AI-Written Code: The 2 Proofs Buyers Check

If an AI tool writes a lot of your code, you might worry a buyer will pay less for your company. Most won’t. In Stack Overflow’s 2026 developer survey, 73% of developers said they use AI coding assistants every day, so buyers expect it.

Instead, they check 2 things. Can your team fix and change software nobody wrote by hand? And can you prove your company owns it? Your employees sign contracts that give their work to the company. An AI tool signs nothing, so you need another way to show you own its code. I’ll show you how to prove both.

You’ll also get the 6 documents that answer both questions before a buyer asks.

Will AI-generated code hurt you in due diligence?

The code itself rarely costs you. What a buyer can’t check about it does.

Due diligence is simply the weeks a buyer spends checking everything you’ve told them before they pay. On the technical side, the questions were always about bugs, security and who built what. AI tools haven’t changed those questions. They’ve made 2 of them harder to answer.

Start with how common this is. In Sonar’s State of Code survey, published in January 2026, 1,149 developers took part. They said 42% of their code is now written or assisted by AI. That’s what developers report about their own work, not a scan of anyone’s code. It still tells a buyer what to expect from most companies they look at this year.

A buyer who marked down every AI-built product would have very little left to buy. So they don’t. They price what it will cost them to own your code after you leave. That cost depends on 2 things, and I check both before any founder I advise goes to market.

Can your team maintain code it did not write?

Here is why a buyer cares. They pay today for revenue they expect to collect for years. That revenue depends on someone being able to fix and improve the product next year. With AI-written code, the person who asked for it may not fully understand it. If that person leaves after the sale, the buyer owns code that nobody can explain.

Developers say as much themselves. In the 2026 Stack Overflow survey, 48% said they trust AI when they can easily check its answers. Only 16% extend that trust to most everyday tasks. The people closest to the code still check it line by line.

That figure comes from Veracode’s 2026 GenAI Code Security Report, published in July. In those tests, AI models wrote code that worked nearly every time. On security, the average pass rate was 56%. In Veracode’s first report it was 55%, so it has barely moved.

That gap is what a buyer is testing. Code that runs is not the same as code your team understands. When a buyer can’t tell the difference, they protect themselves. They ask key people to stay with a retention bonus. They hold back part of the price, which is simply money paid later only if nothing goes wrong. Or they offer less. It’s the same key person risk they already price in every software deal.

Here is what proves your team can run the code:

1. A map of who can change each major part of the product. Any part with only one name next to it is your risk. Fix those first.
2. Tests on the parts that touch money, customer data and logins. Tests let a buyer’s engineer change your code and see that nothing broke, without taking your word for it.
3. A practice walkthrough. Ask an engineer to explain a part of the product they didn’t build. If they can’t, a buyer’s engineer will notice too.

I hold my own software to this. In the product I’m building now, AI agents write code. Before they write any, we write a plain spec for each feature and keep it inside the code repository. Every agent and every engineer works from the same written plan. We started doing this because earlier projects of mine stalled when nobody had written down what the code was supposed to do. The specs let a new engineer, or a buyer, see why the code does what it does.

Code that nobody understands is expensive whether a person or a model wrote it. That’s why buyers treat it like any other technical debt.

Does your company own code an AI tool wrote?

This is the newer question, and it’s a legal one. Your employees and contractors give their work to the company through IP assignment agreements, which are simply signed promises that what they build belongs to the company. An AI tool signs nothing.

So ownership of AI output runs through 2 other places. The first is the tool’s terms. Each vendor’s terms say whether they pass their rights in the output to you, and the terms can differ by plan. Save a copy of the terms for the plan you actually pay for.

The second place surprises most founders. A tool can only pass along rights that exist. The US Copyright Office said in January 2025 that AI output is protected by copyright only where a human decided enough of what it contains. Arranging or changing the output can count. Writing a prompt alone does not.

The courts have held the same line. On March 2, 2026, the Supreme Court declined to hear Thaler v. Perlmutter. That left in place the rule that copyright needs a human author.

None of this makes AI-built code worthless. Your contracts and trade secrets still protect it. It does mean your record of human work matters. Proof that your engineers reviewed, tested and changed the output is the kind of human work that standard looks for.

The older version of this problem hasn’t gone away either. I put IP assignment on the pre-sale homework list I give founders, because a contractor who never signed one can claim part of the code later. This year a seller I advised told buyers about a second product. It raised no ownership questions, because the company itself built it. Code built outside the company, by a founder on the side or a contractor with no signed assignment, is where these problems start. Our guide to IP assignment cleanup for employees and contractors covers that part.

What should you prepare for AI-generated code due diligence?

Most of this is paperwork, not engineering. 6 documents answer almost everything a technical buyer will ask, and only 3 of them need an engineer. The time column is my own estimate from preparing companies for sale.

Founders most often forget to sign their own assignment. A founder who never assigned their own work to the company can delay a closing over a single signature.

The license scan matters more once AI tools write code. An AI assistant can copy in code from an open-source project whose license requires you to share your own code. A buyer’s scanning tool will find it, so find it first. Our guide to open-source licenses and IP cleanup before a SaaS sale covers what to fix.

My rule for timing is simple. Start the paperwork whenever you like. Start the maintainer work at least 2 quarters before you plan to go to market, because getting a second engineer comfortable with a part of the product takes months. If you want the rest of the technical checklist, our guide to technical due diligence for SaaS sellers walks through it.

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