Why Nearshoring Plus AI Is the Greatest Leverage Opportunity for Entrepreneurs in 2026 & Beyond with Brian Samson

Host JLD opens by framing nearshoring combined with AI as a major leverage opportunity for entrepreneurs in 2026 and beyond. He introduces Brian Samson as a nearshoring expert, UCLA MBA, foster-care advocate, and founder of three companies that connect Latin American talent with U.S. clients. Asked to share a belief about success that most people disagree with, Brian says most people assume great talent is scarce. He argues instead that talent is abundant; it is simply not distributed in the way companies search for it. In his view, entrepreneurs look for talent in the one ZIP code where they live, which unnecessarily limits their options. That premise sets up the rest of the conversation. Brian’s argument is not merely that companies can hire more cheaply abroad, but that they can access capable people who are overlooked because employers search geographically rather than globally. JLD previews the specific questions they will address: nearshoring versus offshoring, which functions to place nearshore, the cost and return-on-investment equation, how to select a Latin American country, and how AI changes the value of experienced global talent.

Brian explains that traditional offshoring has concentrated in three familiar locations: China as the world’s factory, India as a major IT center, and the Philippines as a major source of call-center and virtual-assistant talent. He says this model worked well for years, including during the dot-com era, but remote work changed the priorities after COVID-19 in 2020. Once work became remote, employees began testing how far they could move while keeping their jobs—Brian jokes about someone moving from New York to Bali and working on the beach. Companies then realized that time-zone differences could disrupt collaboration. He defines nearshoring relative to the employer’s location: the Philippines might be nearshore for Australia, but not for a U.S. company, whereas Latin America aligns closely with U.S. working hours. Teams can attend the same stand-ups and Zoom meetings, receive immediate responses to texts and Slack messages, and correct misunderstandings within minutes rather than discovering the next day that instructions were wrong. Brian cites a study in which 86% of U.S. leaders ranked time-zone compatibility as Latin America’s biggest advantage. He says that real-time collaboration—not simply lower wages—is the central reason U.S. companies are shifting toward Latin America.

Brian says he generally does not nearshore junior roles because the same budget that buys a junior employee in the United States can often secure a senior-level person in Latin America. He describes this as labor arbitrage: obtaining greater experience for roughly the cost of a less experienced U.S. hire. He is comfortable nearshoring almost any non-executive function, including software engineering, sales, recruiting, finance, accounting, marketing, customer support, and customer service. In his formulation, work requiring critical thinking, creativity, and time-zone alignment has already been successfully nearshored for 10, 15, or even 20 years. When JLD asks about cost, Brian acknowledges that India, the Philippines, and parts of Southeast Asia will often win on the lowest price. However, he says price is no longer the most important measure because wages are rising in those markets and throughout Latin America. He estimates typical nearshoring savings at roughly 30% to 50% versus the United States, while emphasizing that the real calculation is value and ROI. For a somewhat higher cost, a Latin American hire may provide same-day collaboration, flexibility, scrappiness, U.S.-cultural familiarity, and the ability to go off script. Brian gives Brazil as an example: an AI or data engineer may cost $100,000 or more there, but comparable U.S. talent can cost $300,000, $400,000, $500,000, or even seven figures after total compensation and equity. He has personally paid Latin American workers more than six figures when they were helping produce seven-figure revenue, because a 10x return justified the investment.

Brian stresses that Latin America is not a single labor market. Countries differ in culture, English fluency, talent concentrations, cost, customs, safety, and development. He personally spent more than a year in Argentina, has visited nine times, and works with team members throughout the region. He recommends Mexico for many roles because of its compatibility with the United States, particularly in northern cities such as Monterrey, a major technology center close to the U.S. border. Mexico City, he notes, is the largest city in North America—larger than New York—and he pushes back against stereotyped portrayals of the city by describing its green spaces, tree-covered pedestrian areas, and urban quality. He sees Mexico as a strong source for legacy Java and .NET engineers, as well as marketing and accounting talent. Argentina, in Brian’s view, has become a strong pocket for full-stack developers and increasingly sophisticated companies. He compares its emerging ecosystem to the old PayPal Mafia: successful companies such as Mercado Libre generate experienced engineers who leave, found new businesses, and attract capital. He says U.S. venture firms are now investing in Argentine companies rather than treating the country merely as a place to outsource bug fixing. He describes Costa Rica as highly developed, English-speaking, safe, and attractive but expensive because of its small population and development level. Nearby Nicaragua offers a lower-cost pool of young, educated, highly English-fluent workers suited to call-center, customer-service, and virtual-assistant work. Brazil is a fit for AI and data engineers, particularly around Florianópolis, while Medellín, Colombia—despite its older reputation—has become a mature, entrepreneurial technology center. He advises founders to consider budget, travel, office needs, and the exact role before choosing a country.

JLD asks how AI and global talent can complement one another rather than compete. Brian says this is where nearshoring is especially powerful because the roles being sourced in Latin America are often senior positions. He starts with software engineering: AI has made producing code easier, so engineers no longer need to manually write huge quantities of code. The difficult and valuable work is assembling the system correctly—integrating components, understanding context, connecting APIs, designing architecture, performing quality assurance, and managing DevOps. Brian argues that junior developers generally lack this systems-level experience, while mid-level developers have some of it and senior developers are much more likely to possess the full combination. If a company restricts its search to senior engineers in San Francisco, its total addressable talent pool is small. Opening the search to Latin America or South America exposes the company to “tens and tens of thousands” of senior engineers who can connect the pieces and work in the employer’s time zone. His conclusion is that AI does not make experienced talent irrelevant. Instead, AI increases the productivity of senior people who know what to build, how the parts fit together, and how to validate the result. Nearshoring gives companies access to that expertise without requiring them to sacrifice time-zone compatibility or accept a quality drop-off.

For listeners who want to explore nearshoring, Brian directs them to his company, Plugg Technologies, spelled PLUGG. He says he and his partner, Ruben Santana, regularly hold educational conversations with prospective clients without strings attached. They can discuss whether a founder needs one marketing employee, a salesperson, or a larger software-engineering team; which country fits the role; how budget and trade-offs affect the decision; and what technology or hardware considerations matter. Their stated goal is to provide value first, with the option to help when the listener is ready to hire. Brian also recommends the Nearshore Cafe podcast, which has more than 100 episodes. About half the episodes feature U.S. people explaining what it was like to nearshore functions such as a sales team in El Salvador or a software engineer in Lima, Peru, including the costs and complications. The other half feature Latin American project managers, software engineers, venture capitalists, and other participants describing how they work with U.S. companies and what they have learned. JLD closes by directing listeners to EOFire.com and suggesting they search for Brian’s name to find the links discussed. The episode’s final conclusion is consistent with Brian’s opening premise: entrepreneurs should broaden their search beyond local geography, judge talent by the value it can create, and use AI alongside experienced people who can make complex systems work.