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Silicon Valley is doing what it does best: turning hiring into a spectator sport. A 'Battle of the Billions' is being fought in corridors of Menlo Park and Mountain View, as recruiting AI researchers escalates to the level of professional athlete trades.

Meta recently lured top researchers from OpenAI and other companies with compensation packages reportedly totalling $300 mn. Google is aggressively rehiring 'boomerang' workers, including AI pioneers like Noam Shazeer, who left to build Character.ai, with multibillion-dollar deals. Sam Altman has tweeted about '10,000x' researchers shifting the gravity of the industry, and has taken his own 'boomerangs' back from Mira Murati's Thinking Machines.

Corporate India is witnessing its own version of this skirmish. GCCs and IT services giants are locked in a fierce contest for a narrow pool of AI and ML engineers, with AI talent demand jumping over 50%. Familiar symptoms are here too: sharp compensation for niche skills, anxious leaders and raging Fomo. But are we fighting for the right soldiers?

The most important AI talent in your organisation is not the 1% you poach from frontier labs. It's the other 99%. The debate often equates 'AI talent' with elite researchers, model builders and PhDs from Stanford or IITs. To truly win in the AI Age, we must reframe this: real AI talent is every employee - in HR, marketing, operations or finance - who uses AI to augment their work and become a '10x professional'. The far bigger prize is making every function in your company significantly more capable with AI.

At Davos 2026 last week, AI pioneer Andrew Ng warned the risk is not AI replacing humans, but that those who cannot use it will become far less productive. He said he would 'strongly prefer to hire' a marketer or HR professional who can use AI to build tools that improve their work. For India, he cautioned that without rapid upskilling, job disruption could be severe. But if the workforce adapts quickly, value created could be enormous.

It's not AI that will take your job, but a human using AI who could. This is the reframing India Inc - and Silicon Valley - needs. Real AI talent is not only the elite priesthood training foundation models. It's also the mainstream workforce learning to work with AI as fluently as they once learned to work with email, spreadsheets and search.

Barrier to this transformation was the 'coding wall'. But it has crumbled with 'vibe coding', a term Andrej Karpathy used for a shift where users describe outcomes in plain English, and AI generates the code and workflows. Non- tech professionals can now use 'agentic' tools like Lovable, n8n or Replit to automate tasks that once required a development team. 'English is the new coding' is no longer a quip, it's a practical workplace skill.

Imagine an HR manager who doesn't wait for IT to build a tool. Using a 'vibe' prompt, he uses n8n to automate a recruiting workflow: scanning resumes, sentiment-analysing interview transcripts, and automatically scheduling follow-ups based on cultural fit scores.

A brand manager creates a custom agent on Lovable that monitors real-time social media trends and automatically generates (and posts) contextually relevant ad creatives, adjusting the output based on live audience engagement.

A logistics team lead can vibe-code a dashboard that connects supply chain data to weather APIs, automatically rerouting shipments and notifying vendors the moment a disruption is predicted.

These are the new 10x professionals. They are not engineers. They are domain experts who have been rewired. None of these tasks require a PhD. What they require is AI literacy: ability to delegate to AI, verify it, govern it and redesign work around it. We need AI literacy, not as reskilling or a training programme. It's about rewriting your new OS for work in the Age of AI.

So, while you compete for elite researchers at your labs, don't miss the larger, and more controllable, competitive advantage of building an organisation where AI literacy is widespread, safe, governed and practical. Future AI talent strategy will not be judged by how many ML PhDs you have hired. It will be judged by something more operational: how many people in your company can reliably turn intent into outcome using AI.

The next decade will reward companies that stop treating AI as a department and start treating it as a language. In the old world, talent meant 'Can you do the work?' In the new world, talent means 'Can you orchestrate the work?' - with humans, models, agents, tools and judgement woven together.

Real winners of the AI war will not be the companies that pay $10 mn for a single researcher. They will be the companies that empower their 99% to vibe with technology.

Real AI talent is not the 10x engineer but the 10x organisation.