AI-Generated Code & Ownership
Do I own the code an AI tool generates for me?
Under current U.S. copyright law, output from purely generative AI lacks a human author and therefore cannot be copyrighted.
Does writing detailed prompts make me the author?
Prompts guide the system, but typically lack the determinism and creative specificity required to establish human authorship under copyright law.
Can I copyright AI-generated code?
Only the portions created or significantly modified by a human author qualify. Pure AI output cannot be copyrighted.
Can I monetize AI-generated code even if I don’t own it?
Yes, but ownership uncertainty significantly increases risk in licensing, fundraising, enforcement, and exits. Without clear ownership, you cannot create or defend a lawful monopoly over your software, allowing competitors to copy it with impunity and leaving the company with revenue but no defensible asset to protect or sell.
Vibe Coding & AI Assistance
What is “vibe coding”?
“Vibe coding” refers to prompting an AI to generate large amounts of functional code with minimal human design, structure, or revision.
Why is vibe coding risky from an ownership perspective?
Because the AI, not the human, is doing the expressive work. Under current law, vibe-coded output is not human-authored and therefore not a legally protectable asset.
Is an AI prompt processed by a large language model equivalent to source code compiled by a traditional compiler?
No. Compilers deterministically preserve human authorship by transforming source code into another form. Generative AI systems are non-deterministic and generate new expression, severing the one-to-one link required for copyright protection.
Human Authorship & Mixed Codebases
If I edit or refine AI output, do I become the author?
Possibly. Meaningful human revision, selection, restructuring, or creative judgment may establish authorship.
How much human input is “enough”?
There is no bright-line rule. Courts look for creative contribution and judgment, not just the volume of edits. Importantly, the U.S. Copyright Office does not make this determination; courts do. In practice, the issue is typically resolved only if and when authorship is tested in litigation, where prompt history, revision records, and other AI usage artifacts may be examined or compelled through discovery or subpoena. Because this analysis is highly fact-specific, many teams seek guidance in advance, and we can help evaluate authorship risk before it is tested in court.
Does refactoring or rewriting AI code make it mine?
Not automatically. Deterministic or mechanical changes (such as simple transcription or formatting) are insufficient. Authorship may arise only where refactoring reflects independent creative decisions.
Can I combine AI-generated and human-written code and own all of it?
You own what you create. AI-generated portions remain unowned unless replaced or transformed through human authorship.
Open Source, Licensing & Compliance
Can I apply MIT, GPL, or other licenses to AI-generated code?
Applying an open-source license requires copyright ownership. Because pure AI output has no copyright holder, any open-source license applied to that portion would be legally ineffective and unenforceable.
What if AI generates code similar to open-source material?
Similarity can still trigger licensing obligations or infringement risk, especially with copyleft licenses, and can retroactively undermine your IP position, turning what you believed was proprietary software into an enforceable obligation to share it. Because these issues often surface late and are expensive to unwind, we help teams identify and mitigate open-source exposure before audits or exits.
Can derivative works based on public code be copyrighted?
Yes, but only the new, human-created portions qualify for protection. This principle long predates AI, and AI does not change the rule. It only makes violations easier to create and harder to detect.
Does AI usage violate open-source terms?
Not inherently, but unmanaged mixing of sources can silently violate open-source obligations, forcing disclosure or redistribution of proprietary code and surfacing only when an audit, lawsuit, or acquisition makes the problem impossible to ignore.
Employment, Contractors & Work-for-Hire
If an employee uses AI, does the company own the code?
The company owns the human-authored portions via work-for-hire, but it cannot assert ownership over purely AI-generated sections. As a result, parts of a company’s core product may be legally unowned and unenforceable, creating ownership gaps that often surface only during litigation, audits, or an attempted exit.
What if a contractor uses AI to deliver code?
Ownership of AI-generated portions may not transfer unless contracts explicitly address AI usage, authorship, and IP allocation. This can leave critical components of your software legally outside the company’s control, with no clear right to enforce, license, or transfer—issues that are often discovered only during diligence or dispute. We can help you put the right agreements in place before these gaps become irreversible.
Should contracts address AI usage?
Yes. Modern agreements should clearly define permitted AI use, authorship expectations, ownership, and documentation requirements. These provisions are best developed with an experienced IP attorney who knows which questions to ask, rather than relying on AI-generated contract language that may omit or misallocate critical rights, often discovered only after a dispute arises.
Investment, Audits & Exit Strategy
Why do investors ask “Who owns the code?”
Clear ownership is required to enforce rights, defend against competitors, and justify valuation. Without legally enforceable ownership, an investor is being asked to fund a business whose core asset may not be protectable, transferable, or owned at all.
Does AI-generated code reduce valuation?
It can. Unowned or unenforceable assets weaken competitive barriers and increase diligence risk. Investors routinely reduce valuation or abandon transactions when a company cannot demonstrate clear ownership of its core technology.
What must I disclose during due diligence?
AI usage, code provenance, and where demonstrable human authorship exists. Undisclosed or poorly documented AI involvement often surfaces during diligence, triggering valuation reductions, indemnities, escrow holdbacks, or transaction termination, each of which can carry significant monetary consequences. In the event of a dispute, these disclosures may be examined under oath and compared against actual prompt history and other contemporaneous records, including those compelled by subpoena or warrant.
How do I prepare for an audit of AI-generated software?
Maintain prompts, revision history, commit logs, design documents, and evidence of human decision-making. Audit preparation is often where undocumented AI usage is first uncovered. We can help teams prepare defensible documentation before diligence begins.
If customers are paying us, why does ownership still matter?
Revenue does not create ownership. Without enforceable intellectual property rights, you do not possess a lawful monopoly over your software, meaning competitors may legally copy it without consequence. Customer payments confer no exclusivity, no barrier to entry, and no defense against replication. First-mover advantage is temporary; only ownership creates durable control, defensible value, and an asset that can be enforced, licensed, or sold. Without it, revenue exists—but the company does not own what it is selling.
Risk Management & Development Best Practices
Can engineers still use AI safely?
Yes, when AI is used intentionally and with an understanding of ownership implications. AI should assist, not replace, human design, judgment, and authorship, particularly in critical code paths. Teams should adopt clear usage guidelines and maintain documentation showing meaningful human review and decision-making. When used this way, AI can accelerate development without undermining ownership or defensibility.
Where is the boundary between AI assistance and authorship?
There is no bright-line rule. Authorship exists when a human exercises independent creative judgment by conceptualizing the solution, selecting among alternatives, and structuring or materially rewriting the code in a non-trivial way. Courts evaluate authorship qualitatively, based on creative contribution rather than the amount of AI involvement. This analysis is highly fact-specific.
What risks arise if AI creates critical code paths?
Reliance on AI for critical functionality can result in code that is legally unowned or unenforceable, weakening your ability to exclude competitors or defend the software as a proprietary asset. This may increase exposure to infringement, open-source compliance, and diligence risk, often surfacing only during audits, litigation, or an attempted transaction.
How should teams document AI usage?
Documentation is critical to establishing ownership, defensibility, and audit readiness. Teams should retain records of AI prompts, generated outputs, revisions, and the human decisions that shaped the final code. This provenance supports compliance, valuation, and enforcement, and should be maintained with the expectation that it may be discoverable in litigation or subject to subpoena, just like email, chat logs, or source control history.
This FAQ reflects current U.S. copyright law and general international principles. It is provided for educational purposes and does not constitute legal advice.