian or a rock band could change their live performance based on an audience’s reaction, AI can bring new flexibility to otherwise pre-produced and static content. This level of customization can provide users with a unique and memorable experience each time they interact with a piece of content. It can also help media companies with micro-segmentation — targeting niche audiences with highly tailored content.
Challenges and Considerations for Maintaining Consumer Trust
Media companies looking to deepen their user experience and set themselves apart from competitors can leverage AI to transform their businesses — but AI can also bring new risks as companies manage greater volumes of data and cyber threat actors seek new attack avenues to gain access to that data. Media companies are well aware of this risk: According to our 2025 Technology CFO Outlook Survey, 97% of media companies are concerned about AI risk, with 56% ranking it as a significant concern.
Before investing in AI, media companies must identify and proactively address AI-related risks:
AI offers many benefits for personalization, but it also raises important ethical considerations. Because AI requires data to function, media companies will be collecting and storing more user data than ever before. They must navigate a fine line between personalization and privacy, deriving value from user data while keeping it secure and handling it responsibly. Robust data governance and security measures are critical to helping media companies safeguard sensitive information and ensure data usage is appropriate and ethical. In addition, media companies will need to consider what privacy disclosures to make to their users and how to obtain informed consent from customers on their data usage.
AI models can sometimes generate content that is incorrect, misleading, or entirely fabricated, known as AI hallucination. Hallucination poses a serious risk to media companies that intend on leveraging AI in content development. If companies fail to vet AI-supported content, they can unintentionally spread false information and damage their credibility. Companies must put proper verification and controls into place before rolling out AI-supported content, or else media companies risk losing customer trust and harming their reputations.
The term “AI” is often used broadly, encompassing a wide variety tools and technologies. Media companies need to clearly define the role of AI in their strategies to avoid misunderstandings about whether and how it is used. Transparency, especially around the specific tasks that AI is performing and the benefits it provides to customers, can help dispel fear and build trust with key stakeholders
Looking Ahead
AI is ushering in a new age of content and enabling unprecedented levels of personalization for the media industry. From tailored content recommendations to real-time adaptation, AI empowers media companies to deliver experiences that resonate deeply with their audiences. But more data also means more risk, and media companies must prioritize responsible AI use. Companies that can strike the right balance will unlock new potential to create compelling and personalized content that keeps users coming back for more.
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