In February 2026, a quiet revolution began that would fundamentally alter the trajectory of global technology—and nowhere will its impact be more profound than in India. Matt Shumer, a six-year veteran of the artificial intelligence industry who has founded companies, invested in frontier labs, and spent literally thousands of hours working with the latest models, published a declaration on his personal website that would spark worldwide conversation. The title was simple yet powerful: "Something Big Is Happening." Within days, that declaration had been read nearly fifty million times, igniting debates from Silicon Valley to the streets of Bangalore, from tech conferences in Hyderabad to startup offices in Gurgaon.
"I ve been holding back," Shumer confessed in the opening of his now-famous essay. Every time friends or family asked about AI, he had given them the polite version—the conversation-starter version that did not make him sound like an alarmist. But after weeks of intensive conversations with GPT-5.3 Codex and Claude Opus 4.6, he could no longer stay silent. The people he cared about deserved to know the truth.
What Shumer discovered was not merely incremental improvement. It was not the familiar pattern of AI getting "a little better than last month." It was a phase change—a fundamental transformation in what artificial intelligence can do. He put it most starkly: "We are in February 2020 for AI." Just as the world did not realize in February 2020 how drastically COVID would change everything, most people today do not realize how drastically AI is about to change everything.
For India—a nation that has built its modern economic miracle on the foundation of information technology services, a country with over five million software developers and millions more in related professions—this message could not be more relevant or more urgent. Something big is happening, and India must decide how to respond.
table of contentTo appreciate why Shumer's message matters so profoundly for India, we must first understand what makes the current AI transformation fundamentally different from previous technological shifts. India has navigated technological change before—the transition from mainframes to client-server, the internet revolution, the mobile computing wave. Each brought challenges, but India adapted. So why is this time different?
The most important change Shumer describes is the shift from AI as a tool that follows commands to AI as a partner that thinks alongside you. For years, interacting with AI meant giving instructions and receiving outputs. You asked a question, AI provided an answer. You gave a prompt, AI generated content. The interaction was fundamentally transactional: input leads to output, like using any other software tool.
But what Shumer experienced was qualitatively different. He watched GPT-5.3 Codex independently architect production-grade systems—making architectural decisions that would normally require a senior engineer with years of experience. He saw the AI correct his suboptimal prompts, doing so politely but firmly, exactly as a knowledgeable colleague might. He observed Claude Opus 4.6 handling legal drafting, financial modeling, and strategic business planning—producing outputs that were not just correct but exhibited "elegance, restraint, and taste."
This is the crucial distinction. AI is no longer just executing tasks we assign it. It is beginning to exercise judgment, to have preferences, to make choices that reflect something analogous to human reasoning. And it is doing so at a level that rivals or exceeds what most professionals can achieve. As Shumer himself admitted: "In many purely technical domains, I am already no longer a necessary part of the loop. The model can do the core intellectual work better and faster than I can."
For India, where the economy depends heavily on IT services and software development, this represents a fundamental shift in competitive dynamics. The traditional model of Indian IT—providing cost-effective coding and maintenance services to Western clients—is being disrupted at its foundation.
Perhaps the most alarming aspect of Shumer's analysis is his emphasis on speed. He explicitly states that we are not "talking about gradual displacement over a decade." Instead, he suggests we are "talking about twelve to twenty-four months until the majority of white-collar technical work is fundamentally transformed."
This timeline is critical. It means the transformation is not something our children will need to deal with—it is happening now, within the timeframe of typical career planning cycles. The Indian software engineer who assumes they have years to adapt may find themselves suddenly obsolete within months.
India has always prided itself on being quick to adapt. The nation's whole modern economic history is built on the ability to see changes coming and respond faster than competitors. But the speed Shumer describes may challenge even India's legendary adaptability. The water is already up to our chests, and it is rising fast.
Shumer makes another crucial point that deserves attention: AI still makes mistakes, but those mistakes are becoming fewer and less severe at an astonishing rate. The gap between "AI with human supervision" and "human alone" is now smaller than the gap between "average human" and "top one percent human" in many fields.
This observation matters because it changes how we should evaluate AI. We cannot simply look at current limitations and conclude AI is not ready. We must consider trajectory—the rapid improvement curve that shows AI moving beyond "useful helper" to "genuine competitor" in an accelerating path. The AI of twelve months from now will make the AI of today look primitive, just as today's AI would amaze researchers from even a few years ago.
table of contentIndia's IT services sector has been the crown jewel of the nation's economic transformation. Companies like Tata Consultancy Services, Infosys, and Wipro have built global reputations, employing millions of Indians and generating billions in foreign exchange earnings. This sector has been the foundation on which many Indian middle-class families built their dreams. But Shumer's analysis reveals a troubling truth: this foundation is being shaken.
The fundamental business model of Indian IT services has been labor arbitrage—providing skilled but cost-effective technical talent to clients in expensive Western markets. When a US company could pay an Indian developer one-third of what it would pay an American developer for equivalent work, Indian IT companies could offer competitive pricing while maintaining healthy margins.
But what happens when AI can perform the same technical work faster, better, and at near-zero marginal cost? Shumer points out that AI models can now do "the core technical competence—the thing that used to require seven to fifteen years of training—at or above mid-senior level by models that cost twenty dollars per month."
This is the existential threat facing Indian IT. The very advantage that made Indian IT globally competitive—cost-effective human labor—is being undermined by AI that offers superior performance at a fraction of the cost. This is not a future scenario; this is happening now.
For the millions of young Indians joining the workforce each year with dreams of software development careers, the situation is particularly dire. Traditional IT services companies have always relied on a pyramid structure: many junior developers at the base, fewer mid-level engineers in the middle, and a small number of senior architects at the top. The junior developers handled the routine coding work that did not require senior expertise.
But AI is precisely targeting this routine coding work. When AI can write production-quality code, debug complex systems, and even architect new solutions, the need for junior developers diminishes dramatically. The entry-level positions that have traditionally served as the gateway to IT careers are disappearing.
This creates a vicious cycle: without entry-level jobs, aspiring developers cannot gain experience; without experience, they cannot qualify for the fewer remaining positions. The pipeline that has fed Indian IT for decades is being disrupted.
The big IT services companies—TCS, Infosys, Wipro, Accenture India—face a particular challenge. Their business models were designed for a world where human labor was the primary input. Their extensive workforces, while historically an asset, now represent a cost structure that cannot compete with AI-driven alternatives.
These companies are not unaware of the threat. Many have launched AI initiatives and reskilling programs. But the pace of transformation may be faster than their ability to adapt. The question is not whether these giants will transform, but whether they can transform quickly enough to remain relevant.
table of contentWhile the challenges are real, India also possesses unique advantages that, if properly leveraged, could turn this crisis into an unprecedented opportunity. The key lies in recognizing that the game has changed—and India can win by playing by new rules.
India's population of 1.4 billion people represents more than just a challenge—it represents an opportunity. Every one of these 1.4 billion people is a potential user of AI-powered services, a generator of data that can improve AI systems, and a potential creator leveraging AI tools.
In the AI era, data is the new oil. And India, with its vast population engaged in diverse economic activities—from agriculture to healthcare, from finance to education—generates enormous quantities of data. This data, when combined with AI capabilities, can fuel innovation across countless domains.
Moreover, India's population represents a massive market for AI applications. The problems that AI can solve in India—healthcare access, agricultural productivity, educational quality, financial inclusion—are enormous in scale and impact. Companies that solve these problems for India will have solutions that can potentially be adapted for similar markets worldwide.
Indians have long been renowned for their ability to find innovative solutions with limited resources—the concept known as "jugaad." This mindset, often dismissed as informal or unsystematic, is actually a tremendous asset in the AI era.
When AI tools become widely available, the constraint shifts from having technical skills to having creative vision. The Indian ability to improvise, to find workarounds, to see possibilities where others see obstacles—these become competitive advantages. An Indian entrepreneur with AI tools and a jugaad mindset can achieve what previously required large teams and massive resources.
This is not to say that rigor and systematic thinking are unimportant—they remain crucial. But the combination of Indian creativity with AI capabilities represents a superpower that few other nations can match.
For decades, Indian IT has focused primarily on serving Western clients—maintaining legacy systems, implementing enterprise software, providing technical support. This has been economically valuable but has often meant solving problems defined by others.
The AI era offers India an opportunity to shift from being a service provider to being a problem solver. India's own challenges—in agriculture, healthcare, education, infrastructure, financial inclusion—are immense. And these are precisely the domains where AI can make the biggest impact.
Consider agricultural advisory services that can help farmers optimize yields. Or diagnostic tools that can extend healthcare to remote areas. Or personalized learning platforms that can address educational gaps. These are problems worth solving, and AI makes them solvable in ways that were previously impossible.
The companies and individuals who tackle these problems will not just build successful businesses—they will help build a better India. That is a motivation that goes beyond economics.
table of contentUnderstanding the challenge is the first step; responding effectively is the next. India's response to the AI transformation must be comprehensive, coordinated, and urgent. Several strategic pillars must guide this response.
India's education system has produced millions of engineers, many of whom have built successful careers around the world. But the skills that have made these engineers successful are being disrupted. The ability to write code in specific programming languages—valuable as it has been—is becoming less differentiating as AI handles routine coding tasks.
What becomes more valuable is understanding systems architecture, knowing how to integrate multiple components, and being able to direct AI tools toward desired outcomes. Education must evolve to develop these capabilities.
This does not mean abandoning technical education. Rather, it means complementing syntax-focused training with system-thinking, problem-framing, and AI collaboration skills. Students should learn not just how to code but how to identify what should be coded, how to evaluate AI-generated solutions, and how to integrate AI capabilities into larger systems.
The institutions that adapt fastest will produce graduates who thrive in the new environment. Those that cling to old models will see their students struggle.
For the millions of Indians already working in IT, the transformation must be different. These professionals have families to support, mortgages to pay, and careers to build. They cannot simply abandon their existing skills and start over.
The key is to transform existing capabilities rather than replace them. An experienced software developer understands systems, processes, and client needs. These skills remain valuable—but they must be supplemented with AI collaboration capabilities.
The transformation path involves learning to work with AI as a partner rather than a tool. This means understanding AI strengths and weaknesses, developing skills in prompting and evaluation, and learning to integrate AI outputs into larger workflows. It means becoming an orchestrator of AI agents rather than a performer of routine coding tasks.
Companies and governments must support this transformation through comprehensive reskilling programs. The alternative—massive displacement without support—would be catastrophic.
The government has a crucial role to play in enabling India's AI transformation. This includes investment in AI infrastructure—compute resources, data platforms, research facilities—as well as policy frameworks that encourage innovation while managing risks.
India's approach to AI governance must balance competing concerns. On one hand, excessive regulation could stifle innovation and push activity to more permissive jurisdictions. On the other hand, inadequate governance could allow harms to proliferate and erode public trust.
The government must also address the digital divide that could exacerbate inequalities during the transition. Access to AI tools and training should not be limited to urban professionals; India's millions of rural citizens must also have pathways to participate in the AI economy.
table of contentBeyond strategic analysis, the most important question is: What can I do today? Whether you are a student, a working professional, or an entrepreneur, there are concrete steps you can take to thrive in the AI era.
If you are a student—high school or college—consider what Shumer advises: "The skill that matters most now is learning how to think in loops with extremely powerful models. That skill can be developed faster outside traditional institutions."
This means developing skills that AI cannot easily replicate. Critical thinking—the ability to evaluate arguments, identify flaws, and synthesize conclusions—becomes more valuable when AI provides abundant information. Creativity—generating novel ideas and approaches—remains distinctly human. Communication—the ability to articulate ideas, persuade others, and build relationships—underlies all successful human collaboration.
Technical skills remain relevant, but their nature is changing. Rather than focusing on memorizing syntax, focus on understanding systems. Learn how to use AI tools effectively. Practice solving problems with AI assistance. Build projects that demonstrate your ability to direct technology toward meaningful goals.
Remember: you are not competing against AI. You are learning to work with AI. That framing makes all the difference.
If you are already working in IT, the transformation may feel threatening. But Shumer's analysis also points to opportunities. The key is to pivot before you are forced to pivot.
Start by deeply integrating AI into your current work. Use AI tools for the tasks you perform daily. Understand what AI does well and where it still struggles. Develop intuitions for effective collaboration.
Then, look for opportunities to add value beyond what AI provides. This might mean developing expertise in domains where AI is weak—understanding complex business requirements, managing stakeholder relationships, navigating organizational politics. Or it might mean becoming a specialist in AI implementation—helping organizations adopt and integrate AI systems effectively.
The professionals who thrive will be those who view AI as a colleague rather than a competitor, leveraging its capabilities while contributing their unique human strengths.
If you are an entrepreneur—or aspire to be one—the AI era offers unprecedented opportunities. The cost of building technology products has plummeted. The barriers to entry have collapsed. The playing field has never been more level.
The most successful ventures will solve real problems for real people. Look at India's challenges: agricultural productivity, healthcare access, educational quality, financial inclusion, urban congestion. These are problems worth solving, and AI makes them solvable.
Build solutions that address Indian needs, and you will have a market of 1.4 billion people. Adapt those solutions for similar markets worldwide, and you will have a global business. This is the path that Indian entrepreneurs can follow.
table of contentSomething big is happening—and India stands at a crossroads. The choices made in the coming months and years will determine whether this transformation becomes a crisis or an opportunity.
The path forward is not without challenges. The IT services model that has served India well for decades is being disrupted. Traditional jobs are being transformed. The skills that have been valuable are being redefined. This is real, and it deserves serious attention.
But the path forward is also filled with possibility. India's population represents a market and a talent pool unlike any other. Indian ingenuity has always found ways to thrive despite constraints. And the problems that India needs to solve—problems of inclusion, access, and quality—are precisely the problems that AI can help address.
Matt Shumer's warning is clear: "The world is changing faster than almost anyone realizes, and the window to get ahead of it is still open—but it is closing quickly." The question for India is whether we will seize this moment or let it pass.
The history of modern India is a story of transformation—from independence to economic liberalization, from agricultural economy to IT powerhouse. Each transformation seemed impossible until it happened. Each was driven by Indians who saw opportunity where others saw threat.
This is that kind of moment again. Something big is happening. And India—with its talent, its ingenuity, its ambition—can make this transformation its greatest achievement yet.
The phoenix rises from the ashes. And India, too, will rise.
Absolutely not. The democratization of AI means that the tools and knowledge are more accessible than ever before. What matters now is not when you start but how you approach learning. Focus on understanding how to collaborate with AI rather than trying to compete with it on technical grounds.
Every day, millions of people are discovering AI for the first time. The best time to start was yesterday. The second-best time is today. The resources are available; the willingness to learn is the only prerequisite.
The future is not about humans versus AI—it is about humans with AI versus humans without AI. Those who learn to work effectively with AI will thrive; those who resist will struggle to compete.
Rather than viewing AI as a replacement, see it as an enhancement. An AI assistant can handle routine tasks, freeing you to focus on higher-value work. It can amplify your capabilities, not diminish your worth. The question is not whether AI will change your job—it will—but whether you will change with it.
Never has it been easier to build without traditional credentials. AI tools can translate ideas into working products, can help navigate technical challenges, and can compensate for gaps in formal training.
What matters is not your degree but your ideas, your persistence, and your ability to identify problems worth solving. The barriers to technical creation have collapsed. What remains is the creative spark—and that cannot be taught, only nurtured.
India does not need to compete on the same terms as Silicon Valley. The Valley builds foundation models requiring billions of dollars; India can win by building applications that solve real problems for real people.
India's advantage is scale—scale of population, scale of problems, scale of data. The solutions built for India's 1.4 billion people can be adapted for similar populations worldwide. This is not a劣势; it is a competitive advantage that few can match.
The most important skill is the ability to learn—and to keep learning. In a world of accelerating change, the specific knowledge you have matters less than your capacity to acquire new knowledge.
Beyond that, cultivate critical thinking to evaluate information, creativity to generate novel ideas, and empathy to understand human needs. These are the capabilities that AI augments but cannot replace. They are the skills that will define success in the AI era.
➡️Something Big Is Happening: India's Transformative Moment in the Age of AI
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