AI Radio, HI!

I am Ricardo Gurgel, a Brazilian civil engineer and psychology student, combining sciences to understand markets and mass radio movements. Here, I present simulations I’ve created for a future radio supported by artificial intelligence as its main tool. I originally wrote this post in Portuguese, but this version was lovingly crafted for English-speaking readers. (versão original em português)

By gathering what’s already available in AI—whether free or paid—along with tools that could be easily developed worldwide, and exploring what we can achieve by combining all these resources, we can create a nearly "full AI" radio operation—a real blast! The more I mentally pieced together these AIs, the more I realized how much they could simplify each function in a radio station. This exercise, done in just a few minutes, showed me how close we are to making this a reality. As I wrote, I was able to further expand the boundaries (or lack thereof) of what I now call "broadcasting AIs"—the concept I’m developing.

Hugo, a friend and colleague who worked with me at the DIAL Natal group, used to say: "If you’ve had an idea, chances are someone’s already thought of it before." For now, though, I’ll stick with calling it "broadcasting AIs" as I flesh out this idea.

We’re on the verge of witnessing the birth of the "broadcasting AI manager," who will coordinate the "creative" processes of the AIs involved in radio, including their integration and updates. Let’s break it down into sectors to see how close this already is to becoming reality:

AI-Driven Programming

With guidance on the target audience and solid data input for learning local trends, this AI will handle music curation, selecting what gets the best response based on local demand and eliminating human bias through BIG DATA curation.

Current Development Level:  

• Major players like Spotify already demonstrate that the technology exists; it just needs greater accessibility and customization for urban groups.

  
  

  Disadvantages:  

• It hasn’t yet achieved total precision regarding each city’s culture, but that seems to be just a matter of rapid learning.

• Current costs don’t fully justify a 100% AI-driven functionality, and a skilled programmer can still optimize a lower-cost AI to create excellent programming.

• It will likely reach international markets first, with processes not yet adapted locally.

  
  

  Horizons:  

• Entire networks could create personalized radios for each location, sending data to affiliates with a decoding system for each, offering either unified or customized broadcasts.

  
  

  Advantages:  

• Speed in programming.

• Precision in selection, leveraging massive data to track audience trends, enabling monthly or even daily segmentation.

• Can feed radio networks with different profiles.

  
  

AI-Generated Voiceovers

Packages offering everything from fully AI-generated voices to voices of real announcers enhanced by AI, delivering live-like broadcasts addressing local topics.

Current Development Level:  

• Already in use, with varying quality levels.

  
  

  Disadvantages:  

• Public resistance when it replaces human announcers.

• Difficulty building strong audience connections, as the AI isn’t physically present beyond the studio.

• High-quality options aren’t yet affordable.

  
  

  Horizons:  

• Could enable real-time conversations with listeners, leveraging the impressive knowledge of current AIs.

• Could simultaneously respond to listeners via text while broadcasting.

  
  

  Advantages:  

• 24-hour operation, with the ability to change voice and personality throughout the day based on programming needs.

• In time, audiences might feel genuinely heard and understood by the AI, potentially achieving a level of likability similar to human customer service agents (an experience already seen outside Brazil).

  
  

AI-Created Jingles and Soundtracks

Just as in other fields where images and videos are generated limitlessly, AI excels at creating jingles and soundtracks.

Current Development Level:  

• Systems like Shazam already identify a large volume of AI-generated music, showing we’re on the right path, though final products aren’t yet locally adapted.

  
  

  Disadvantages:  

• A highly skilled artistic director will be needed to guide AI creations, preventing it from merely mimicking other stations.

• With so many options, maintaining focus will be key to avoid constant changes that could hinder building a lasting identity.

  
  

  Horizons:  

• AI could produce financially unattainable sound designs—like choirs and instruments used by major stations—at a much lower cost, with technical ease and minimal human resources.

  
  

  Advantages:  

• Reduced timelines and costs, allowing smaller stations to compete with big players.

AI-Driven Artistic and Commercial Projects

AI will be able to identify each program’s audience, map potential clients, customize commercial materials, and suggest projects and formats with the highest likelihood of success.

Disadvantages:  

• Once again, integrating commercial direction with artistic programming will be crucial for the AI to quickly learn how to generate material that meets both the station’s commercial and artistic needs. The "perfect prompt" will be essential to optimize AI use.

  
  

  Horizons:  

• Rapid material generation to meet urgent needs.

• AI-driven artistic-commercial planning, including budgets, timelines, and goals.

• Use of BIG DATA to suggest promotional boosts.

  
  

  Advantages:  

• Reduced planning time, allowing more focus on event execution and tailored client production.

There are even more existing and developing AIs that I’m fitting into the broader picture of broadcasting operations, but I’ll save those updates for another time. The future is approaching fast, and the question is simple: there’s no stopping the ocean’s waves.

Reflections and Ethics

The advancement of artificial intelligence (AI) technologies has transformed many industries, including radio, with automation gaining traction in functions like voiceovers, music programming, and other operational processes. We should expect to see this first as experiments in countries like the United States, Germany, France, and Japan before it reaches developing nations, but at some point in the future, it will become commonplace. This may present several challenges but also opens doors to new possibilities and paths for professionals in the field. Below, I explore these challenges and potential ways forward for announcers, music programmers, and other radio staff:

Challenges:

1. Replacement of Creative Roles: AI can automate repetitive and even creative tasks, like voiceovers or music programming, raising concerns that announcers and programmers might be replaced by automated systems.

2. Lack of Personalization and Human Touch: Radio has always been a medium tied to human interaction. Announcers and programmers connect with audiences, build a station’s identity, and convey emotion. While efficient, AI may struggle to replicate the authenticity and empathy humans provide.

3. Devaluation of Human Work: Professionals may feel their work is undervalued or obsolete, leading to job insecurity.

4. Need for Adaptation and Training: Radio staff will need to constantly update their skills to keep up with new technologies, which could be challenging for those unfamiliar with advanced tools.

Paths Forward:

1. Adaptation and Upskilling: Rather than resisting automation, professionals can specialize in using AI as a tool to enhance their work. For example, announcers and programmers could leverage AI to optimize music curation, audience analysis, and content creation more efficiently.

2. Focus on Humanization and Connection: AI may be efficient, but it can’t replace the emotion, unique voice, and empathy of a human announcer. Emphasizing the emotional side of communication—like live interactions, interviews, and personalized events—will remain a key differentiator. Announcers can use technology as an ally to focus more on creative and emotional audience engagement.

3. Developing New Content Models: Automation can streamline certain content formats, but it also offers a chance to create more interactive and innovative programming. Music programmers could explore new ways to craft personalized playlists with AI while adding human-curated themes to enhance the listener experience.

4. Exploring New Niches and Formats: Instead of fighting AI, professionals can seek niches that still demand a human presence, such as community-focused shows, live music programs, interactive broadcasts with real-time audience feedback, and content that avoids the standardization AI might bring.

5. Human-Machine Collaboration: Radio professionals can learn to work with AI to boost productivity and content quality. For instance, announcers could use AI to generate faster, more efficient scripts while adding the human touch that makes the final product stand out. AI can provide audience insights, optimize playlists, and personalize experiences, while humans focus on creative areas.

6. Innovation in Advertising and Marketing: With AI, personalized ad campaigns based on listener data become possible, creating new monetization opportunities for stations to offset cost reductions elsewhere. Marketing and ad professionals in radio could specialize in this new personalized approach.

7. Enhancing Live Entertainment Quality: AI can free up announcers and staff to focus on live programming, which requires improvisation, real-time interaction, and audience engagement—skills machines can’t easily replicate.

The World Keeps Turning

While AI-driven automation poses significant challenges for radio and its professionals, it also offers opportunities for innovation and improvement. The key for announcers, music programmers, and other staff will be adaptation. They must upskill, use new technologies to their advantage, and find ways to excel in areas where machines can’t compete—like empathy, creativity, and genuine human connection with the audience.