Colombia wants South Korea to help turn its national artificial intelligence strategy into infrastructure, business adoption and environmental technology. The proposal is not merely diplomatic. It raises a question for Latin America: can international technology partnerships build domestic AI capability rather than deepen dependence on imported systems?
At a bilateral cooperation meeting in Bogotá, Colombia’s Vice Minister of Knowledge, Innovation and Productivity, Ana Isabel Vargas Salazar, outlined three priorities: research computing and regional data access, AI deployment among smaller businesses and applications for energy and water management.
Each addresses a different barrier to meaningful AI adoption. Research institutions need affordable computing capacity and usable datasets. Smaller companies need tools they can integrate into everyday operations. Utilities and environmental agencies need systems capable of supporting decisions about scarce resources.
The first priority may prove the most consequential. Without access to computing infrastructure, Colombian universities and start-ups risk becoming consumers of models developed elsewhere. Shared research capacity could give regional institutions greater freedom to train, test and adapt AI systems to local languages, industries and public needs.
Yet computing power alone is insufficient. Data governance, technical expertise, connectivity and operating budgets will determine whether new infrastructure becomes a lasting asset or an expensive showcase.
The second proposal targets micro, small and medium-sized enterprises, where AI’s economic impact could be broad but uneven. Businesses may benefit from predictive maintenance, customer service automation and improved forecasting. However, adoption depends on training, cybersecurity, integration costs and evidence that these tools deliver measurable returns.
This is where Korean experience in industrial technology could offer lessons. The challenge is translating those lessons into solutions for Colombian businesses rather than assuming that technology designed for larger enterprises will transfer automatically.
The third priority connects AI with the energy transition and water management. Potential applications include electricity demand forecasting, grid optimization, leak detection and monitoring water availability. These are attractive opportunities, but AI models depend on trustworthy data and institutions capable of acting on their outputs.
Colombia’s proposal sits within its National Artificial Intelligence Policy, CONPES 4144 of 2025. According to the 2026 Latin American Artificial Intelligence Index, the country ranks fourth among 20 regional economies and is one of only two, alongside Brazil, to specify funding for implementing its AI strategy.
That distinction matters, although an allocated budget is not the same as delivery.
Vargas Salazar suggested a bilateral technical working group involving Korea Eximbank and KOICA to identify feasible projects. The meeting also involved Korean development and environmental institutions alongside multilateral financing organizations.
No financing package, procurement timetable or infrastructure commitment was announced. The next test is whether the proposed cooperation produces funded projects with ownership, milestones and measurable outcomes.
For Colombia, the opportunity is to move from AI policy ambition to operational capacity. For South Korea, it is a chance to demonstrate that technology diplomacy can support innovation.
The measure of success will not be how many agreements are signed. It will be whether Colombian researchers, businesses and public institutions gain capabilities they can sustain independently.
