Elvis left the building in 1977. According to a new federal lawsuit, his songs never left Anthropic’s servers.

On Friday, October 23, 2026, the companies that own Elvis Presley’s music sued Anthropic, the maker of the Claude AI models, in federal court in San Francisco. They say Anthropic copied 274 Presley songs to train Claude without permission or payment. They want up to $150,000 per song. Do the math and you land at about $41.1 million.

This isn’t just a celebrity headline. It’s one more test of the question every business using AI should be asking: who owns what goes into these models, and who pays when it comes back out?

What the Lawsuit Says

The plaintiffs are led by Authentic Brands Group, the licensing company that controls much of Presley’s intellectual property. They’re joined by other companies, trusts, and individuals who own rights in his music. Their lead lawyer is Richard Busch, the attorney who won the “Blurred Lines” case for Marvin Gaye’s family.

Here’s what the complaint alleges, as reported by the press:

  • The catalog. 274 songs, lyrics and compositions, from deep cuts to “Can’t Help Falling in Love,” “All Shook Up,” “Don’t Be Cruel,” “A Little Less Conversation,” and “Return to Sender.”
  • The copying. The songs were allegedly placed in a central library and copied again each time Anthropic trained a newer Claude model. One copy becomes many.
  • The output. Claude allegedly still reproduces the material on request, even after Anthropic added guardrails against generating song lyrics. Asked to recreate songs “for a modern audience,” it allegedly produced something close to the originals.
  • The intent. The plaintiffs say Anthropic knew its guardrails didn’t work and kept going anyway. That’s the hook for willful infringement.

They’re asking for statutory damages for all 274 songs, a permanent injunction, and an order that Anthropic destroy every unauthorized copy. Busch put it bluntly: Anthropic “has built its entire business model based on copyright infringement at a scale never seen before.”

Anthropic says it disagrees and will defend the case. It has long argued that training AI on copyrighted material is fair use. None of these allegations has been tested in court yet.

The Legal Fight: Inputs, Outputs, and Fair Use

Let’s not overcomplicate this. The case really asks two questions.

  1. Was copying the songs into the training data infringement? Copyright gives the owner the exclusive right to make copies. Anthropic’s answer is fair use, the doctrine that allows some unlicensed use when it’s “transformative,” meaning it serves a different purpose than the original. In other words: did Anthropic use Elvis’s lyrics to teach a machine how language works, or to build a jukebox that never pays royalties?

We have an early clue. In the 2025 authors’ case against Anthropic, Bartz v. Anthropic, Judge William Alsup ruled that training on lawfully purchased books was fair use. But he also ruled that building a permanent library out of pirated copies was not. That’s why the Elvis complaint leans so hard on the “central library” that was copied again and again. The plaintiffs are aiming squarely at the part of the Bartz ruling that went against Anthropic.

  1. Does Claude spit the songs back out? This is the stronger-sounding claim for the plaintiffs. Fair use arguments about training get much weaker if the model can be coaxed into reproducing the lyrics on demand. A tool that hands users near-copies of “Return to Sender” looks less like a student and more like a photocopier.

Why the $150,000 number matters. Under the Copyright Act, a copyright owner can elect statutory damages instead of proving actual losses. The range runs from $750 to $30,000 per work, and up to $150,000 per work if the infringement was willful. That’s why the complaint spends so much energy on Anthropic allegedly knowing its guardrails failed. Willfulness is the difference between a $206,000 floor and a $41.1 million ceiling.

One more thing worth noticing: as reported, this is a copyright case, not a right-of-publicity case. Tennessee’s ELVIS Act, passed in 2024, protects an artist’s voice and likeness against AI imitation. It doesn’t appear to be part of this lawsuit, at least not yet.

Elvis Isn’t the First in Line

The King is joining a crowded room. At least half a dozen related cases are already pending in the same San Francisco federal court.

When Case What happened
Oct. 2026 Presley rights holders v. Anthropic 274 songs, about $41.1M in statutory damages sought
Sept. 2026 Jason Isbell and other artists v. Suno Musicians allege an AI music generator lets users imitate their identities and styles
2026 Sony Music Publishing, Warner Chappell, BMG v. Anthropic Publishers allege lyrics and sheet music (Beatles, Taylor Swift, Michael Jackson) were used to train Claude
2026 Round Hill, Reservoir Media v. Anthropic and Suno More publishers join the fight
July 2026 Bartz v. Anthropic settlement approved $1.5 billion to authors, about $3,000 per book, for 400,000+ pirated books
Oct. 2023 Universal Music, Concord, ABKCO v. Anthropic The first lyrics case (Katy Perry, Gloria Gaynor, Rolling Stones); expanded in January 2026

The pattern is clear. The $1.5 billion Bartz settlement, the largest copyright settlement in U.S. history, showed that these claims carry real money. Every rights holder with a large catalog is now doing the same math the Elvis team did.

What This Means for Your Business

You probably don’t own 274 hit records. But you may own product manuals, training videos, marketing copy, software code, or photographs. Here’s what founders don’t realize until it’s too late: the same rules that let Elvis’s rights holders demand $41 million apply to your work too.

  1. Register your copyrights. Early. Statutory damages and attorney’s fees are generally available only if the work was registered before the infringement began, or within three months of publication. Without registration, you’re stuck proving actual losses, which is hard and expensive. The Elvis plaintiffs can ask for $150,000 a song because their paperwork is in order. Is yours?
  2. Know where your content lives. If your work is on the open web, assume it’s been scraped. Review your website terms, consider technical opt-outs, and keep records of when and where you published.
  3. Read the fine print on your AI tools. If your team uses AI to write lyrics, jingles, ad copy, or code, find out what the vendor promises about indemnification. If Claude can allegedly reproduce “Don’t Be Cruel,” ask what your tool could reproduce under your company’s name.
  4. Don’t publish AI output blind. Run AI-generated content through the same review you’d give a freelancer’s work. “The robot wrote it” is not a defense to infringement.
  5. Watch the courts. The line between fair-use training and infringing copying is being drawn right now, case by case. The rules a year from now may look very different than today.

The Bottom Line

Elvis’s rights holders are in a strong position for one reason: they did the boring work decades ago. The songs are registered, the ownership is documented, and the damages math is simple. AI didn’t create that leverage. Good IP housekeeping did.

If you’re building it, you should be protecting it. At Martin IP Law Group, we help businesses register their copyrights, audit their IP, and set sensible rules for using AI tools. If you want to know where your content stands, give us a call. We’ll be watching this case closely, and we’ll keep you posted.

This post is for informational purposes only and does not constitute legal advice.

Sources

Every IP lawyer has heard some version of this story from a founder: we shared our technology with a bigger, better-connected partner during “partnership talks,” the deal fell apart, and a few years later our idea showed up inside someone else’s billion-dollar company. Usually the facts are murkier than the founder’s telling. But when the allegations land in a filed complaint, with a granted patent number attached and a state economic development agency named as a defendant, the story becomes a useful case study regardless of how it ultimately resolves.

That is exactly what happened on March 5, 2026, when Barbara Bessolo, founder and CEO of the Carmel, Indiana-based startup DynamoEdge, filed suit in Marion Superior Court against Michael Andretti, Andretti Autosport Holding Company, Andretti Global, the Indiana Economic Development Corporation (IEDC), former IEDC chief innovation officer David Roberts, Indy Autonomous Challenge founder Paul Mitchell, contractor 9-12 LLC, Palantir Technologies, the Applied Research Institute/Indiana Innovation Institute, and more than a dozen additional individuals and entities.

The technology at the center of the dispute

DynamoEdge builds real-time “edge AI” for motorsports telemetry — software designed to process vehicle sensor data on the fly and predict performance outcomes and equipment failures before they happen. The complaint centers on U.S. Patent No. 12,518,219, which DynamoEdge filed for in May 2022 and which was granted in early 2026, covering real-time processing of vehicle sensor data. Bessolo also claims common-law rights in the phrase “Predicting the Unpredictable,” which she says DynamoEdge has used as a slogan since around 2021.

How the relationship allegedly unraveled

According to the complaint and subsequent reporting, the story begins in October 2020, when DynamoEdge entered partnership discussions with Andretti. Bessolo alleges Andretti agreed to rebrand the company as “AndrettiEdge” and brought her into investor meetings with AT&T. Around 2021, DynamoEdge also held a subcontract with 9-12 LLC, which was terminated that September. A May 2021 matching-grant agreement between 9-12 and DynamoEdge was reportedly canceled within weeks of being signed.

Bessolo alleges that David Roberts, in his IEDC role, undermined her relationships with prospective partners including Cisco and AT&T, at one point allegedly telling her the technology was “never going to be at IMS” — a reference to the Indianapolis Motor Speedway. By 2024, Andretti had launched an AI venture reported to be valued at roughly $1 billion, which the complaint alleges incorporates DynamoEdge’s vehicle-performance-prediction technology and marketing language. The complaint also points to a 5G proof-of-concept project involving 9-12 LLC, AT&T, and Purdue University as another avenue through which DynamoEdge’s IP allegedly ended up in other hands.

The legal theories

The complaint reportedly pleads several distinct causes of action rather than a single trade secret claim, which is worth noting for anyone tracking how these disputes get pleaded in practice: misappropriation of trade secrets, breach of contract, tortious interference, defamation, and a claim for an accounting of IEDC contracts and grants dating back to 2016. That last piece is unusual — Bessolo’s team is effectively asking the court to require a public agency to open its books, on the theory that public funds may have supported ventures built on her technology without authorization. She is seeking exemplary and punitive damages along with an injunction barring further use of the disputed IP, trademarks, and technology.

Roberts, through his attorney Paul Jefferson, has already pushed back publicly, characterizing the suit as resting on “a fundamental lack of knowledge of the facts.” None of the defendants have been found liable, and the case is still in its early stages.

Why this case is worth watching

Setting aside how the facts eventually shake out, the fact pattern touches several issues that come up constantly in technology partnership deals: what happens when a startup shares proprietary technology during unsigned “partnership” discussions with a larger, better-resourced counterparty; whether a slogan or brand phrase used consistently in commerce can support common-law trademark rights; how patent prosecution timing (a 2022 filing, a 2026 grant) interacts with allegations of use that predate issuance; and the added complexity of layering a public-private economic development relationship — with grants, subcontracts, and a state agency’s own conflict-of-interest exposure — on top of an ordinary commercial dispute.

For founders, the practical lesson is the same one IP counsel gives in every deal-stage conversation: get the NDA and any IP assignment or license terms in writing before the pitch, not after the rebrand discussion; file for patent protection early rather than relying on trade secret status alone once a technology is being shopped around to partners; and document who said what, and when, because years later those details are exactly what a complaint like this one is built on.

We’ll continue to monitor this case as it proceeds through Marion Superior Court.

 

This post summarizes publicly reported allegations from a filed civil complaint. The claims described above are allegations only and have not been proven in court.

Sources

A question we’re hearing more and more from inventor clients goes something like this: I used AI tools throughout development — for research, for organizing my notes, for drafting business documents, for thinking through regulatory strategy. Does that create a problem for my patent application?

It’s a fair question, and it’s usually prompted by half-remembered headlines about Thaler v. Vidal — the case that made clear an AI system can’t be named as an inventor on a U.S. patent. That headline is accurate, but it answers a narrower question than most people think it does. Below is how we walk clients through it, using a recent (anonymized, and lightly composited) fact pattern as an illustration.

The scenario: The client’s product idea originated years earlier from the client’s own hands-on experience solving a personal problem. Long before any AI-assisted work began, the client had privately worked out the core mechanism themselves. The client also happened to have a timestamped chat log — from before any substantive development work — in which they described the concept, in their own words, to an AI assistant. From that point forward, the client used AI tools extensively: researching related art and regulatory questions, organizing findings, drafting business documents, and thinking through strategy. All physical testing and refinement was done by the client, by hand, on the actual product.

1. Does this create an inventorship problem, or a disclosure obligation?

Short answer: not on these facts, and here’s why.

Thaler v. Vidal held that under the Patent Act, an “inventor” must be a natural person — a machine can’t be listed as one. The Federal Circuit decided that in 2022, and the Supreme Court has since twice declined to disturb the underlying principle (denying certiorari in the original patent case, and again in the companion copyright dispute over AI-generated output). That rule is now settled.

What it does not say is that using AI during the invention process disqualifies you as the inventor. The USPTO addressed that directly, first in 2024 guidance and then in a revised version issued in late November 2025 that simplified the standard considerably. The Office now applies a single, uniform inventorship test regardless of what tools were involved: did a natural person form the definite and permanent idea of the complete and operative invention? The 2025 revision explicitly frames AI as “a sophisticated tool, akin to a laboratory instrument” — the same category as a modeling program, a search database, or a bench assistant who follows instructions. Using a tool to research, organize, draft, or test doesn’t make the tool a co-inventor, any more than a word processor or a CAD program would be.

Applied to the scenario above: the conception — the actual inventive insight — occurred in the client’s own head, based on personal experience, and there’s a contemporaneous, timestamped record showing the concept was already fully formed before any AI involvement. Everything after that point — research, drafting, strategy discussions, and the physical testing that reduced the idea to practice — is exactly the kind of tool-assisted work the current guidance says doesn’t touch inventorship, provided the AI wasn’t the source of the inventive contribution itself. The one thing we’d always confirm with a client in this position: did the AI, at any point, propose a specific technical solution or design element — as opposed to organizing, summarizing, or explaining things the client already directed — that ended up in the claims? If so, that particular element deserves a closer look. Explaining well-understood concepts or executing on the inventor’s specific instructions doesn’t count as a contribution to conception; independently proposing a novel technical fix might.

As for disclosure: there’s no separate box to check telling the USPTO “I used AI.” What does apply is the ordinary duty of candor and good faith that already governs every filing — the Office’s April 2024 guidance made clear that duty extends to “the actions individuals take with any automated tools, including AI tools,” meaning anything AI-assisted that’s material to patentability has to be handled with the same honesty as anything else. Practically, that means two things: the inventor’s declaration (the sworn statement that you believe yourself to be the true inventor) has to remain accurate, which it is here; and nobody gets to treat AI output as pre-verified. If an AI tool is used anywhere near the substance of the application — drafting language, characterizing prior art, describing what the invention does — a human has to independently check it before it’s filed. The Office has been blunt that “simply relying on the accuracy of an AI tool is not a reasonable inquiry.”

A contrasting example — where it gets murkier

Not every AI-assisted development story is this clean, and it’s worth showing the other end of the spectrum so the line is clear. In a different (also anonymized and composited) matter, a founder came to us with a working prototype and a fairly polished specification, largely shaped by an AI tool from early on. Their process had been to describe the problem they wanted solved and ask the tool to propose a mechanism, then build around whatever it suggested. When we asked the founder to walk us through their own contribution to the core mechanism in the claims, the honest answer amounted to: recognizing that the AI’s suggestion would work, and then building it.

That’s a materially different fact pattern, and current guidance treats it as a real risk rather than a formality. Identifying a problem and prompting a tool to solve it, then appreciating that the tool’s proposed solution is a good one, generally isn’t enough to establish conception of that solution — a person has to have actually formed the definite and permanent idea of the claimed invention, not merely recognized the value of an idea that originated elsewhere. If no natural person can honestly say they conceived a given claim element, that element is on shaky ground: it can jeopardize the validity of the claim, and it puts the inventor’s signed declaration at real risk of being inaccurate.

Situations like this are usually recoverable, but not by adjusting the paperwork. The fix is substantive: go back and identify where the founder’s own independent judgment actually entered the process — a modification, a rejection of one AI-suggested approach in favor of another, a design constraint only the founder would know to apply — and build claims around what they can honestly stand behind as their own. Where there wasn’t much of that, the claims may need to be narrowed, or the invention may need further independent development before it’s ready to file. What doesn’t work is treating an AI-proposed mechanism as your own idea simply because you were the one who typed the prompt.

2. Documentation practices worth adopting going forward

None of this requires overhauling how a client works — it mostly means being deliberate about what gets recorded and when.

  • Keep the conception record intact and separate. The dated, contemporaneous description of the idea — in the client’s own words, before AI-assisted development began — is exactly the kind of evidence that makes this analysis easy. Export it, preserve the metadata, and don’t let it get mixed in with later, more collaborative research threads.
  • Maintain an ongoing inventor’s record. Dated notes, sketches, or a simple log of testing and iteration — kept independent of any AI tool — continues to be the strongest evidence of who actually conceived and refined the invention.
  • When AI is used to brainstorm technical options, document the human judgment layer. If a client ever does ask an AI tool for possible solutions to a design problem, the record should show the client evaluating, selecting, modifying, and testing those options — not simply adopting an output wholesale. That evaluative work is itself evidence of inventive contribution.
  • Verify before it’s filed. Any AI-touched language, citation, or technical characterization headed for the application should be independently checked against source material — both because of the duty of candor and because AI tools are known to occasionally fabricate or misstate details.
  • Mind confidentiality, separately from inventorship. Before pasting unfiled invention details into a consumer-tier AI account, check the provider’s data-use settings. It’s less about patent law and more about not inadvertently sharing confidential technical information more broadly than intended.

The bottom line for clients using AI as part of an otherwise ordinary R&D and business-development process: the Thaler rule is about who — or what — can be named as an inventor, not about what tools an inventor is allowed to use along the way. Good habits around dating and preserving your own conception evidence do more to protect the application than any change in how AI is used.

This post discusses general principles of current U.S. patent law and USPTO guidance for informational purposes; it isn’t legal advice and doesn’t create an attorney-client relationship. The scenario described is a composite, anonymized illustration and doesn’t identify any client or specific matter. Every fact pattern is different — if you’re navigating a similar question, talk to counsel about your specific situation.

A client asked me last month whether the AI-generated product renderings her design team had been using could be protected as her company’s intellectual property. It’s a great question, and as of this spring, we finally have a clearer answer from the courts — even if it isn’t the one everyone wanted.

In March 2026, the U.S. Supreme Court declined to hear Thaler v. Perlmutter, letting stand a ruling that copyright law requires a human author. If you’re using AI in your business — and by now, most of us are, in one form or another — this case is worth five minutes of your time.

What Happened

Dr. Stephen Thaler, a computer scientist, applied for copyright registration on an image called “A Recent Entrance to Paradise,” which he said was generated entirely by his AI system, DABUS, with no human prompting, editing, or creative input at all. He was upfront about that — no human touched the creative process. The Copyright Office denied the application. The D.C. Circuit agreed with that denial. And on March 2, 2026, the Supreme Court declined to take the case, leaving the D.C. Circuit’s ruling in place.

The rule, in plain terms: a work produced entirely by a machine, with no human creative contribution, cannot be copyrighted. It doesn’t matter how original the output looks.

What This Case Didn’t Decide

Here’s the part I want my clients to understand, because it’s where the real-world stakes are. Thaler’s case was an extreme, deliberately clean test — he disclaimed any human involvement on purpose. The Court didn’t address the situation most businesses are actually in: a person using AI as a tool, prompting it, picking through outputs, editing results, or combining AI-generated pieces into something new.

That situation is governed by the Copyright Office’s own guidance, and it’s more workable than people assume. Here’s how I’d summarize it for clients:

AI-assisted work can be copyrighted if a human is genuinely exercising creative control — writing a piece and using AI to edit or polish it, for example, doesn’t put your authorship in doubt.

Selection and arrangement can count. If you select, arrange, or substantially modify AI-generated elements in a creative way, that arrangement can be protected — even if the individual AI-generated pieces, on their own, couldn’t be.

A prompt alone isn’t authorship. Typing a prompt into a generative AI tool, no matter how carefully crafted, doesn’t by itself make you the legal “author” of the output. The Office’s logic: identical prompts can produce very different results, which tells you the human isn’t controlling the actual expression — the AI is.

Pure AI output is not protectable. Full stop. If nothing about the final product reflects human creative judgment, it isn’t yours to copyright.

Why I’m Telling You This

If your business leans on generative AI for marketing content, product designs, written materials, or other creative assets, this matters more than it might seem. Content that’s essentially raw AI output — accepted as-is, without meaningful human editing or arrangement — may not be something you can actually stop a competitor from copying. No demonstrable authorship, no enforceable copyright.

It also affects how you should be filing. The Copyright Office now requires applicants to disclose AI’s role in a work and explain the human contribution specifically. I’ve seen clients try to skip past this on an application, and it’s not worth the risk — an inaccurate disclosure can undermine the registration itself, and with it, your ability to enforce the work down the line.

What I’d Recommend

Keep a record of the human creative process behind anything you want to protect: what was selected, edited, arranged, or substantially changed, and by whom. Treat AI output as a draft or raw material rather than a finished product if copyright protection is something you care about. And when you do register AI-assisted work, disclose the AI’s role honestly — the Copyright Office is actively looking at this, and it’s far better to get it right the first time.

Thaler may be the last word on purely autonomous AI authorship, but it’s really just the opening chapter on how the law will handle humans and AI working together, which is the situation nearly all of us are actually in. I’ll keep tracking how this develops. If you have questions about protecting AI-assisted work at your company, give me a call.

 

Rick Martin

IP Solutions Law

This post is for informational purposes only and does not constitute legal advice. If you have questions about protecting AI-assisted work, please contact us and schedule a strategy session.

Skip to content