Artificial intelligence (AI) is the single biggest area of transformative tech in modern life. It is already completely disrupting the way content is created, discovered, and monetised. But as the conversation (and applications) around AI evolves, it’s clear that we need to move beyond broad strokes and focus on its real-world impact for our sector. Rather than discussing AI’s potential, let’s examine where it is already making a tangible difference—improving user experiences, driving new revenue streams, and ensuring regulatory compliance.
From smart recommendations and multilingual support to targeted advertising and metadata enrichment, AI has moved from being a buzzword to a business tool that’s rapidly reshaping media organisations. This blog explores the practical applications of AI in the media industry, based on insights from DTG working groups, whitepapers and events, and looks at how it is unlocking new possibilities and paving the way for innovation.
AI-Powered Content Discovery and Personalisation: Creating Value through Smarter Experiences
When it comes to enhancing the viewer experience, the importance of accurate content recommendations cannot be overstated. But the sophistication of these recommendations is evolving rapidly. Rather than relying solely on viewing history, AI now leverages deep learning models to analyse subtle patterns in user behaviour, mood, and even real-time engagement metrics to offer recommendations that are not just relevant but contextually appropriate.
For example, during peak viewing hours, AI-driven platforms may prioritise lighter content, while during quieter periods, it might suggest more in-depth programming based on previous user engagement. The shift from simple content suggestion to nuanced personalisation is boosting engagement levels and ensuring that viewers are consistently discovering content that resonates with them.
Smart Metadata: Fuelling Enhanced Content Delivery and Monetisation
Content metadata used to be a rather mundane subject—think titles, genres, and cast lists. Today, it’s one of the most valuable assets in media. AI has brought metadata into a new era, with sophisticated algorithms capable of generating enriched metadata that includes emotional tone, visual aesthetics, and even inferred viewer sentiment. This depth of understanding is changing how content is categorised, searched, and monetised.
Take, for example, AI’s role in automating the creation of enriched metadata for vast content libraries. This doesn’t just optimise content delivery by enabling more precise categorisation, but also drives monetisation by making content more discoverable and appealing to advertisers. Metadata that captures deeper context—like themes or moods—opens the door to new monetisation models, such as contextual advertising that aligns more closely with the content’s tone or themes.
Revenue Generation Through Targeted Advertising and Monetisation
One of AI’s most significant impacts on revenue generation comes from its ability to understand and segment audiences in ways that were previously unimaginable. By analysing data from multiple sources—such as social media activity, viewing habits, and even environmental factors like time of day—AI can create highly granular audience profiles.
These profiles enable media companies to offer more targeted advertising solutions, increasing ad relevancy and boosting revenue. What’s more, AI’s ability to track real-time engagement means that adverts can be dynamically adapted based on viewer interaction, ensuring that advertisers are reaching the right people with the right message, at the right time.
Optimising Content for Diverse Audiences: AI’s Role in Multilingual Support and Accessibility
AI has also become an indispensable tool in making content more accessible and inclusive. Automatic translation and subtitling powered by natural language processing (NLP) are already enabling broadcasters to reach global audiences with more ease. But it goes further—AI can analyse regional idioms and cultural nuances to ensure that translations resonate with audiences, not just linguistically but culturally as well.
Additionally, AI’s capabilities extend to automated audio description and closed captioning, enhancing the viewing experience for individuals with visual or hearing impairments. This not only widens the potential audience but also aligns with the industry’s increasing focus on accessibility and compliance.
AI in Compliance: Ensuring Content Safety and Regulatory Adherence
The compliance landscape for media is becoming more complex, with evolving regulations around data privacy, content standards, and even misinformation. AI is stepping in as a powerful ally in navigating this maze. Automated content moderation tools, powered by AI, can detect inappropriate or harmful content in real-time, ensuring that platforms adhere to local and international regulations.
Moreover, AI can monitor content for adherence to new regulations like the UK’s Media Act, which requires broadcasters and content creators to uphold certain standards of accuracy and impartiality. By flagging content that may be non-compliant, AI helps organisations stay ahead of regulatory challenges, avoiding potential penalties and reputational damage.
AI’s Role in Content Analysis: From Audio and Facial Recognition to Advanced Classification
One of the most exciting applications of AI in media is in deep content analysis. AI-powered tools can perform audio recognition to detect music, sound effects, or dialogue. Facial recognition technology, meanwhile, can identify on-screen talent, making it easier to tag and categorise content. These capabilities not only streamline production workflows but also enable new forms of content discovery and viewer engagement.
For instance, a viewer might search for content featuring a particular actor and instantly receive a personalised playlist across various shows and films, thanks to AI’s ability to analyse and classify visual data. This level of granularity enhances the value of content libraries and improves the overall user experience.
Augmenting Human Processes with AI: Where the Balance Lies
While AI is taking on many tasks traditionally performed by humans, it’s essential to recognise that its role is often to augment rather than replace human expertise. For example, automated video editing tools can handle the basic assembly of footage, but final editorial and creative decisions are still best left to human judgement.
In areas like content tagging and recommendation management, AI can rapidly sift through data and identify patterns that might be missed by a human. However, human oversight is crucial to ensure that these outputs align with creative intent and editorial guidelines. The ideal balance is a collaborative model where AI handles routine, data-heavy tasks, freeing up human teams to focus on strategic and creative decisions.
Challenges in Implementing AI: Overcoming Bias, Accuracy, and Trust Issues
Despite its many advantages, AI is not without its challenges. Algorithmic bias, for instance, is a major concern, as it can lead to skewed recommendations or unintended exclusion of content. Ensuring the accuracy and fairness of AI models is an ongoing challenge that requires continuous monitoring and refinement.
Transparency is also a critical issue. As AI becomes more embedded in media processes, organisations must be transparent about how AI is being used, especially in content recommendation and moderation. Building trust with users and regulators alike will be key to fully realising AI’s potential in the media landscape.
Conclusion: The Future of AI in Media – A Strategic Asset for Growth and Innovation
AI is no longer a distant prospect—it’s here, and it’s already making waves in the media industry. From enhancing user experience with personalised content discovery to driving new revenue through targeted advertising, AI is proving to be a strategic asset that can fuel growth and innovation.
As we continue to explore its potential, it’s crucial to focus on how AI can complement human capabilities, maintain compliance, and support ethical use. By embracing these principles, the media industry can leverage AI to not only enhance current offerings but also pioneer new forms of content creation, distribution, and engagement.
At DTG, we’re committed to leading the way in understanding and deploying these technologies to shape the future of TV. By fostering collaboration and driving innovation, we can ensure that AI’s integration into media is both impactful and sustainable, creating value for all stakeholders.
