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Every once in a while, I make the mistake of opening LinkedIn. I know I should not. For an unemployed former Big Tech engineer, LinkedIn often feels like an abusive relationship. I log in knowing there is a good chance I will encounter some combination of layoffs, humblebrags, AI hype, and carefully curated success stories that leave me questioning every major life decision I have ever made. And yet, like drivers slowing down to stare at a highway accident, I sometimes cannot resist the morbid curiosity. Recently, that curiosity led to a conversation that has been occupying my thoughts ever since. An old colleague reached out. Let us call him Kaushik. For several years, Kaushik and I worked together inside a large technology organization. He was a senior architect based in India, working out of one of the company’s offshore centers. We collaborated on multiple projects and developed the kind of professional relationship that forms when two people spend years solving difficult problems together. Back in 2023, our organization was hit by a major round of layoffs. Roughly half the organization disappeared overnight. I survived, although survival came with a soft demotion. My title was downgraded from Chief Architect to Senior Architect. To regain my previous position, I had to navigate a familiar corporate ritual. There were applications, self assessments, recommendation letters, and endless documentation designed to demonstrate my value to the company. Kaushik played an important role in that process. He wrote one of the strongest recommendation letters I have ever received. Reading it felt almost surreal. According to Kaushik, I was apparently a visionary thought leader whose technical brilliance illuminated the path for offshore engineering teams across the organization. The praise was generous to the point of comedy. But it helped. With support from Kaushik and several others, I eventually regained my Chief Architect title. By then, however, Kaushik had already moved on to another company. Fast forward to today. He is back on the job market. And according to him, the situation is grim. Very grim. What he described was not simply a difficult hiring environment. It sounded like an entire economic model under existential threat. The Great Engine Behind Global Offshoring To understand the problem, it helps to understand why India became the center of the offshoring world in the first place. For decades, India possessed a unique combination of advantages. A large population. Strong technical education. Widespread English proficiency. And labor costs dramatically lower than those found in North America and Western Europe. These conditions allowed India to become one of the world’s largest providers of outsourced technical services. Entire industries grew around this model. Software development. Business process outsourcing. Customer support. Quality assurance. Infrastructure management. Financial operations. Data processing. For many global corporations, India became an extension of their workforce. The arrangement was never perfect. Offshoring always came with hidden costs. Time zone differences slowed communication. Language barriers occasionally created misunderstandings. Cultural differences introduced friction. Knowledge transfer was often inefficient. Work was frequently thrown over organizational fences. Yet despite these inefficiencies, the labor savings were so substantial that the model remained highly attractive. For decades, the economics worked. Now AI may be changing the equation. The Collapse of Traditional Outsourcing According to Kaushik, traditional outsourcing firms are experiencing severe pressure. This should not be surprising. Most outsourcing work revolves around routine cognitive tasks. Tasks that are structured. Predictable. Repeatable. And increasingly automatable. Consider the kinds of activities commonly performed by large outsourcing organizations. Basic customer service. Data entry. Billing operations. Simple application development. Maintenance work. Standardized testing. Documentation. CRUD software development. These are precisely the categories where modern AI systems are improving at astonishing speed. The question facing corporate executives is becoming increasingly obvious. Why pay an external vendor to perform work that internal employees can now complete with AI assistance? Even more importantly, why accept the communication overhead, coordination challenges, and quality risks associated with offshoring if similar outcomes can be achieved in house? The result appears to be a shrinking pool of contracts. Less work means fewer employees are needed. Hiring freezes follow. Layoffs follow. Entry level opportunities disappear. The traditional outsourcing pipeline begins to break. And when the pipeline breaks, an entire generation of future talent loses its path into the industry. The GCC Paradox The second pillar of the offshore ecosystem consists of Global Capability Centers. These are not outsourcing firms. They are fully integrated extensions of multinational corporations. Think Google. Oracle. Microsoft. Amazon. Major banks. Large pharmaceutical companies. These organizations establish engineering centers overseas and assign them direct responsibility for critical products and services. Historically, GCC jobs have been viewed as more prestigious and more technically demanding than traditional outsourcing positions. Ironically, AI may strengthen GCCs while simultaneously weakening everything around them. The reason is simple. AI tends to amplify highly skilled workers more effectively than less skilled workers. A senior engineer with ten or fifteen years of experience can leverage AI to become dramatically more productive. An architect who already understands systems design, tradeoffs, business requirements, and organizational complexity can use AI as a force multiplier. The challenge is that only a minority of workers possess these capabilities. Companies are no longer searching for people who can merely write code. They are searching for people who can solve problems. That distinction matters. A lot. As a result, GCCs continue competing aggressively for elite talent while the broader outsourcing sector struggles. The strongest engineers migrate toward multinational organizations. The rest of the ecosystem becomes increasingly hollowed out. It is a form of talent cannibalization. The most capable workers are concentrated into a relatively small number of organizations while everyone else faces increasing pressure. A Dangerous Concentration of Talent This creates another risk that receives far less attention. As more elite technical talent becomes concentrated inside multinational corporations, local technology ecosystems become increasingly dependent on decisions made thousands of miles away. The leadership teams controlling these organizations often reside in the United States. The strategic priorities are determined elsewhere. The investments are determined elsewhere. The layoffs are determined elsewhere. If those corporations decide to reduce investment, shift priorities, or close operations entirely, the consequences could ripple through entire regions. The danger is not merely economic. It is structural. When enough talent becomes dependent on a handful of global organizations, local resilience begins to disappear. An ecosystem that cannot stand on its own eventually becomes vulnerable to forces beyond its control. What Can Offshore Workers Do? I have spent many years working alongside offshore teams. Most of the people I met were intelligent, hardworking professionals trying to build better lives for themselves and their families. That makes this situation difficult to watch. Unfortunately, I do not see any perfect solutions. Only coping strategies. The first strategy is to move up the value chain and target positions within Global Capability Centers. That means improving technical skills. Improving communication skills. Learning AI tools. Developing stronger problem solving abilities. The competition is intense, but higher value work is likely to remain more resilient than routine work. The second strategy is to focus on local and regional technology ecosystems. The world may gradually become more multipolar. China has already built a sophisticated technology ecosystem independent of Silicon Valley. Europe is increasingly discussing digital sovereignty. Other regions may eventually follow. Opportunities may emerge closer to home, even if compensation is lower than what American companies traditionally offered. The third strategy is immigration. Historically, moving to higher income countries has been a pathway toward greater opportunity. However, this path appears increasingly uncertain. Many developed countries are facing economic anxieties of their own. Labor markets are becoming more competitive. Public sentiment toward immigration is often more complicated than it was a decade ago. The path remains available, but it is unlikely to be easy. The Bigger Question After my conversation with Kaushik, I found myself thinking about a broader issue. For decades, offshoring was built on the assumption that cognitive labor could be distributed around the world in much the same way manufacturing had been. AI may be challenging that assumption. For the first time, companies have access to tools that can automate portions of cognitive work itself. If that trend continues, the implications extend far beyond India. Far beyond outsourcing. Far beyond technology. Entire labor markets may need to rethink their purpose in a world where intelligence is no longer scarce. Perhaps the real question is not whether AI will disrupt the offshoring industry. Perhaps the real question is what happens when one of globalization’s most successful economic models suddenly stops making sense. And if that day is truly arriving, then Kaushik’s struggle may not be an isolated story. It may be an early warning. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe [https://asiandadenergy.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]
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