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Writer's pictureInside Audio Marketing

AI and Radio: Parlor Trick? Existential Threat? or Huge Opportunity?

In an article late last year, a radio personality referred to AI as a potential evil, an existential threat to radio. Others are applauding what they see as the potential AI has for enhancing broadcast content quality and creating opportunities for radio’s growth, while others dismiss it as an interesting parlor trick that will have little impact. So, where does the truth lie? My take is somewhere in the middle.


To start with, AI can mean many things. There is traditional AI which has been around for years and enhances task intelligence – basically, it is reactive, learning from data to make decisions or predictions. And then there is generative AI, which is where most of the alarmist rhetoric is focused, because generative means it generates something new that it decides is right or true, based on, or mirroring, data sets.


When it comes to broadcast radio, in my opinion, with the right guardrails, AI has tremendous positive potential for broadcasters. But, to be honest, radio’s current AI hat trick, which is traditional AI, is not that fancy, not that much of a shiny object, but profoundly practical. Rather than replacing human broadcast talent with machines, AI’s current best use in radio is as a useful tool operating as the lighter fuel on the fire of the targeted advertising the internet made possible. AI can leverage its nimble learning capabilities around listener habits, enhancing precision marketing to personalize ads on the fly and in a way that is relevant to the user’s specific audio environment – all of which increases CPMs and monetization efforts.


Traditional AI can help broadcasters more accurately understand their clients and bridge what makes a station a good venue for the client and the gaps in the client’s current advertising. It also has multiple applications in creating more compelling sales materials and presentations, so broadcasters don’t need to reinvent the wheel each sales cycle with each new client and can skip those multiple, endless meetings used to pull out client needs.


But I would also like to focus on where I am seeing new alchemy every day, and not just a hat trick. That is in the machine learning-driven techniques used in our DTS Auto Stage platform, which offer the potential of enduring and dramatic change to broadcast radio’s benefit. Over the years, we have enabled our platform to globally connect over 50,000 radio stations, as it ‘listens’ to these stations in a deep way that enables understanding well beyond generic labels like rock and country. And this is so important because these genres can mean different things in different states (or countries). For example, country means something very different in Austin than it does in Topeka, Kansas.


So, the platform’s machine learning technique looks at the characteristics of the music, not just the genre, but the actual playlists, logs the songs and contextualizes them, adds in metadata and all the behavior preferences used to characterize and describe the music, and then builds a profile of what the radio station actually is, which, in many ways, can be more precise than even the radio station knows.


Why is all this useful? Because – and this is where we get into the potential of generative AI – it means a future where we can detect the nuanced characteristics that connect station and listener with profound relevance. For example, let’s say I am on a road trip and I am a big fan of David Letterman, and I just drove through Des Moines and the station there is doing a live interview with him, the platform automatically switches me to, or recommends that station; or maybe if I have a specific interest in a writer or a sports team – the platform will know my passions and push radio content that is, in real-time, relevant to me.


This is just one positive example; there are many more. So, on balance, I am bullish on AI, machine-learning, and its impact. I think about generative AI’s potential for medicine, and how, with its limitless data set, there may be a not-so-far-off future where it will be able to detect skin cancer. This is a very good thing. And, no, AI in radio is not going to cure cancer, but I have to think if it has that much power for good in medicine, if it's deployed with the right intent, it will make radio much more relevant, entertaining, engaging, and meaningful to its audience, and more valuable to the advertiser.


We may not know exactly what that AI radio secret sauce is yet, but if radio is ready and willing and inquisitive, they're going to find the application. And it's going to make radio that much more powerful.


Joe D’Angelo is the Senior Vice President of broadcast radio and digital audio for Xperi. Based in Columbia, Maryland, he is responsible for the global broadcast radio business and product development. Joe joined Xperi in 2015, by way of acquisition, as one of the founders of iBiquity Digital Corporation, the company behind HD Radio technology. Joe manages resources around the world committed to ensuring broadcast radio has a rich and vibrant offering in today’s digital broadcast and connected world.

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