Copyright Claims Are Cheap. Challenging Them Isn't.

2026-11-02

In his October 31 essay, Formalities, Cory Doctorow makes an intriguing prediction: generative AI is going to force corporations to take copyright administration seriously again.

His argument begins with a straightforward proposition about American copyright law. Copyright protects human creativity, not the outputs of autonomous machines. As businesses increasingly mix human and AI-generated work, they will therefore need to distinguish which parts of their products are actually protected.

Doctorow concludes that businesses will be forced to maintain detailed records of how their creative products are made. He predicts a return to copyright formalities, this time imposed by the private sector rather than the government. Companies will have to document the provenance of every pixel, word and note if they want to defend the intellectual property they claim to own.

There is something appealing about this prediction. Copyright formalities fell out of favour partly because they imposed administrative burdens on rights holders, leaving the public with an enormous universe of works whose ownership and protection are difficult to establish. Perhaps AI will finally force corporations to confront those problems.

But I think Doctorow makes a significant leap from a correct observation about copyright doctrine to an unlikely prediction about corporate behaviour.

Copyright law does not operate in a vacuum. It operates within a market in which property rights are asserted, recognised, traded and valued, frequently without anyone testing their validity.

And that market has powerful reasons to preserve the existing arrangements.

The difference between having copyright and claiming copyright

Let's begin with the legal point on which Doctorow is substantially correct.

Under current US law, purely AI-generated expression is not eligible for copyright protection. The Copyright Office's January 2025 report confirms that human authorship remains essential.

The report also makes an important qualification. Human creative contributions can remain protected even when a work includes AI-generated material. Editing, arranging or incorporating such material doesn't necessarily invalidate the copyright in the resulting work. Nor does using AI as an assistant automatically make a work uncopyrightable.

The DC Circuit's decision in Thaler v. Perlmutter in March 2025 affirmed that a machine cannot be the sole author of a copyrighted work.

None of this is particularly helpful to a corporation hoping to claim exclusive rights over material generated entirely by AI.

But copyrightability is only one part of the question.

Suppose a corporation publishes a successful illustrated book. It claims copyright in the ordinary way, identifying the corporation as the rights holder.

Perhaps an employee drew the illustrations. Perhaps a contractor drew them and assigned the rights. Perhaps the employee generated them with an AI tool and made extensive creative modifications. Or perhaps the images came almost directly from an image generator.

These possibilities have different legal implications.

But from the outside, they might look exactly the same: a book bearing a corporate copyright notice and being sold through ordinary commercial channels.

Why would the market suddenly stop treating that book as proprietary?

The corporation will continue asserting ownership. Its distributors will continue selling it. Its licensees will continue paying for permission to use it. Competitors considering reproducing it will still face the possibility of a copyright lawsuit.

Nothing in the Copyright Office's position requires the corporation to establish its entire creative history before it can make those claims.

That distinction between the legal validity of a right and its ordinary commercial recognition is central to understanding what will happen next.

What happens when someone actually challenges ownership?

Imagine two companies, A and B.

Company B sells a successful illustrated product and claims copyright. Company A suspects that much of the artwork was generated by AI with insufficient human involvement to qualify for protection.

Company A wants to reproduce the artwork without paying.

How does it proceed?

It could simply reproduce the material and defend itself if sued. Alternatively, where there is a sufficient concrete legal controversy, it could seek declaratory relief.

Either approach involves legal uncertainty, expense and risk.

And the US legal system already has established procedures for resolving disputed copyright claims.

Under 17 USC §410(c), copyright registration made before or within five years after first publication provides prima facie evidence of the copyright's validity and the facts stated in the registration certificate.

This is a rebuttable presumption, not an absolute guarantee. A credible challenge can overcome it. But it means a registration isn't simply an unsupported assertion that must be proved afresh whenever someone questions it.

The Copyright Office also requires applicants to disclose more-than-trivial AI-generated content and exclude unprotectable material from the scope of their registration claims. Inaccurate applications can create serious problems for claimants.

And registration is no longer optional for a US work whose owner wants to bring an ordinary federal infringement action: Fourth Estate v. Wall-Street.com confirmed that registration, or refusal of registration, generally must precede such a lawsuit.

These requirements create a genuine incentive for businesses to document human authorship, particularly for commercially important works.

But notice the scale at which they operate.

A copyright claimant doesn't generally need to prove the creative history of every work before publishing it. Nor must every potential rights holder publicly establish that a work contains no AI-generated expression.

If a dispute goes to court, the claimant may need substantial evidence of human authorship. Where a registration presumption has been effectively rebutted, or no applicable presumption exists, uncertainty may ultimately defeat the claimant's case. The copyright owner still has to establish a protectable right.

That is a real risk.

It is not, however, a new principle that uncertainty automatically places the disputed material in the public domain.

In the ordinary marketplace, the burden of deciding whether to challenge an asserted copyright remains with whoever wants to act contrary to that claim.

And that practical burden matters enormously.

The value of copyright is determined in the market

The more interesting question is not whether a particular work is legally copyrightable.

It is whether doubts about copyrightability materially reduce the economic value of a corporation's intellectual property.

For companies whose value depends heavily on copyright portfolios, intellectual property is a commercial asset. Rights generate income through licensing, distribution agreements, publishing, merchandising and countless other arrangements.

Investors value that property because they expect it to produce future cash flows.

They don't require absolute certainty that every underlying right would survive every conceivable legal challenge.

They require commercially sufficient confidence.

This is already true of ordinary intellectual property. Patents can be invalidated. Copyright ownership can be disputed. Licenses can contain defects. Contracts can be challenged. The commercial value of those assets nevertheless persists.

A useful way to think about the question is that the economic impact of an authorship defect depends on the probability of a successful challenge, the consequences if one succeeds, and the costs and disruption associated with defending it.

If those risks are material, they can reduce the price a buyer is willing to pay.

If they are remote, commercially tolerable or inexpensive to manage, they may have little effect.

Consider a fictional entertainment company with a valuable character franchise. The franchise generates revenue from films, merchandise, games and licensing agreements.

Someone alleges that AI was involved in producing some recent artwork.

Does this make the entire franchise substantially less valuable?

Probably not.

There may be existing human-authored characters, scripts, designs, trademarks, contracts and other rights supporting the business. AI authorship uncertainty concerning particular images need not threaten all of those interests.

At the other extreme, imagine a company whose principal asset is a catalogue of unmodified AI-generated illustrations, marketed on the promise that customers are buying exclusive rights to the images.

That company has a much more serious problem. If the images aren't copyrightable, competitors may be free to reproduce them, subject to any other applicable rights.

The difference is not whether AI was used.

It is how much of the business's value depends on the particular exclusivity that AI authorship might undermine.

This suggests a more selective commercial response than Doctorow's prediction.

Companies will devote resources to proving copyrightability where the value at risk justifies it.

Everywhere else, they may simply continue operating as before.

Are companies actually introducing AI formalities?

Here Doctorow has stronger evidence on his side than might initially appear.

There are already concrete examples of businesses introducing AI-specific documentation, warranties and restrictions.

The most revealing are not announcements about ethical AI or voluntary transparency. They are actual commercial agreements.

In April 2024, the National Venture Capital Association updated its model financing documents to include representations concerning generative AI use. Among other things, companies may be asked to confirm that their use of generative AI has not materially compromised intellectual property they intend to maintain as proprietary.

Law firm Mayer Brown examined these provisions in its May 2024 analysis of AI representations in technology acquisitions.

Its observations are particularly relevant: many AI-specific representations substantially duplicate protections already provided by ordinary intellectual property warranties. The firms are largely adapting existing transaction procedures to address newly identified risks.

More significantly, there are now examples in actual SEC-filed transaction documents.

A November 2025 merger agreement between Kratos Defense & Security Solutions and Orbit Technologies contains representations addressing whether generative AI was used in ways believed to materially affect proprietary intellectual property rights.

A July 22, 2026 asset purchase agreement between Progress Software and Domo includes assurances regarding AI use in developing material proprietary IP, alongside commitments concerning AI controls and procedures.

And an October 27, 2026 merger agreement between EnerSys and Ultralife goes considerably further.

Its intellectual property provisions refer to a disclosure letter listing AI models used by the company, the purposes for which they were used, descriptions of material outputs, and how those outputs were employed.

It also contains representations addressing AI-generated outputs whose ownership or eligibility for intellectual property protection may be uncertain.

This is real evidence of the private sector creating additional administrative requirements around AI.

But it is also remarkably revealing about what form those requirements are taking.

The language is concerned with material outputs, proprietary intellectual property, commercial risk, and the allocation of responsibility between buyer and seller.

It is not a universal public system for documenting the authorship of every piece of expression.

Nor does the existence of contractual representations demonstrate that a business has implemented exhaustive provenance tracking. The disclosure records are generally private, and the degree of scrutiny behind particular assurances is not visible from the public agreements alone.

What we can observe is a process of private due diligence becoming more explicit about AI.

That is a significant development.

But it is recognisably an extension of existing commercial practice.

Different industries are responding differently

The broader evidence is also instructive.

Adobe Stock accepts generative AI images, vectors and videos, provided contributors comply with its licensing and disclosure requirements. Contributors must identify qualifying AI-generated submissions.

This is a formality, but it is not a requirement to prove that every image is entirely human-authored.

It is a classification and risk-management mechanism operating inside an existing licensing business.

Getty Images, by contrast, does not accept AI-generated or AI-modified editorial submissions.

That makes commercial sense for a different reason. Editorial photography is valuable partly because customers expect it to document actual events. Authenticity matters independently of copyrightability.

Shutterstock takes another approach. Its generative AI licensing arrangements can include contractual indemnification for eligible images that have passed human review.

Here the seller is managing legal risk and providing commercial reassurance. Indemnification doesn't magically create copyright in otherwise uncopyrightable expression, but it can make the transaction more attractive to customers.

In entertainment, Netflix has published guidelines for production partners using generative AI. Certain uses require disclosure or approval, particularly when generated material may appear in final productions or involve major creative elements, performers or other rights holders.

Meanwhile, the Writers Guild of America's 2023 agreement established requirements concerning AI-generated material supplied to writers. Its 2026 agreement added notification requirements where companies license writers' work for training commercial generative AI systems.

These are meaningful contractual controls, some of which directly advance the interests of human creators.

And there are technical formalities emerging too. Adobe automatically attaches Content Credentials to certain Firefly-generated assets, using provenance metadata to disclose information about how content was produced.

But Content Credentials primarily establish and communicate a record of provenance. They are not a judicial determination of copyright validity, and they don't create ownership rights merely by recording an assertion.

Taken together, these developments show that AI is changing commercial procedures.

They do not establish that companies are being forced to prove human authorship for every expressive element in everything they sell.

Indeed, the diversity of responses suggests something else: markets are finding different ways to accommodate different kinds of AI-related risk.

Sometimes that means disclosure. Sometimes it means excluding AI-generated content. Sometimes it means licensing, indemnification or contractual assurances. Sometimes it means making AI use an ordinary part of the product.

There is no single inevitable response.

Why these aren't the formalities Doctorow is imagining

Doctorow's larger historical argument concerns the disappearance of copyright formalities.

Historically, the United States imposed administrative requirements that could determine whether copyright protection was obtained or maintained. These included notice, registration, deposit and, under earlier regimes, renewal.

The modern system differs fundamentally.

Copyright generally arises automatically when an original work of human authorship is fixed in a tangible medium, under 17 USC §102.

Registration remains important for enforcement and certain remedies, but it is not ordinarily a condition for copyright to exist.

The United States implemented the Berne Convention through legislation enacted in 1988 and joined the Convention effective March 1, 1989—not in 1976, as Doctorow's article suggests. The Copyright Office confirms that date.

None of the corporate practices described above changes the fundamental operation of that system.

A private buyer can require detailed representations before acquiring a company. A stock photography marketplace can demand labels. A film studio can impose production rules. A platform can require metadata.

But none of those procedures becomes a general condition for enjoying copyright protection under American law.

And the incentives driving them are quite different from those of a public copyright registry.

A public formality can make rights easier for everyone to identify and challenge.

A private disclosure process primarily protects the commercial interests of the parties involved.

The EnerSys–Ultralife agreement illustrates this distinction neatly. Its AI disclosure requirements are extensive, but the resulting information is supplied through a private transaction process.

The existence of those records doesn't mean the public gains access to them.

Corporations can become better at documenting the property they claim to own without making it materially easier for outsiders to challenge those claims.

That may be the opposite of the public-interest result Doctorow hopes to see.

The deterrent effect of an uncertain copyright claim

There is another important asymmetry here.

A corporation asserting copyright in a commercially valuable work can be quite comfortable with uncertainty about the ultimate outcome of a hypothetical lawsuit.

Its competitors may be considerably less comfortable.

Suppose a publisher suspects that a rival's bestselling illustration was generated entirely by AI.

It might be legally entitled to reproduce the image.

But how confident must it be before doing so?

If the rival has registered a copyright claim, maintains that substantial human authorship was involved, and has the resources to litigate, the decision is not straightforward.

Even successful litigation can be expensive and disruptive.

The larger publisher may have a diversified portfolio, legal counsel and substantial cash reserves. A smaller competitor may have much more to lose from a single dispute.

This is not a guarantee that the larger publisher wins. A credible challenge can succeed, and litigation risks cut both ways.

But it creates a possible gap between de jure exclusivity and de facto exclusivity.

A work can be treated commercially as exclusive even if some of its claimed copyright protection would fail under sufficiently close examination.

That doesn't make the claim legally valid.

It can nevertheless make the claimed property commercially valuable.

This phenomenon isn't unique to AI. It arises whenever enforcement costs, uncertainty and unequal resources influence how people respond to asserted legal rights.

AI may create more opportunities to challenge copyright validity without necessarily making those challenges cheap enough to change ordinary market behaviour.

Indeed, widespread uncertainty could favour established rights holders, who are better positioned to manage the disputes.

Does the threat of AI reduce the value of corporate intellectual property?

Sometimes, certainly.

If a company derives most of its economic value from exclusive rights over material that turns out to be uncopyrightable, the consequences could be severe.

A potential buyer would be rational to investigate the issue. A lender might discount assets that cannot reliably support expected revenues. A licensee might demand additional assurances.

The SEC-filed agreements discussed above demonstrate that these questions are already entering transaction documentation.

So Doctorow is right that provenance may become increasingly important.

But his prediction becomes much less convincing when generalised to the whole creative economy.

A corporation does not need every creative element of every product to be independently copyrightable for its business to possess valuable intellectual property.

Human-authored material can remain protected within mixed works. Existing catalogues can retain their rights. Trademarks, contracts, exclusive access arrangements and other commercial assets can preserve value independently of copyright in particular outputs.

The potential loss of one category of rights doesn't automatically destroy the economic usefulness of the larger product.

Even contractual terms from AI providers illustrate the difference between commercial ownership arrangements and the existence of statutory copyright. OpenAI's terms assign users whatever rights OpenAI may have in their outputs, while acknowledging that outputs may not be unique. Such terms help allocate rights between contracting parties. They cannot manufacture a copyright where the law recognises none.

In other words, companies can continue trading, licensing, valuing and making representations about AI-assisted products even when the precise extent of their statutory copyright protection is uncertain.

The market can live with that ambiguity.

It already lives with plenty of others.

The greater threat may be competition, not copyrightability

There is a final distinction worth making.

AI may substantially undermine the economic value of some intellectual property businesses even if their copyright claims remain completely defensible.

Consider the stock imagery market.

A company with a large catalogue of human-created photographs might retain perfectly valid copyrights in every image it owns.

But if customers can generate acceptable substitutes at negligible cost, those copyrights become less commercially valuable.

Not because they have been invalidated.

Because customers no longer need the protected works as much as they once did.

This is a much more direct economic mechanism.

Copyright prevents certain unauthorised uses of protected expression. It does not prevent others from producing different works that satisfy the same customer demand.

Generative AI may make that competition dramatically easier.

The price of exclusive rights to a particular image can fall even when those exclusive rights are legally impeccable.

The same argument potentially applies to commercial illustration, advertising copy, routine software development, music and other markets where AI lowers the cost of producing substitutes.

If corporations find their creative assets losing value, this may be a far more important cause than uncertainty over who authored particular outputs.

And unlike a legal challenge that might never happen, competition can affect revenue immediately.

What I think will actually happen

The evidence points towards a fairly conventional commercial adaptation.

Companies will continue claiming copyright over their products. They will continue publishing copyright notices, registering commercially important works, licensing their catalogues and asserting ownership in transactions.

Buyers and investors will increasingly ask whether AI use has materially compromised the rights being sold.

Contracts will acquire additional warranties. Some industries will introduce disclosure requirements. High-value productions will maintain more detailed creative records. Platforms will develop provenance metadata.

Where the risk is substantial, these requirements may become rigorous.

Where it is insignificant, they may remain minimal or disappear into ordinary business procedures.

This is not a prediction that AI provenance won't matter. It clearly already does.

It is a prediction that companies will respond to it in proportion to commercial incentives rather than adopting a universal new standard of copyright documentation.

Crucially, the evidence so far supports the emergence of targeted contractual controls, not an industry-wide requirement to track the human or machine origin of every expressive element.

Those are very different outcomes.

Formalities for whom?

Doctorow sees a possibility that AI will force corporate copyright holders to treat creative rights with more seriousness and, perhaps, create a system that works better for artists and the public.

Some of the changes he describes may indeed benefit creators. Better records of human contributions could make attribution and compensation easier. Stronger agreements could prevent employers from using AI to evade obligations to writers and artists.

But there is nothing inevitable about that distribution of benefits.

A corporation can document its provenance privately, satisfy its financiers, maintain its proprietary claims and give the public almost no additional information.

It can insist that contractors disclose their AI use without making equivalent disclosures about its own productions.

It can demand warranties from smaller suppliers while preserving ambiguity in its dealings with competitors.

It can afford the legal advice, compliance systems and litigation required to navigate uncertain copyright claims.

Smaller businesses and individual creators may be less able to do so.

If private copyright formalities become widespread, they may strengthen the ability of large corporations to assert and defend intellectual property rather than weakening it.

The real question is not whether companies will be required to do more paperwork. It is who gets access to that paperwork, who bears its cost, and who gains bargaining power as a result.

Doctorow is right to identify a tension between generative AI and the doctrine of human authorship.

He is also right that we are seeing the emergence of new private procedures for managing that tension.

But there is a missing step in his argument.

Why should those developments cause the market to stop accepting corporate claims of ownership?

Why should they fundamentally diminish the commercial value of those claims, except where particular risks become demonstrably material?

And why should the resulting private systems serve the public interest rather than the interests of the companies implementing them?

The more likely outcome is not the restoration of copyright formalities as a public institution.

It is the expansion of ordinary corporate due diligence, contractual risk allocation and selective provenance management.

Businesses will still claim ownership. Markets will still assign value to those claims. Competitors will still weigh the risks of challenging them.

The legal limits of AI authorship will matter whenever they become commercially consequential.

But until then, copyright will continue to operate much as it does today: partly as a system of enforceable statutory rights, and partly as a market of claims that most participants find it cheaper to respect than to contest.

AI may change what corporations can legally own. That doesn't mean it will quickly change what they claim to own—or what the market is prepared to pay for it.

Australian companion: No Register, Plenty of Copyright Claims examines the equivalent questions under Australian law, including its lack of copyright registration and its rules for disputed authorship.

AI disclosure: Generative AI was used in the production of this article. How much? I'm not telling. ;-)