How the Cost of Doing Reshapes Your Hiring Strategy

McKinsey estimates that AI can already automate around 60% of the tasks in a typical knowledge work role. That is not a projection for 2030. That is now. If you are hiring someone this quarter, the question is no longer "can this person do the work?" It is something more fundamental than that.

The bit I want to focus on

When the cost of doing drops - and it is dropping fast - what remains expensive is knowing what to do. Judgment. Taste. The ability to look at AI's output and know whether it is right, whether it is good enough, and whether it actually serves the goal.

This is the cost of doing thesis applied to your people strategy. When doing becomes cheap, you stop hiring for doing. You hire for the things AI cannot supply: the capacity to decide, to prioritise, to spot what is missing, to understand context that a model has never seen. What that means is your hiring criteria need to shift from "can this person execute?" to "can this person think clearly about what to execute?"

Harvard Business School put it well earlier this year: AI cannot reliably distinguish good ideas from mediocre ones or guide long-term business strategy on its own. The winning combination is AI for speed, humans for judgment. That framing should be written into every job description you publish this year.

How does AI change the cost of doing business?

AI compresses the cost of execution while the cost of good decisions stays the same. That gap is where human value now concentrates. For hiring, this means the premium shifts from people who can do things quickly to people who can determine what is worth doing. Organisations that still hire primarily for task execution will find themselves paying for capability that AI provides for a fraction of the cost.

What this means for your next hire

There are a couple of practical implications here. The first is job descriptions. If more than half of a role's listed tasks could be handled by AI, the description is out of date. Rewrite it around the decisions that role needs to make, the judgment calls it requires, and the outcomes it is accountable for.

The second is interviews. Asking candidates to demonstrate task execution tells you very little about what they will actually contribute. Ask them how they would evaluate AI-generated work. Ask them to describe a situation where the obvious answer was wrong. You are hiring for the ability to think, not the ability to produce.

The third is the pipeline problem. Harvard Business Review flagged this in February: if AI handles the messy, repetitive tasks that used to build judgment in junior staff, how do those people ever develop the expertise you need them to have in five years? That is not a hiring question - it is a workforce design question. And it needs answering now, not when your leadership pipeline thins out.

The opportunity here is real

The cost of doing is falling. That is not a threat to your hiring strategy - it is an invitation to rethink what you are actually paying for. The organisations that get this right will have smaller teams doing more meaningful work, with AI handling the volume and humans handling the direction. I made a short video unpacking how the cost of doing reshapes business economics if you want the fuller picture. And if you are a managing director navigating this shift, the practical question is the same: what decisions does your team need to make, and are you hiring people who can make them?

That is the hiring strategy that fits the moment we are in.