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Phonorecords V Settlement Proposal Emerges: Major Labels, NMPA, A2IM, and Others Say the Existing Rates ‘Should Not Be Amended Except for Continuing Inflation Adjustments’
The major labels, the NMPA, and others have reached a settlement covering stateside mechanical rates for physical formats and permanent downloads across 2028 and 2032. But the proposal, which would leave the existing Phono IV rates in place except for an annual inflation adjustment, is already eliciting criticism.  The majors and the National Music Publishers’ Association (NMPA), along with the Nashville Songwriters Association International (NSAI), the Music Artists Coalition, and the American Association of Independent Music (A2IM), just recently informed the Copyright Royalty Board of their settlement — and DMN was granted first-look access. The current Phono IV rates, also extending to ringtones, “should not be amended except for continuing inflation adjustments to the rates for physical phonorecords and permanent downloads.” Beyond having the final rate-setting say, the Copyright Royalty Judges arrive at those annual adjustments by calculating based on Consumer Price Index movements. For 2026, the physical and permanent download rate is “13.1 cents [per work] or 2.52 cents per minute of playing time or fraction thereof, whichever amount is larger.”  In other words, though the yearly inflation bump would drive modest physical- and download-rate growth through 2032 as outlined, it wouldn’t deliver a material compositional royalties boost. 

 

The Royalty Registration Checklist: A complete checklist to global rights administration, metadata accuracy, and capturing 100% of your master and publishing royalties.
In the modern music industry, your music can be played millions of times. Still, if your administrative foundation isn’t solid, that revenue either stays in the platform's hands or gets lost in “black box” accounts.  If you are not correctly registered with the appropriate organizations, the money your music generates remains “unclaimed.” Without the right digital paper trail, you cannot claim what you are rightfully owed.  Use this checklist before your next release goes live to claim every dollar that rightfully belongs to you. See Examples below:
1. Performance Royalties (PRO)  US: Register with ASCAP or BMI (writer + publisher side)

2. Mechanical Royalties Collects money when your song is played publicly — radio, streaming, live sets, TV, background music in venues.Paid out for reproduction of a composition — streams, downloads, physical sales (vinyl, CD, cassette).  US: Register with The MLC (Mechanical Licensing Collective) — mandatory for US streaming mechanicals. 

3. Neighboring Rights and Master Royalties  Separate from songwriter royalties — this pays the performer and rights holder of the actual recording, not just the composition.  US: Register with SoundExchange (covers non-interactive digital platforms such as SiriusXM, Pandora, and online radio stations)

4. Publishing Administration  If you write your own music and don’t have a publisher, someone still needs to actively chase royalties across territories and DSPs on the composition side. Decide: self-administer or use an admin service (there are several — compare fees and territory coverage before picking one).
Confirm your publishing entity is registered with your PRO as both writer and publisher, if applicable.
Set a calendar reminder to audit unclaimed/unmatched royalties every quarter

5. Double-Check Your Metadata  Bad metadata = royalties sitting unclaimed in a black box, sometimes indefinitely. ISRC: assigned to every recording (unique per version. Don’t reuse across remixes, edits or distinct remasters). All songwriters, producers, and publishers are listed correctly, with correct splits. Cross-check everything: Ensure your distributor, PRO, and MLC/CMO details are identical. 

 

US Register of Copyrights continues The MLC’s designation as the statutory Mechanical Licensing Collective 
The US Register of Copyrights has continued the designation of The Mechanical Licensing Collective (The MLC) as the statutory collective responsible for administering the blanket compulsory mechanical license for eligible streaming and download services in the United States. The decision follows the Register‘s first periodic review of The MLC‘s designation, as required by the Music Modernization Act (MMA). The rule, published in the Federal Register on Wednesday (June 3), determined that The MLC “continues to meet each of its statutory criteria for redesignation”. “Overall, the administration of the MMA‘s blanket mechanical license has been a great success for publishers, songwriters, and DMPs,” the Copyright Office said in its decision.  Since beginning operations in January 2021, The MLC has enrolled nearly 90,000 members, built a public database containing data for more than 54 million songs, and reached total royalties distributed of nearly $4 billion. The next periodic review of The MLC‘s designation is expected to begin in January 2029.

 

US senators revive bill that would force AI-generated audio, video and images to carry labels
A bipartisan group of US senators has reintroduced legislation that would require AI-generated audio, video and images to carry disclosures identifying them as artificially generated. Its backers include SAG-AFTRA, the Songwriters Guild of America, Music Creators North America and the Society of Composers and Lyricists.  The AI Labeling Act would require providers of generative AI systems to attach a visible disclosure to AI-generated content, along with a machine-readable disclosure recording the system used and the time it was created. Large social media, search and content-sharing platforms with at least 10 million monthly US users, or more than $1.5 billion in annual revenue, would also have to flag that content and would be barred from stripping out the disclosures, under the proposal.  Any AI chatbot would separately have to tell users they are interacting with an artificial intelligence system. The Federal Trade Commission would enforce the requirements, and the National Institute of Standards and Technology (NIST) would convene a working group to set technical standards for labeling and detecting AI content.

 

Suno’s latest legal opponent fought the tobacco industry – and won a quarter of a trillion dollars
Suno and Udio have a new adversary in their copyright fight with independent musicians: Hagens Berman, the law firm that took on the tobacco industry.  The firm has joined forces with Delgado Entertainment Law to represent independent artists whose recordings were allegedly copied without permission to train the two companies’ AI music-generation models. The firm’s arrival raises the stakes for Suno and Udio.  Hagens Berman represented 13 US states in what it describes as the largest recovery in litigation history, a settlement with the tobacco industry that the firm values at $260 billion. “Independent artists and producers represent the heart and soul of the music industry, and in the landscape of AI, they stand to lose the most,” said Berman, the firm’s managing partner. The case Hagens Berman has joined was first filed in June 2025 by country musician Tony Justice and his label, 5th Wheel Records.  Justice, a full-time truck driver whose song Last of the Cowboys has been streamed more than 8 million times on music platforms such as Spotify, sued both companies in June last year, in separate complaints against Suno in Massachusetts and Udio in New York.  That lawsuit argued that “rather than simply license these copyrighted songs like every other tech-based business does, Suno/Udio elected to simply steal the songs and generate AI-soundalike music at virtually no cost.” Suno did not deny stream-ripping music from YouTube, but its lawyers argued the practice is not illegal under the DMCA. The lawsuits against Suno and Udio seek damages for affected artists and an injunction to end what the firm calls “massive and ongoing infringement” of their rights.

 

NMPA Releases Latest Per-Stream US Publisher Payouts from Spotify, YouTube, Apple, and Amazon
NMPA president and CEO David Israelite unveils the latest per-stream songwriter and publisher payout across Spotify, YouTube, Apple, and Amazon.  In a post on LinkedIn, National Music Publishers’ Association President and CEO David Israelite unveiled the latest per-stream songwriter and publisher payout. These numbers represent both mechanical and publishing sub-licenses across Spotify, YouTube Music, Apple Music, and Amazon Music. Notably, YouTube is not at the bottom of that barrel.  “How much is 1 million streams worth to the songwriters who make these businesses possible? And remember—most songs are written by 4-5 songwriters, so this amount is split among all of the writers and publishers,” Israelite wrote, noting in an email to Digital Music News that this data from the Mechanical Licensing Collective (MLC) is only inclusive of the U.S., across both mechanical and performance payouts. Specifically, Spotify’s free, ad-supported tier saw a payout of $800, (.0008 per stream for publisher and writers combined) while individual paid Spotify accounts raked in $1,346 (.001346 per stream) Individual YouTube accounts led to a payout of $2,159 (.00216 per stream); individual Apple accounts amounted to $2,367 .00237 per stream), while individual Amazon accounts led to a payout of $3,743 (00374 per stream). Already, A&R representatives and others across the industry are speaking out about those numbers, noting that they represent broader issues across the royalty payout structure.

 

Music streaming services targeted as Texas Attorney General launches payola investigation
The Attorney General of Texas has launched an investigation into payola in music streaming. He wants to know if any music companies have “undisclosed financial arrangements” with the streaming services that result in their music being unfairly prioritised, and which violate Texas state law. Allegations of payola in music streaming are being put in the spotlight by the Attorney General of Texas, Ken Paxton, who wants to know if there are any “undisclosed financial arrangements” between the streaming services and music companies that allow specific artists or tracks to “boost visibility, playlist placement or recommendation rankings” in violation of the state’s laws. As a statement from Paxton’s office explains, “payola is the practice of receiving compensation in exchange for preferential promotion without proper disclosure”. In the US, the most famous form of payola involved labels or their agents paying or otherwise bribing programmers at radio stations so that they would playlist specific tracks. Such conduct is “prohibited by federal law”, Paxton’s statement reminds us. But are the streaming services themselves involved in any of that dodgy conduct? And if so, does that involve secret envelopes of cash and other freebies for influential executives, as in the radio payola heyday? Then there’s Spotify's controversial Discovery Mode, where independent artists and labels get an algorithmic boost in return for accepting a 30% discount on royalties. That’s not done in secret at all - the marketing scheme has its own website - but some argue that it’s basically a modern form of payola. It’s not clear how much of all this will be covered by Paxton’s investigation. However, with plenty of allegations of dodgy music marketing doing the rounds - and ongoing criticism of things like Discovery Mode - it should be interesting to see what the Texas AG uncovers. 

 

iHeartMedia cuts radio jobs across US as it targets $50m in annual cost savings (report)
iHeartMedia has begun another round of layoffs across its radio division.
The cuts began on Tuesday (June 23) and rolled out across stations in markets across the country through the week, according to RadioInsight, which has tracked the named exits.  iHeartMedia framed the cuts as part of a change to how it programs its stations, in a memo sent to staff by Multiplatform Group CEO Ann Marie Licata and Chief Programming Officer Tom Poleman. “As the number one company in audio, our business model is to build engaged relationships with listeners and then monetize those relationships,” the iHeartMedia executives wrote.  They said iHeartMedia was “now taking an important step that will move us further into the future: Evolving how we program our stations to reward and develop our leading and up-and-coming talent.”  The memo pledged that “Guaranteed Human” would stay “at the core of everything we do,” and that “real voices and real talent strengthen our real connection and commitment to our communities.”  On the cuts themselves, Licata and Poleman wrote that the changes were built around speed for advertisers. The layoffs are tied to a cost-cutting program iHeartMedia outlined alongside its first-quarter results in May.  The company said it anticipated a further USD $50 million in annualized cost savings this year, to begin in the second half of 2026.

 

NO FAKES: Senate panel backs bill that could cost platforms $750k per AI deepfake
The US Senate Judiciary Committee has advanced the NO FAKES Act, the bipartisan bill that would create a federal right protecting Americans’ voice and visual likeness from AI-generated deepfakes.  The committee passed the bill unanimously by voice vote on Thursday (June 18), according to Deadline, which noted that “three Republican senators — Mike Lee, Ted Cruz, and Eric Schmitt — raised First Amendment concerns”.  Clearing the committee sends the bill toward a vote by the full Senate, after which it would still need to pass the House of Representatives and be signed by the President before becoming law. Penalties under the bill are tiered: $5,000 per work for an individual, $25,000 per work for a company that creates or distributes a replica, and up to $750,000 per work for an online service that fails to comply. 

 

AI Could Use as Much Water as 1.3 Billion People by 2030, U.N. Report Warns
he water used by artificial intelligence is expected to equal the needs of 1.3 billion people by 2030—threatening natural resources for billions around the world. That’s according to a new report from the United Nations University Institute for Water, Environment and Health (UNU-INWEH) which quantifies the carbon, water, and land footprints of AI's electricity use around the globe. The report finds that AI’s environmental cost is often mismeasured—focusing solely on carbon emissions. However, cooling and generating power for data centers comes with a “water footprint,” while the energy infrastructure and supply chains to build the data centers have a “land footprint.” These are important factors to consider, the report says, when analyzing the stressors a region might be facing due to data centers. By 2030, the report finds, global data centers powering artificial intelligence are projected to consume 945 terawatt-hours of electricity. This is nearly triple the combined annual electricity use of Pakistan, Bangladesh, and Nigeria—countries that together are home to more than 650 million people. The water footprint of data centers is projected to equal the basic domestic water needs of all 1.3 billion people in Sub-Saharan Africa for a year, while their land footprint could exceed 5,590 square miles.But switching to cleaner sources of energy isn’t as simple as it sounds. Minimizing one footprint could come at the expense of magnifying another, researchers say. For example, switching from coal to bioenergy cuts electricity’s carbon footprint by 70%—but increases its water footprint more than 30-fold and its land footprint 100-fold. For a number of communities around the globe, AI is already using up significant energy resources. In 2025 alone, data centers consumed an estimated 448 terawatt-hours of electricity, the report found—more than the country of Saudi Arabia. In many cases, this excessive energy use comes at a cost to those who reside near them. 

 

Is Anyone’s Music Safe? Newly Identified ‘Giant Datasets’ Containing Millions of Songs Raise Fresh Questions About Music AI Training Processes
Are gen AI companies actively developing their music models with the same collections of copyrighted tracks? And despite ongoing discussions about free-for-all training, is this process far more systematic than we’ve been led to believe?  These and other pressing questions are taking center stage following an investigative report from The Atlantic’s Alex Reisner, who identified “four giant datasets of songs that are being shared within the AI-development community.” Unsurprisingly, even in light of the noted report, we don’t have a concrete answer. Said report pinpointed four training datasets consisting of north of 22 million recordings between them – including two collections clocking in at closer to 100,000 recordings apiece, one containing 9.7 million songs, and the last with roughly 12.3 million tracks. Google and Stability AI have reportedly utilized tracks from one of the 100,000-song datasets, the Free Music Archive. Owing to “the industry’s secrecy around training data, we don’t currently know who has used the others” – though all four are said to have been “downloaded thousands of times” in total, per the report.