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Why India's AI Habit Will Cost You Your Job
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Why India's AI Habit Will Cost You Your Job

Vaibhav Sisinty 31.10.2025 27 445 просмотров 874 лайков обн. 18.02.2026
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🔗 Subscribe to our Newsletter! Get the latest AI updates, tips, and insights straight to your inbox: https://dub.link/staying-ahead India scored 0.27 on the Anthropic AI Usage Index. This single number reveals why we're falling behind in the global AI race—and what it means for your career. I spent 3 days analyzing Anthropic's groundbreaking AI report tracking millions of users across 150+ countries. What I found about India's AI adoption will shock you. 🚨 THE BRUTAL TRUTH: → India should be 18% of AI users globally. We're only 7.2% → Over 50% of our AI usage is just for coding (vs 36% globally) → We're automating instead of augmenting—and that's costing us jobs → 77% of enterprise AI usage is full automation replacing workers → Entry-level IT jobs are disappearing RIGHT NOW The West is using AI to make their entire workforce smarter. India is using AI to make coders faster at tasks AI will soon replace. This isn't just about technology. It's about your job security, India's economic future, and whether we'll be creators or operators in the AI age. 0:00 - INTRODUCTION: India's Shocking 0.27 Score [Hook: Anthropic report analysis, the number that shocked everyone] 0:32 - UNDERSTANDING AUI: The Anthropic AI Usage Index [Explanation: What AUI measures, India's 7.2% vs expected 18%] 1:07 - GLOBAL LEADERS: Who's Winning the AI Race? [Singapore 4.57, USA 3.62, Canada 2.91 - GDP correlation] 1:33 - THE ELECTRICITY ANALOGY: History Repeating [140 years for electricity to reach all of India, same pattern with AI] 2:18 - INDIA'S REALITY: We're in the Bottom 25% [Context about Claude being premium tool, but data still revealing] 3:36 - THE WHY: Quality vs Quantity Problem [Transition: It's not just how much, but HOW we use AI] 3:57 - WHAT THE WORLD IS DOING [DC, California, Florida - diverse AI usage across industries] 5:27 - WHAT INDIA IS DOING: The Code Monoculture Problem [50%+ coding tasks vs 36% globally, overrepresentation in software] 6:25 - THE HIDDEN DANGER: Optimizing What AI Will Replace [We're sharpening one tool while world builds toolbox] 7:30 - AUTOMATION VS AUGMENTATION: The Game-Changing Concept [Two fundamentally different relationships with AI explained] 8:34 - THE SURPRISING DATA: High Adopters Don't Automate More [Countries with high AUI actually augment more, not automate] 9:09 - WHERE INDIA STANDS: The Automation Nation [India's 0.27 + coding focus = heavy automation preference] 9:32 - THE JOB CRISIS: Junior Positions Being Erased [Entry-level IT jobs disappearing, calculator analogy] 10:41 - WHAT BUSINESSES ARE DOING: The 77% Reality [Enterprise API data, automation at scale happening now] 11:28 - THE COST PARADOX: Companies Automate Expensive Tasks [Higher-cost tasks see MORE automation, not less] 12:11 - THE ONE ADVANTAGE: Context as Career Protection [Complex tasks need context, diminishing returns explained] 13:06 - THE BRUTAL TRUTH: Two Types of Jobs Splitting [Task-based = automated, Context-rich = augmented] 13:53 - THE REAL QUESTION: Replaceable or Indispensable? [Final call to action, are you automating or augmenting?] 15:07 - CLOSING: Join the Conversation [Comment prompt, wake-up call, AI revolution is here] -------- To Know More, Follow Vaibhav Sisinty On ⤵︎ Instagram @VaibhavSisinty https://www.instagram.com/vaibhavsisinty Twitter @VaibhavSisinty https://twitter.com/VaibhavSisinty Facebook @VaibhavSisinty https://www.facebook.com/vaibhavsisinty/ LinkedIn - Vaibhav Sisinty https://www.linkedin.com/in/vaibhavsisinty --------

Оглавление (19 сегментов)

  1. 0:00 INTRODUCTION: India's Shocking 0.27 Score 71 сл.
  2. 0:32 UNDERSTANDING AUI: The Anthropic AI Usage Index 98 сл.
  3. 1:07 GLOBAL LEADERS: Who's Winning the AI Race? 86 сл.
  4. 1:33 THE ELECTRICITY ANALOGY: History Repeating 124 сл.
  5. 2:18 INDIA'S REALITY: We're in the Bottom 25% 260 сл.
  6. 3:36 THE WHY: Quality vs Quantity Problem 48 сл.
  7. 3:57 WHAT THE WORLD IS DOING 210 сл.
  8. 5:27 WHAT INDIA IS DOING: The Code Monoculture Problem 157 сл.
  9. 6:25 THE HIDDEN DANGER: Optimizing What AI Will Replace 170 сл.
  10. 7:30 AUTOMATION VS AUGMENTATION: The Game-Changing Concept 187 сл.
  11. 8:34 THE SURPRISING DATA: High Adopters Don't Automate More 82 сл.
  12. 9:09 WHERE INDIA STANDS: The Automation Nation 73 сл.
  13. 9:32 THE JOB CRISIS: Junior Positions Being Erased 188 сл.
  14. 10:41 WHAT BUSINESSES ARE DOING: The 77% Reality 121 сл.
  15. 11:28 THE COST PARADOX: Companies Automate Expensive Tasks 87 сл.
  16. 12:11 THE ONE ADVANTAGE: Context as Career Protection 153 сл.
  17. 13:06 THE BRUTAL TRUTH: Two Types of Jobs Splitting 105 сл.
  18. 13:53 THE REAL QUESTION: Replaceable or Indispensable? 215 сл.
  19. 15:07 CLOSING: Join the Conversation 15 сл.
0:00

INTRODUCTION: India's Shocking 0.27 Score

I just spent three days analyzing Anthropic's new AI report. They tracked millions of users across 150 plus countries. And when I got to India's number, I had to refresh the page. I thought there was an error. India's score of just 0. 27. Now, before you ask, what does 0. 27 even mean? Let me explain because understanding this number is crucial to understanding where we're headed as a country.
0:32

UNDERSTANDING AUI: The Anthropic AI Usage Index

Anthropic created AUI, Anthropic AI usage index, a metric that helps them analyze and assemble Claude's user data for their research. AUI asked one question. If India is 18% of the world's workers, shouldn't we be 18% of AI users, too? But we're not. We're only 7. 2%. That's our problem. So, who are the global leaders according to the AUI? The anthropic report finds a powerful, almost undeniable correlation. The higher a country's GDP per capita, the higher its AI usage. The map of AI adoption looks hauntingly similar to the map of global wealth. The countries
1:07

GLOBAL LEADERS: Who's Winning the AI Race?

leading AI adoption are small, technologically advanced, high income nations. Singapore has an AUI of 4. 57. That means they are using claude over 4 and a half times more than expected. Canada is at 2. 91. And despite being a large nation, the United States is also a leader with an AUI of 3. 62. If you are wondering why China is not in this list, it's because China hasn't allowed its people to use claude. The key finding here is that AI adoption is
1:33

THE ELECTRICITY ANALOGY: History Repeating

geographically concentrated just like previous transformative technologies like electricity or personal computers were. Think about it. Electricity first came about in the 1880s, lighting up just a few streets in London and New York at first, mostly as a novelty for the wealthy. The west was fully electrified within 50 years while colonial hubs like Kolkata and Bombay gained power by 1905 but only for the ports and the powerful. It became a slow postindependence mission for India. The last mile India's last village was lit in 2018. It took 140 years for electricity to reach the last person in India. The productivity benefits, the innovation, the wealth creation, it's all happening in a concentrated set of already rich regions. This brings us to
2:18

INDIA'S REALITY: We're in the Bottom 25%

India. With our massive workforce, our IT capabilities and our large youth population, you would expect us to have an AUI of at least one if not higher. The reality, India's AUI is 0. 27, which means we are using AI at a rate that is less than one/ird of what would be expected based on the size of our workforce. Now, speaking outside of the report, there is something we need to keep in mind. The report is based on users of Claude, which is a paid premium tool. In a price sensitive country like India, free tools like Gemini and ChatGpt are popular among people. So this report is not the ultimate survey. It's just based on users of Claude. However, it gives us a powerful look at India's early high-end adopters. In a country like ours where free alternatives are king, the people paying for a premium AI like Claude are most likely to be professionals who need it for specialized work like coding. This context is key. So keep that in mind. Now back to the anthropic report. The report highlights how we are not in the league of the US or Singapore. We are not even in the middle tier. We are in the bottom 25% of countries when it comes to per capita adoption. This is the first shocking number and the anthropic report is very clear about the danger it represents. Right now, richer countries are using AI way more than developing ones. This could make the economic gap between them even bigger.
3:36

THE WHY: Quality vs Quantity Problem

But why? Why is our score so low? The answer to the why lies in our what. What are we using AI for? Because to win this race, we don't just have to work on the quantity of our AI usage, but also on the quality of it.
3:57

WHAT THE WORLD IS DOING

Let me show you something that really opened my eyes. Within the United States, there's a massive variation in how different states use AI. And it tells us a lot about what successful AI adoption looks like. Washington DC leads with an AUI of 3. 82. Utah's at 3. 78, actually higher than California. California comes in at 2. 13. New York at 1. 58. So what's DC doing differently? The report shows DC has disproportionate use for document editing, information retrieval, job applications, and career assistance, all of which are tasks common in government and policy work. California is using AI for software development mixed with creative industries and digital marketing. Florida is using it for business advice, financial services, and even fitness related queries. Each region has adapted AI to its local economic strengths. They're using AI in diverse ways across multiple industries touching every part of their economy. And when you look at high adoption countries globally, you see the same pattern. The usage is incredibly diverse. People in these countries use AI for household management, medical questions, travel planning, creative projects, business strategy, and education. AI is integrated across every aspect of life. They're not just using AI for one thing. They're using it for everything.
5:27

WHAT INDIA IS DOING: The Code Monoculture Problem

Now, let me show you India's data. And this is where things get uncomfortable. The report found that coding tasks account for over half of all AI usage in India compared to roughly one-third globally. When you look at India's over represented request clusters, the things Indian users ask AI to do more than any other country. They focus almost exclusively on software development, debugging web applications, building business software, mobile app development, technical problem solving, code optimization. It's all just coding. Now look, on one hand, this makes complete sense. India has a world-class IT sector. We have millions of developers. Our tech industry is our greatest strength. Of course, our developers are going to be early adopters of AI tools. And in the short term, this is actually good news. We're making our strongest sector even more efficient. Our coders are getting faster. Our companies are saving time and money. But here's where I started
6:25

THE HIDDEN DANGER: Optimizing What AI Will Replace

losing sleep over this data. While we are using AI to make our coders more productive at the tasks they already do, the rest of the world is using AI to transform entire industries that they weren't even competitive in before. We're optimizing our existing strength. They're building entirely new capabilities. We're sharpening one tool. They're creating a whole new toolbox. And here's the brutal economic reality. We're concentrating all our AI adoption in the exact domain that's easiest for AI to eventually automate. Think about it. Software development is pure logic, clear inputs, clear outputs, objective success criteria. It's literally one of the most AI friendly tasks that exist. We are using AI to become better at the job that AI is coming to take. But honestly, that's not even the scariest part of this report. The scariest part is how we're using AI. Because it's not just about what task you do with AI, it's about the relationship you have with it. And this is where everything changes.
7:30

AUTOMATION VS AUGMENTATION: The Game-Changing Concept

Okay, this genuinely changed how I think about my entire career. So, pay attention. There are two fundamentally different ways to use AI and the anthropic report calls them automation and augmentation. Let me explain what these actually mean. Automation is when you give AI a task and it completes it independently. You're delegating work. You say, "Write this code, debug this error, generate this report, and you walk away. " AI does it. You take the output, done. It's fast. It's efficient. You save time. But here's the problem. You don't learn anything. You're just replacing your own effort with AI's effort. Augmentation is completely different. With augmentation, AI becomes your thinking partner. You're still in control, but you're using AI to get smarter. You're learning. You're growing. You're becoming more capable with every interaction. Automation replaces you. Augmentation empowers you. Now, here's where the data gets absolutely fascinating. I assume the most advanced AI users would be automating everything, right? Maximum delegation, maximum efficiency. just let AI do all the work. Turns out the opposite is true. The report found that high adoption countries actually
8:34

THE SURPRISING DATA: High Adopters Don't Automate More

use AI in a less automated way. After controlling for what types of tasks people are doing, low adoption countries are way more likely to just delegate complete tasks to AI. While high adoption countries tend toward learning and collaborative iteration, Singapore, the United States, Australia, the countries using AI the most are not using it to replace work. They're using it to make their workers smarter, more creative, more capable of handling complex problems. They're building human capacity, not replacing it.
9:09

WHERE INDIA STANDS: The Automation Nation

So where does India fit in this framework? With our AUI of 0. 27 and our extreme concentration in coding tasks, we're leaning heavily toward automation. We're using AI to delegate tasks, not to learn, to replace effort, not to build capability. And look, I get it. When you're working in a high pressure environment with tight deadlines, it's tempting to just let AI write the code and move on to the next
9:32

THE JOB CRISIS: Junior Positions Being Erased

task. But here's what's happening as a result. Indian IT services companies are already cutting junior positions. The entry-level roles that used to be the stepping stones for thousands of engineering graduates every year are being erased. Why? Because if you're using AI to complete tasks, you don't fully understand. If you're copying outputs without learning the underlying logic, if your entire value proposition is just executing simple, clearly defined work, you're not becoming more valuable. You're proving you're replaceable. The task being automated right now are basic execution, simple problem solving, and entry-level debugging. The easiest things for AI to fully automate. When companies need to cut costs, those jobs go first. Here's how I think about it. We're giving people a calculator for the math test. Sure, they get answers faster, but underneath they're forgetting how to do the math. They're not learning the formulas, the reasoning, the problem solving skills. Meanwhile, people in high adoption countries are using calculators to check their work, explore more complex problems, and understand concepts at a deeper level. They're using the tool to get smarter, not to avoid thinking.
10:41

WHAT BUSINESSES ARE DOING: The 77% Reality

But individual usage is only part of the story. Let me show you what businesses are doing with AI because this is where the real transformation is happening. Anthropic analyzed over a million enterprise API calls. These are companies that have integrated claw directly into their operations. Real businesses deploying AI at scale. And they found something that should wake up every entry-level worker. 77% of enterprise AI usage is full automation. Not augmentation, not collaboration, automation. Companies are programmatically replacing entire tasks that employees used to do at scale. And here's what really surprised me. I thought companies would start by automating the cheapest, simplest tasks first. Why spend more money if you don't have to? Completely wrong. The data
11:28

THE COST PARADOX: Companies Automate Expensive Tasks

shows that higher cost tasks actually see more usage. Each 1% increase in average task cost is associated with a 3% increase in how much businesses use AI for that task. Why? Because businesses aren't optimizing for cost. They're optimizing for value. Simply speaking, companies will happily pay more to automate complex, expensive tasks if those tasks provide enough economic value to justify the investment. This is creating a massive split in the job market. Entry-level task-based work, highly automatable, experience-based, contextrich work much harder to replace.
12:11

THE ONE ADVANTAGE: Context as Career Protection

But there's one thing in this report that actually gave me hope. One factor that might save some careers. The report found that complex tasks require way more context than simple ones. And there are diminishing returns. For each 1% increase in how much context you give to AI, you only get a 0. 38% increase in how much useful output it can produce. Why does this matter for your career? Because for coding tasks, context is easy. Your entire codebase is sitting in GitHub. Everything's documented. AI can read it all. But for complex business decisions, that context is scattered everywhere. It's in emails from 3 years ago that nobody saved properly. It's in conversations that never got documented. It's in someone's head as tribal knowledge. It's in relationships and institutional memory that can't be written down. AI can't access what doesn't exist in an organized, accessible form. So, here's the brutal
13:06

THE BRUTAL TRUTH: Two Types of Jobs Splitting

career truth. If your job is just executing clearly defined tasks with minimal context requirements, following documented processes, and doing routine work that AI can handle with a few instructions, you're at high risk. But if your value comes from tacit knowledge, understanding how your organization really works, knowing the unwritten rules, having the relationships, seeing the patterns that aren't in any document, you become more valuable because a I needs what's in your head to work effectively. The job market is splitting right now. Entry-level task based work is being automated, experience-based, contextrich work is being augmented. Which side are you positioning yourself for?
13:53

THE REAL QUESTION: Replaceable or Indispensable?

So, let me bring this all back to where we started. India's AUI is 0. 27. We're using AI at 1/3 the rate we should be based on our workforce size. But the quantity problem isn't even the scariest part. The quality problem is worse. Over half of our usage is concentrated in coding. We're automating instead of augmenting. We're optimizing one narrow domain instead of transforming our entire economy. Meanwhile, 77% of global businesses are already deploying AI to automate complete tasks. And they're not starting with the cheap, easy stuff. They're going after the high value, complex work. The gap isn't just wide. It's widening every single day. So, here's the question I want you to ask yourself. Are you replaceable or indispensable? Are you using AI to get answers faster or to get fundamentally smarter? Are you copying outputs or learning the logic behind them? Are you automating yourself out of a job or augmenting yourself into an irreplaceable position? Because that 0. 27 score, it doesn't have to define us if we change how we think about AI. This anthropic report is our wakeup call. The AI revolution isn't coming. It's already here. And the only question that matters is, are you ready? Drop a comment and tell me, are you
15:07

CLOSING: Join the Conversation

automating or augmenting? Because this is a conversation we all need to be part of.

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