Why AI governance matters for startups from the outset
AI governance is not a luxury reserved for large companies. For an AI startup in Latin America that wants to scale internationally, raise institutional capital, or sell to corporate and public sector clients, it is a practical necessity. Investors with European or North American LPs are incorporating AI governance questions into their due diligence processes. Enterprise clients, especially in regulated sectors such as finance, healthcare and education, increasingly require AI governance documentation before signing contracts.
The good news: for a startup, implementing AI governance from the outset is far cheaper and faster than having to retrofit it after scaling. The three minimum documents we recommend are achievable in one week of dedicated work.
The three minimum documents
The first is a Training Data Policy: it documents what data you use to train your models, on what legal basis, how you obtained it, and how you ensure it is accurate and representative. The second is a Register of AI Systems: a list of all the AI models and systems your company uses or develops, with their purpose, the data they process, and who is responsible internally. The third is a Risk Assessment Process: before launching a new AI feature or model, a checklist of questions about potential risks, bias, privacy, explainability and impact on users.
The EU AI Act and LatAm startups
If your startup places its AI system on the EU market or puts it into service in the Union, or if the outputs that system produces are used there, the EU AI Act applies. Compliance planning should begin before the expansion: assess whether your product falls into the high-risk category (Annex III), document the life cycle of your AI model, and implement the required transparency measures. Startups that do this work in advance have a real competitive advantage in the European market.
