The Global Hiring Floor

I run an executive search firm and a hiring operations company. Which means I spend most of my professional life thinking about what makes human talent valuable, where to find it, and what it should cost.

The last two years have been the most disorienting of my career in that respect — not because the fundamentals of what I do have changed, but because the context in which they operate is changing faster than I can track.

The arrival of capable AI tools in the knowledge economy has done something that is rarely described precisely: it has raised the floor. Not the ceiling — the floor. The baseline of what a moderately capable person can produce with access to AI tools has increased dramatically. The research that used to take three days can be completed in three hours. The analysis that used to require a specialist now has a competent first draft available to a generalist. The code that used to require a senior developer can be scaffolded by a junior with the right tools.

That floor change has consequences for every talent market in the world. Some of them are already visible. Most of them are still arriving.

What the floor change actually means

A floor change is not the same as a ceiling change. The output of the best researchers, analysts, writers, and engineers has not been replaced by AI. In many cases, the best people with AI tools are more productive than the best people without them — the ceiling has moved up.

But the floor change is what disrupts markets. When the baseline output of a competent person with AI assistance approaches what a specialized person without AI used to produce, the economic case for the specialized person at their prior price weakens. This is not a hypothetical. It is already visible in routine legal work, basic financial analysis, entry-level copywriting, and standard software development tasks.

The disruption moves up the value chain over time. Tasks that seemed safely specialized two years ago are floor tasks today. What is ceiling work today may be floor work in three years.

For talent markets, this is reshuffling who competes with whom. A well-tooled generalist now competes with a specialist for tasks that the specialist previously owned. A team of ten people with AI tools now competes with a team of twenty people without them. The numerics of headcount and cost that companies built their hiring strategies around are changing.

The global dimension

The floor change is happening everywhere simultaneously, and that simultaneity is economically significant.

For the past two decades, a significant amount of global talent arbitrage was based on the following logic: highly capable people in lower-cost geographies could be hired for routine-to-moderately-complex knowledge work at a fraction of the cost of equivalent people in high-cost markets. India's IT services industry, the global business process outsourcing sector, and significant parts of the fintech and media industries were built on this logic.

AI disrupts that logic at the lower end. If routine knowledge work can be done by AI at lower cost than any human — regardless of geography — then the cost arbitrage for routine work collapses. The question is not whether to hire in India or the US for routine tasks. The question is whether to hire a human for routine tasks at all.

This is genuinely disruptive for the parts of India's service economy that are built on routine work arbitrage. And it is an opportunity — not equally distributed — for the parts of India's talent pool that have moved beyond routine work into genuine capability.

I have built businesses that place senior talent globally. I have seen, over years of doing this work, that the supply of genuinely excellent people in India's talent pool is large and substantially underutilized relative to what the global market would pay for their capabilities. The global hiring floor change creates conditions where that talent can access opportunities more efficiently than the old model allowed — not because the arbitrage logic changed, but because the tools now allow a talented person in Bhubaneswar to produce and deliver work that competes directly with a talented person in Boston, without the friction of physical relocation.

What remains unmistakably human

There is a version of the AI-and-work conversation that ends in pure displacement: AI takes the floor, then the middle, then eventually the ceiling, and humans are left looking for meaning outside the economy.

I don't believe that version. Not because I'm optimistic by disposition — I'm actually fairly hard-nosed about this — but because I can see clearly what AI cannot replicate at the level that determines executive-level outcomes.

What remains unmistakably human is judgment in specific, high-stakes contexts where the cost of error is large and the situation does not match known patterns. When I'm helping a CEO assess a VP candidate, I'm not doing pattern matching against resumes. I'm reading a person — their confidence, their self-awareness, their ability to think under pressure, their cultural fit with a specific team at a specific stage. That read involves forty years of accumulated context about how humans work, what people look like when they're genuinely capable versus performing capability, and what the specific company will need from this person in twelve months.

AI tools are genuinely useful to me in parts of that work. They are not the work.

The same applies to client relationships. The reason a CEO trusts me with a VP search for their most critical revenue-generating role is not that I have a good database. It's that they've talked to me, that I've understood something true about their situation, and that I've been honest when it was uncomfortable to be honest. That trust is a human thing. It is not systemizable or AI-augmentable in the way that research is.

The implication for how we think about talent

What the global hiring floor change actually requires is a more precise understanding of what we're buying when we hire.

If we're buying routine output — research, first drafts, standard analysis — AI is a better, cheaper option and the talent question is who operates the tools.

If we're buying judgment, relationships, accountability, and the ability to navigate novel situations — we're buying something that remains genuinely human, and the market for it may actually be strengthening as the AI floor rises and the value of what remains above the floor becomes more visible by contrast.

The hiring mistake of the next decade will be applying the wrong logic to the wrong category: either over-investing in humans for routine work that AI handles better, or under-investing in human judgment under the assumption that AI will eventually cover that too.

It won't cover it, not for the things that matter most. The global hiring floor is rising. What is left standing above it is what companies actually need to compete.

Manas Majhi is the founder of Majhi Group, a retained executive search firm, and Majhi OS, a hiring operations platform. He writes about talent, AI, and the future of work.