--- title: "Who Owns the Code in an AI Development Project?" description: "Find out who really owns your AI code — client, vendor, or both. Learn the key clauses to demand and how to protect your competitive advantage before you sign." slug: "quien-es-dueno-del-codigo-desarrollo-ia-en" url: "https://catalizadora.ai/blog/quien-es-dueno-del-codigo-desarrollo-ia-en" cluster: "roi-ia-decision" published_at: "2026-08-24T07:41:27.084164+00:00" updated_at: "2026-08-24T07:41:43.427396+00:00" read_minutes: "7" lang: "en" --- # Who Owns the Code in an AI Development Project? > Find out who really owns your AI code — client, vendor, or both. Learn the key clauses to demand and how to protect your competitive advantage before you sign. # Who Owns the Code in an AI Development Project? Signing an AI development contract without checking who keeps the code can cost you years of competitive advantage — and thousands of dollars in licenses you never negotiated. Software intellectual property is one of the most poorly negotiated points in technology projects, and in AI the risk is even greater because the strategic asset isn't just the product: it's the trained model, the data pipelines, and the proprietary logic that sets your business apart. This article breaks down **who owns the code in an AI development project**, the three most common contractual structures in Latin America and the US, and the specific clauses you need to demand before you sign. --- ## Why Code Ownership in AI Is Different from Traditional Software In a conventional software project, the source code is the primary asset. In an AI development project, there are at least four layers that can have separate owners: - **Application source code** — the logic, APIs, and interfaces built by the development team. - **Trained or fine-tuned models** — weights, hyperparameters, and architectures adjusted to your data. - **Training and labeling data** — datasets that, depending on the contract, the vendor may retain or reuse. - **Prompts and reasoning chains** — in LLM-based systems, system prompts and agent chains are IP just as valuable as any algorithm. If the contract only mentions "source code," the other three layers fall into a legal gray area that, in practice, favors the vendor. --- ## The Three Most Common Ownership Structures ### 1. Full Vendor Ownership (Misconfigured "Work for Hire") In this model, the vendor retains all intellectual property rights. You receive a **usage license**, not ownership. This is the most common model in AI SaaS platforms and in standard agency contracts that don't specify IP transfer. **Practical consequences:** - If the vendor goes out of business or changes their business model, you lose access. - You can't modify, audit, or migrate the system without permission. - You pay recurring licenses indefinitely, even though you already "paid" for the development. - The vendor can sell the same solution — including logic specific to your industry — to competitors. ### 2. Shared Ownership or Bidirectional License Here both the client and the vendor retain rights over parts of the system. This is common when the vendor contributes a proprietary base framework or library. **What you need to verify:** - Which components belong to the vendor and which belong to you? Require an **IP annex** that lists each module. - Can the vendor use your usage data to improve their own products? - Does the license on the base framework prevent you from making modifications without approval? This structure can work, but it requires sharp legal counsel and very specific contract language. ### 3. Full Client Ownership (Complete IP Transfer) The most favorable scenario for the client: the vendor builds, the client keeps **everything** — source code, models, derived data, documentation, and associated intellectual property. The vendor may retain rights to pre-existing generic tools (open-source frameworks, for example), but everything created specifically for the project is yours. This is the model Catalizadora adopts by default on all its projects. No recurring licenses, no vendor dependency, no asterisks. The client receives the complete repository, trained models, and technical documentation from day one of delivery. --- ## Specific Clauses You Need to Demand in Your Contract It's not enough for the contract to say "the client owns the code." These are the specific clauses that make the real difference: ### IP Assignment This must explicitly state that **all intellectual property rights** over the developed work are transferred to the client upon payment, with no additional conditions. In Latin American jurisdictions this is frequently called "assignment of economic rights" (*cesión de derechos patrimoniales*). ### Broad Definition of "Deliverables" The contract must list: source code, compiled binaries, trained models, neural network weights, datasets generated during the project, system prompts, technical documentation, and any trade secrets developed for the project. ### No-Competition Clause for Data Use The vendor must not be able to use your business data, usage logs, or system outputs to train their own models or those of third parties. This clause is especially critical if you work in fintech, healthcare, or any sector involving sensitive data. ### Original Software Warranty The vendor must warrant that the delivered code does not infringe on third-party rights and does not contain components with restrictive licenses (GPL, AGPL) that could contaminate your ownership. ### Code Escrow For long-term projects, consider an escrow agreement where the code is deposited with a neutral service (such as GitHub Enterprise with managed access) from the start — not just at the end. --- ## The Vendor Lock-In Problem in AI Beyond legal ownership, there's an equally serious operational risk: **technical lock-in**. An AI system may legally belong to you, but if it's built on a proprietary platform with no standard APIs, migrating is so expensive that in practice you have no real control. Warning signs: - The system only runs on the vendor's infrastructure. - The models are in proprietary formats that you can't load in another environment. - Technical documentation is incomplete or withheld "for support purposes." - You can't bring in another team to make modifications. A well-built AI development project — with portable architecture, models exportable in standard formats like ONNX or Safetensors, and complete documentation — gives you real flexibility, not just legal flexibility. --- ## How to Evaluate an AI Development Vendor Before You Sign Before you commit, ask these direct questions: 1. **Does the contract transfer 100% of the IP to the client, including models and derived data?** 2. **Are there vendor-owned components that require an ongoing license to operate the system?** 3. **Can I bring in another team to maintain or modify the system after delivery?** 4. **Are the trained models delivered to me in standard, open formats?** 5. **Are there clauses that allow the vendor to use my data for their own purposes?** A serious vendor answers these questions without ambiguity. If the answers are vague or get pushed to "review with legal," that's a red flag. --- ## Intellectual Property and ROI: The Direct Connection Code ownership isn't just a legal issue — it's an ROI factor. Consider this scenario: A logistics company invests $80,000 in developing an AI-powered route optimization system. If the vendor retains the IP: - They pay $2,000/month in licenses = $24,000/year in additional costs. - Over 3 years, the real cost exceeds $150,000. - If the vendor raises prices or shuts down, the company starts from scratch. If the company owns the code from day one: - Total cost: $80,000. Full stop. - They can modify, scale, or sell the system as an asset. - The system appears on the balance sheet as a technology asset with book value. The difference between a "perpetual license" and "full ownership" can represent 2–3x the initial project cost over a five-year horizon. --- ## What the Law Says in Mexico, Colombia, and the United States **Mexico:** The Federal Copyright Law establishes that computer programs created within an employment relationship belong to the employer. In third-party service contracts, ownership must be expressly agreed upon — without a clause, the author (the vendor) retains moral rights and the client receives only a usage license. **Colombia:** Law 23 of 1982 and its amendments follow a similar logic: economic rights can be contractually assigned, but must be expressly agreed upon. Silence benefits the creator. **United States:** The *work for hire* doctrine under the Copyright Act allows the commissioning party to be considered the author if the work was created by an employee in the course of employment, or if there is an explicit written agreement for specific categories. In contracts with independent contractors, the transfer must be explicit and signed. **Legal takeaway:** Under the three most relevant legal frameworks for companies in Latin America and the US, contractual silence favors the vendor. Protection requires active, specific, and signed language. --- ## CTA: Build on Assets That Belong to You The code that generates competitive advantage should be in your hands, not your vendor's. At **Catalizadora** we develop custom AI software — from agent systems to complete platforms — and we deliver 100% of the intellectual property to the client from the first sprint. No recurring licenses, no technical dependency, no fine print. Learn how we work and what every project includes in our [Manifesto →](/manifiesto) ## Preguntas frecuentes ### Who owns the code when you hire an AI development agency? It depends on the contract. By default, in most Latin American and US jurisdictions, the vendor retains copyright if there is no explicit IP transfer clause. For the client to own the code, the contract must include an express assignment of all economic rights over the developed work. ### Do AI models trained on my data belong to me? Not automatically. Trained models, their weights, and data derived from the process are separate assets from the source code. The contract must explicitly state that fine-tuned models, neural network weights, and any datasets generated during the project are the client's property. ### What is vendor lock-in in an AI project and how do you avoid it? Vendor lock-in occurs when the AI system can only run on the vendor's infrastructure or in proprietary formats that make migration impossible without rebuilding everything from scratch. You avoid it by requiring portable code, models in standard formats (ONNX, Safetensors), complete technical documentation, and the contractual ability to bring in another team for maintenance. ### Can the vendor sell my AI solution to other clients? If the contract doesn't transfer the IP to the client, yes. The vendor can reuse the logic, architecture, and even industry-specific components in projects for your competitors. A confidentiality clause is not enough: you need an intellectual property transfer and a clause prohibiting the use of your data or business logic for third parties. ### How much more expensive is it in the long run to not own the code? Considering typical recurring licenses of $1,500–$3,000/month for mid-sized AI systems, over a 3-year horizon the additional cost can exceed the original development cost. On top of that, if the vendor raises prices, shuts down, or changes their model, the cost of migration or reconstruction can be equal to or greater than the initial project investment. --- Source: https://catalizadora.ai/blog/quien-es-dueno-del-codigo-desarrollo-ia-en Author: — AI Catalysts, LLC (catalizadora.ai)