Why Peru and Chile Could Turn AI Disruption into Advantage

I knew I was back in South America the moment I stepped onto the humid tarmac in Lima, yet this trip could not have been more different from my backpacking adventure twenty-five years ago. Then I was chasing nature and learning my first spanish.. Now I was chasing conversations about algorithms and governance. Over two brisk weeks I addressed developers in crowded tech hubs, briefed CEOs in boardrooms, and fielded questions in Spanish that stretched from strategizing AI in an organization to the future of specific professions. Instead of tents and hostel bunks, my souvenirs were whiteboard sketches of agent architectures and a phone full of WhatsApp invites from entrepreneurs hungry for a competitive edge.

One statistic formed the spine of every talk: roughly 90 percent of generative-AI proof-of-concepts never reach production, a sobering figure first flagged by Forbes in early 2024. I framed it not as a failure rate but as a training-ground reality. Just as call-center recruits learn scripts before meeting customers, AI agents must be coached, aligned, and evaluated before they can safely touch live data. Companies that skip this pedagogy stall. Those that embrace it discover new gains in productivity and trust.

What surprised me most was how naturally Peruvians and Chileans see this revolution as a levelling force. They speak candidly about the local talent gap, yet their optimism is palpable and they see the opportunity which AI brings them to close the gap with the west.

This urgency is not misplaced. AI is rearranging the global leaderboard faster than any trade accord or venture fund ever could. Nations that move early on governance, data accessibility, and skills will draft behind the giants within a decade. Nations that hesitate will watch their exports commoditise while imported algorithms decide margins and policy. South America has weather, minerals, renewable power, and now a window of opportunity. The question is whether it will organise those assets into a flywheel before the window closes.

My parting message in every auditorium was simple: start small but start now. Put an evaluation harness around one high-value workflow, pair each human expert with an AI assistant, and measure the uplift weekly. Upskilling must run in parallel with deployment; regulation must evolve with experimentation. If Lima and Santiago can translate their curiosity into disciplined execution, they will not just catch up to the West - they will help define how AI will shape the next industrial age.