AI Generated Music on the Charts: With Dee Peterschmidt, Industry Deals, and a Pioneer’s Perspective

Overview

AI-generated music has moved from novelty to a trending force, with platforms like Suno and Udio producing huge volumes of songs and viral hits such as Zanaya Monet’s work. The episode tracks turning points, including Beanie Pray’s TikTok viral AI song, the Velvet Sundown project, and Zanaya Monet’s reportedly multimillion-dollar traditional-label deal, revealing how AI is shaping genres and discovery.

Interviews with Billboard journalist Kirsten Robinson and pioneer Laurie Spiegel, plus industry voices like Imogen Heap, explore the tensions around compensation, licensing, and what “authentic” musical expression means when algorithms participate in the creative process.

AI Music Boom and the Players

The episode opens with Flora Lichtman and Dee Peterschmidt examining AI-generated music's growing footprint, from meme songs to chart presence. Dee notes that AI songs have begun to surface on mainstream charts and in production sessions, prompting questions about who profits and how rights are managed. A key turning point in public awareness is Zanaya Monet, an AI-generated avatar created by Talisha Nikki Jones, whose songs climbed charts and led to reports of a multimillion-dollar deal with Hallwood Media. The royalties reportedly flow to Jones, who uses Zanaya Monet as a persona to express poetry through song, with a manager guiding the project. This signals a shift in how AI personas might function in the music industry, potentially enabling experimentation in new genres.

“I think Zanaya Monet was a real turning point.” - Kirsten Robinson, senior writer at Billboard

Viral Trends, Niche Genres, and the Sound

Robinson describes additional inflection points, including Beanie Pray’s A Million Colors on TikTok and the Velvet Sundown project, which combined AI-generated music with AI-generated images, capturing online attention. These cases illustrate how AI can drive niche genres—gospel, country, and retro-doo-wop—by leveraging formulaic structures that AI can emulate convincingly, even if the resulting sound is not yet indistinguishable from human-made music. A French study cited in the piece claims that 97% of listeners cannot reliably tell AI from human songs, underscoring how consumer perception can obscure the source of music in-stream.

“A million colors” and Velvet Sundown showed how fast AI content can spread online, raising questions about authorship and licensing. - Kirsten Robinson, senior writer at Billboard

Artist Voices, Rights, and Compensation

The episode turns to artists and songwriters who are engaging with AI tools in professional settings. Imogen Heap, a longtime technologist-musician, speaks to balancing exploration with fair compensation, warning about training data used by AI models if rights holders aren’t fairly compensated. The conversation highlights a broader industry concern: models trained on copyrighted material could threaten the value of human-created works if licensing and payment are not properly addressed. The conversation also notes that many in the industry are using Suno in writing sessions, suggesting AI contributions are already present in songs that may eventually reach the Hot 100.

“Imogen Heap has always been on the cutting edge, leaning in, but she is still very concerned about models that train AI music models on works like hers without any compensation.” - Kirsten Robinson, senior writer at Billboard

Tech Giants, Labels, and the Business Trajectory

The discussion shifts to the business landscape: Suno, Udio, Google’s Lyria 3 and Producer AI, and the evolving role of major labels. Once poised to sue AI music companies, the industry has begun licensing and partnering, driven by shareholder pressure in publicly traded companies to innovate and capture value. Dee notes that startups have dominated the early AI music space due to the technical difficulty of generating music, with Google and others entering with competing models. The show suggests the next year could bring more licensing deals, remixer capabilities at scale, and more AI-assisted creative tooling in professional studios.

“There’s so much shareholder pressure to innovate and capture value, and licensing is part of that shift.” - Kirsten Robinson, senior writer at Billboard

Historical Perspective: Laurie Spiegel and Algorithmic Music

The episode closes with an interview with Laurie Spiegel, a pioneer of electronic and algorithmic music. Spiegel reflects on early resistance to computer music, the perception of computers as oppressive, and her belief that technology is a deeply human endeavor. She discusses how early experiments with Bach-inspired harmonic progressions fed into later algorithmic tools and emphasizes that authentic musical expression arises from inside the artist, not merely from the tool. Spiegel also notes the evolving nature of interaction with AI, arguing that prompt-writing is an emerging art form but that the visceral, tactile act of musical performance remains central to self-expression.

“There was a lot of heavy anti computer sentiment back then because computers belonged to the most oppressive of organizations, only they weren’t Personal computers yet.” - Laurie Spiegel, electronic-music pioneer

The segment also mentions Music Mouse, Spiegel’s 1986 software, which has been re-released and is described as an interactive instrument that users can experiment with to explore musical ideas, reflecting the ongoing interplay between human creativity and software tools.