Colombia is moving fast to regulate artificial intelligence, with a draft bill modeled on the European Union’s AI Act. That ambition signals political commitment, but copying a complex regulatory model without adapting it to local reality creates practical and financial risks for companies, regulators, and investors.
The Pitfalls of Regulatory Transplantation
The EU AI Act is built on a regulatory ecosystem with technical standards bodies, judicial precedent, and agencies funded to audit and enforce advanced compliance regimes. Many emerging markets lack that infrastructure. Transplanting the rules creates mismatches: obligations that are hard to implement, monitoring gaps, and legal uncertainty that raises costs for businesses. For investors the consequence is twofold: higher compliance spending and unpredictable enforcement that can alter project economics overnight.
AI Control: The Global South’s Regulatory Challenge
Many AI systems deployed in Colombia are developed and hosted by foreign firms. That creates a paradox: local regulators impose obligations but have limited leverage over source code, model governance, and data flows. The result is disproportionate burden on small local firms and public agencies that must certify or audit technology they cannot fully inspect. For financial actors, this means compliance risk concentrates on local partners and suppliers, increasing counterparty and operational exposure.
Designing AI Rules for Real-World Impact
Effective AI governance in emerging markets should be proportional, practical, and staged. Start with rules focused on high-risk applications, data governance, and clear liability paths. Build capacity through targeted funding for technical audits and public-private partnerships that improve visibility into foreign-supplied systems. For investors and executives, the lesson is to press for regulatory clarity, allocate runway for compliance, and favor partners with verifiable controls. Thoughtful, locally adapted regulation protects markets without imposing costly, ill-fitting obligations.
