For nearly a century, recorded music has been used in retail environments to stimulate sales, bolster branding, and influence customer mood and behavior. Due to the cost and complexity of music licensing, many businesses rely on B2B (business-to-business) background music providers to manage compliance, report usage, and distribute royalties. The recent rise of generative AI, however, has led to several startups—including Purilian, Rightsify, and Soundraw—advertising royalty-free, AI-generated background music. While still in early stages, some retailers have started experimenting with AI music, raising questions about labor and economics in the contemporary background music industry. This paper explores the growing use of generative AI for background music by analyzing B2B platforms and their marketing materials. It demonstrates that this phenomenon is an extension of earlier industry logics seeking to minimize licensing fees and maximize control, from Muzak’s in-house recordings in the 1930s to the expansion of production music libraries for commercial use. However, AI-generated background music is unprecedented in its scalability and adaptability, meaning that widespread adoption could reduce demand—and thus revenue—for artists. This use of AI is particularly pernicious precisely because it is in the background, masking the consolidation of economic and creative power in platforms.

In 2022, I experienced the most striking shift in nearly a decade as a B2B background music curator: a marked increase in U.S.-based businesses foregoing Christmas-season holiday music altogether. With no shortage of new recordings, the argued cause was oversaturation: genre distinctions within holiday music output were becoming blurred, and retailers were eager to avoid customer burnout. However, I assume Jonathan Sterne’s assertion (1997) that engagements with programmed music exist beyond “whatever the statistical and scientific rhetoric of marketing research might suggest” and posit motivations eluding such easy and easily sold observations. Specifically, I suggest that considering how well the world evoked by holiday standards aligns with present-day realities in the U.S. provides a pathway into these motivations; in other words, recent trends beg the question, “What outmoded ideals does this music sell alongside goods and services?” Supported by participant-observation while a music supervisor for Mood Media, interviews with former co-workers, and survey results, my presentation examines the past five years of retail-and-hospitality holiday music’s diminishing returns in light of holiday programming strategies in place since the 1990s. I argue that, regarding the nostalgia it promotes and the ideas it normalizes, this programming is no more innocuous in its messaging than post-Reconstruction plantation songs or missionary hymnody. As historically the most in-demand service provided within the U.S. background music industry, holiday programming’s decline exposes not only brick-and-mortar competition post-Covid but also entrenched choices that sustain background music curation’s death knell in streaming’s wake and just ahead of generative AI’s impact.

In her 2025 book The Mood Machine, Liz Pelly identifies a new genre called “Spotify-core” that emerged as Spotify ramped up for a blockbuster IPO. It privileges middle-to-slow tempos, even dynamics, emotional warmth, and calmingly mellifluous vocals in the vein of indie-folk, female-identifying singer-songwriters. These aesthetic qualities make Spotify-core playlists as fitting for commercial background music programming as for foreground music driven by personal taste, prompting streamers like Spotify and Pandora to launch “Soundtrack Your Brand” and “Pandora for Business,” respectively, to compete for additional income with B2B background music industry giants like Mood Media (which acquired Muzak, DMX, and Trusonic in 2012 and Play Network in 2021). While Pelly addresses how shifts from foreground to background music, and vice-versa, impact streaming royalties for content creators, the effects of these shifts upon listeners and listening cultures remain to be considered. For instance, Muzak playlists of the past were constructed to increase productivity among workers and energetic shopping among store visitors; however, Spotify-core – which I conceive of as at-home “neo-Muzak” music – encourages a darker, more reflective mood. In my paper, I ask how ethnomusicologists and adjacent scholars can approach emergent aesthetics that respond to and reinforce mixed attention and attentional drift (background listening) amidst the ubiquity of private listening via earbuds and headphones (foreground listening).