India, Nov. 22 -- There's a moment every professional dreads: that instant you realise the work that once defined you can now be done by a machine: faster and more cheaply. For V Shrinath, the Bengaluru-based founder of Salient Advisory and a Google Startups mentor, that moment arrived last year. He had spent years straddling consulting and technology. He knew how these worlds operated, how firms sold expertise, how talent pipelines were built, and how carefully the illusion of craft is maintained. But he was also watching AI evolve closely. He kept coming back to one question: when would AI replicate the parts of his job he considered as expertise? He broke his work down line by line, the kind of audit consultants recommend to clients but almost never do for themselves. The analysis was scary but telling. He saw that much of consulting followed patterns. AI could accurately handle topics like "How do you write specifications for development or Go-to-market?" The processes don't change. AI knows them. It executes them. It standardises them. Technology work was no safer. AI could read patterns better than humans, spot anomalies faster, even suggest fixes. Creative code? That was still human turf, at least for now. But everything around it, all the scaffolding, all the logic, all the boring bits? It was slipping out of human hands. Shrinath realised what most white-collar professionals still refuse to accept: AI wasn't going to disrupt his job. It was going to expose it. He chose a direction that others might have read as a leap. To him it was the logical move. "I didn't move from stability to risk," he said. "I moved away from a future that no longer made sense." He turned toward the kind of work that remains firmly human: reading situations with incomplete information, opening conversations that data cannot start, and piecing together insights that aren't captured anywhere. His story isn't an exception. It is a preview. Because everywhere you look, the surface is cracking. Beneath it lies something uncomfortable: much of modern white-collar work doesn't require the expertise we think it does. The Big Four professional services firms have announced layoffs. Inside these firms, senior partners concede what the press statements don't. Close to 60% of analyst-grade work is now done or heavily assisted by generative AI. Analysts who once spent nights writing reports, synthesising data, and building decks are discovering the machine does the same thing in minutes. Managers quietly complain that new hires cannot write, cannot structure, cannot think - because the tools do it for them. But the deeper crisis is this: the tools outperform the juniors at their own jobs. The first ten rungs of the career ladder have vanished. Journalism is cracking even faster. Global newsrooms now run AI systems that churn out business briefs, sports updates, earnings summaries, and weather stories at near-zero cost. The use of synthetic articles by newsrooms has been going by significantly year on year. In India, rewrite desks are testing automated bots. Reporters who spent careers reworking press releases now face a void: the "craft" they believed in turns out to be something a machine can reproduce at scale. What remains is the one thing AI cannot do - report. And many professionals, shielded for years by desk jobs, never learned how. Marketing, finance, legal, education - all face the same story with different accents. AI studios now automate ad variations and campaign concepts. AI drafts contracts in minutes. AI tutors personalise lessons better than most teachers. For decades, white-collar work rested on a comfortable assumption: that intelligence, judgment and experience made people irreplaceable. But when AI reads scans more accurately than a radiologist, drafts contracts faster than a junior lawyer, writes sharper reports than an analyst, builds tighter lesson plans than a tutor, and coaches sales agents more consistently than a manager, what is left of the old professional hierarchy? The data reflects a brutal sorting ahead. Roles with "high human interaction" - negotiation, conflict resolution, relationship management - are projected by the World Economic Forum to grow 21-25% over the next five years. Roles dependent on predictable cognitive tasks are projected to shrink by over 40%. The future belongs to those who step out from behind information and into the world. Those who build moats on originality, not outputs. This is what Shrinath understood. He isn't future-proofing a career. He is future-proofing an identity. Because what is collapsing now is not employment. It is the story professionals tell themselves about why they matter. And that is the part that should leave every reader slightly breathless: AI is not taking away jobs. It is taking away excuses. The people who will endure are not the ones who learn to use the machine. It will be those who learn to do what the machine cannot: look clearly, judge wisely, and create meaning that isn't already on the page....