3Strategic path forward: building a competitive AI ecosystem This chapter outlines a roadmap of actions that could bridge Latin America’s AI competitiveness gap. Newly deployed technology takes time to generate measurable returns; while AI may not deliver immediate impact, it is important to take decisive action now to realize future benefits. Driving transformation across the region is also challenging due to the diversity of each nation’s size, culture and resources, as well as due to shifts in national priorities over time and political cycles. This underscores the importance of building consensus around key actions that can sustain progress across different administrations. A clear and consistent suite of actions can help maintain focus, develop talent pipelines and attract investment. Yet countries and companies in Latin America are at different stages in their AI adoption, and a one-size-fits-all approach will not achieve the necessary shift. Instead, increasing Latin America’s AI competitiveness should be viewed as a journey, where each country and company takes practical measures best suited to its own context yet guided by a common ambition. A Define implementable AI strategies 1. Create strategies focused on measurable outcomes in key sectors Well-defined AI strategies help ensure resources are directed towards initiatives that result in transformational change; without strategies, stakeholders may lose focus and pursue activities that distract resources and dilute the true value of AI. In the short term, national AI strategies could focus on creating the right conditions and on driving innovation for strategic economic sectors, such as agriculture, mining, energy and tourism, to help maintain and amplify the region’s competitive advantages. This could include creating sector- specific AI centres and designing AI training programmes across all education levels. In the private sector, AI strategies should translate into measurable economic impact in order not to create the AI fatigue caused by a lack of a return on investment that – according to our survey – many organizations currently experience. Companies must move beyond individual productivity usage and pilots to embed AI at scale in core domains, reimagining from end to end how the organization operates. This work requires a clear prioritization of AI opportunities by domain or journey to avoid fragmentation of these efforts. Successful AI strategies across sectors depend on leadership sponsorship, clear decision rights, disciplined funding and collaboration models that build trust, align incentives and track measurable outcomes that are tied to societal and operational impact. B Build the infrastructure and data backbone 2. Fuel AI sustainably As demand for GenAI surges throughout the region, fuelling the necessary computing power runs the risk of a resource crunch across energy, water and land use. In the future, the current level of power generation will be insufficient, and investment in capacity expansion is required. While parts of Latin America possess beneficial clean energy resources (Brazil and Paraguay draw heavily on hydropower, Chile offers solar potential, Patagonia is home to strong wind corridors, Central America holds geothermal reserves), there are at least two key challenges of tapping into those reserves. First, the supply is often not where the demand is, so additional investment in grid connectivity will be key. Second, it is of utmost importance that investment into data centres and power generation does not create new equity challenges or negative environmental consequences for the communities and natural ecosystems that are affected by them. This 3.1 10 targeted actions to drive execution The roadmap is organized into four groups that cluster actions by purpose: Latin America in the Intelligent Age: A New Path for Growth 24

Latin America Intelligent Age