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Recent developments show AI‑generated tracks are at the center of a growing crisis in music streaming. The U.S. Copyright Office has opened a public inquiry into music streaming fraud, seeking input on how bot farms and AI‑generated tracks are siphoning money from the royalty pool. A high‑profile case illustrates the scale: Michael Smith uploaded hundreds of thousands of AI‑generated songs and used thousands of bot accounts to stream them, collecting about $10 million in royalties before pleading guilty to wire fraud. Major labels are responding; Universal Music Group sued DistroKid over an “AI slop pipeline,” and IFPI launched a Streaming Integrity Initiative focusing on verification and content vetting. Platforms report massive AI volume—Deezer sees 90,000 AI tracks uploaded daily, while Spotify now adds AI credits and “AI personas” to flag AI‑created artists. Meanwhile, regulatory bodies are tightening rules: Australia’s ARIA bans purely AI‑generated music from its charts, labeling only AI‑assisted works, and Spotify’s AI personas are excluded from algorithmic recommendations. Legal pressure mounts on AI firms: Suno faces lawsuits from Universal and Sony for allegedly ripping off over 60,000 copyrighted recordings, though it argues its training data falls under fair use. Suno’s latest v6 model, trained exclusively on licensed music from Warner Music Group and others, includes revenue‑sharing for participating artists, signaling a shift toward licensed‑AI collaborations. The Copyright Office notes U.S. streaming revenues total roughly $9.5 billion (about $22 billion globally), and fraud threatens to shrink these payouts for honest creators. Together, these moves highlight why AI‑generated music matters—its potential to distort royalty streams and copyright enforcement—and what to watch next: further legal actions, industry‑wide licensing frameworks, and evolving platform safeguards to curb fraudulent AI‑driven streams. [[1, 2]]