The audio industry has experienced a dramatic evolution , driven by the rise of streaming, on-demand audio, and the growing popularity of podcasts. Now, with the rapid advancements in artificial intelligence (AI), the audio sector is facing a new wave of transformation. Technologies like generative AI (GenAI), machine learning (ML), and natural language processing (NLP) are accelerating change across industries, including media.
A recent report by egta (international trade body for multiplatform TV and audio businesses) focuses on concrete case studies, showcasing how radio and audio companies are leveraging AI to enhance creativity and sales. From AI tools for automated spot creation to AI DJs delivering live content, radio companies are integrating AI into their operations. Technologies like text to-speech, voice cloning, and AI-driven content curation are helping broadcasters provide personalised audio experiences. AI is also playing a crucial role in optimising sales strategies, optimising brand safety, and improving contextual targeting for advertisers. Key outtakes from the report are below:
AI for audio spot creation
AI can be very powerful for audio spot creation; the process that previously took days can now be almost instantaneous. Spots can be created directly during a meeting , allowing for rapid prototyping of audio campaign ideas and co-creation. There are different levels of adoption of this technology; a significant push is the automated process that has a self-service component, especially for smaller clients. It is an ideal tool that puts the creation of audio ads on par with social media in terms of cost-efficiency, speed, user-friendliness, and accessibility.
Dynamic Creative Optimisation (DCO), enables advertisers to create customised audio ads that respond to real-time data and context. DCO utilises preset scenarios and data sources - like weather conditions, sports updates, or traffic reports - to dynamically adjust media plans and ad content. This means audio ads can be tailored on the fly to resonate with specific audiences, enhancing relevance and impact.
AI for audio content creation
AI can assist in audio content creation. Voice cloning, and text-to-speech (TTS) technologies, offering a wide range of opportunities for both creative and commercial uses. AI can assist in generating and enhancing audio content, opening new opportunities for creators, brands, and industries. AI models can generate music, sound effects, and even whole programming segments and podcasts on a given topic. AI DJs are becoming more common, often filling in gaps where there was previously just music programming but also taking on co-hosting roles together with their human counterparts.
AI Text-to-Speech technology converts written text into natural-sounding speech. Recent advancements have significantly improved the quality, making it hard to distinguish between AI-generated and human voices. Companies can clone brand ambassador voices for marketing, customer service, or digital assistants. Voice cloning allows broadcasters to automate parts of their programming. For example, a cloned voice of a popular host could deliver news updates, weather, or even entire segments when the host is unavailable, providing consistency in voice and style. Some broadcasters use voice cloning to offer personalised content to listeners, such as personalised radio shows, greetings, or responses, all voiced by a cloned personality.
AI for content curation
AI has become a part of audio content curation for both streaming services and broadcast radio stations. AI systems analyse listener data, including geographical location, listening history, and even inferred emotional cues, to generate playlists that resonate with specific audience segments. Some audio companies, like iHeart in the U.S., are using AI to create detailed taste profiles, optimising the listening experience for individual listeners and demographic groups. By leveraging machine learning, radio companies can offer more dynamic and relevant programming, blending the personalisation typical of streaming services with the traditional reach and immediacy of radio broadcasting. This shift enables a deeper connection with audiences, making audio content more engaging and customised than ever before.
AI for sales optimisation and audience insights
AI offers advanced tools that help companies understand their audiences more deeply. By analysing listener data, AI enables precise audience segmentation, creating listener personas, allowing advertisers to target the right demographics with personalized ad placements. AI can also analyse the context and help dynamically place most suitable ad based on content, sentiment etc. This approach leads to higher engagement and improved conversion rates. AI can easily pull together different types of datasets such as panel data from audience measurement combined with other surveys and behavioural data allowing to then build custom data sets that might be helpful in the campaign planning. While many of these AI applications are still in the testing phase, radio and audio companies are actively exploring their potential.
AI for brand suitability and contextual targeting
AI can analyse the context, tone, and overall sentiment of content, ensuring that ads are placed in environments that align with a brand’s values and avoid harmful associations. This more advanced approach provides a deeper understanding of the content, beyond just the words used, and enables more precise contextual targeting. Contextual targeting is gaining relevance with the eventual demise of cookies and is something especially agencies are looking into and are already getting from other video-based media. AI also allows for real-time monitoring, helping brands adjust their strategies and reduce risk.
AI can monitor and analyse thousands of podcasts, applying the GARM (Global Alliance for Responsible Media) brand safety floor and custom frameworks tailored to specific brand needs. The platform not only enhances brand safety but also boosts content discovery by ensuring alignment with a brand’s values.
AI for attribution and analytics
Through advanced AI tools, stations can now transcribe and index everything said on-air 24/7, enabling sales teams to quickly search for specific moments and verify when content was aired. AI can also summarize entire campaigns by identifying key moments based on specific keywords or phrases mentioned during broadcasts, offering more accurate insights into ad performance.
AI is a powerful way to automate airchecks as well as to create analytics around all of the ad occurrences a sponsor/ advertiser receives in programming, beyond just spots (live mentions, product placement, naming rights, presenting sponsorships, promos, and more). The software allows for ad-hoc searches (like “Google” for radio or TV station content) as well as proactive monitoring and campaign recapping. It’s a powerful tool for quantifying and taking credit for the “earned media” or added value (additional exposure that advertisers receive but aren’t always quantified).
AI-powered attribution solutions work by capturing everything said on air and cross-referencing it with real-time website engagement data from advertisers. By tracking when specific ads or sponsor mentions occur, AI tools can combine this data with the advertiser’s site metrics (like website visits and engagement). This allows radio stations to demonstrate the direct impact of radio on website traffic. It also provides insights that help optimize campaigns through testing different variables, such as creative types or time slots, ensuring better results for advertisers.
Summary
AI is improving the audio industry by streamlining processes, enhancing creativity, and offering new opportunities for personalisation. Its applications range from automated spot creation, which significantly reduces production time and costs, to dynamic creative optimisation that allows for hyper-targeted and contextually relevant ads. AI-generated audio content, including AI DJs and voice cloning, is reshaping traditional broadcasting, enabling continuous programming with lifelike synthetic voices. These advancements, however, come with challenges around authenticity, ethical concerns, and the risk of losing the unique emotional touch provided by human hosts. Balancing technological innovation with ethical standards and transparency remains a critical focus, especially as AI’s capabilities continue to evolve. AI, while transformative, is a tool that should enhance the strengths of traditional radio and digital audio, providing opportunities for more personalised, efficient, and innovative content without compromising ethical values.
You can download the full report by clicking the link below.