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Home » How To Divide Work Between Humans And AI Agents
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How To Divide Work Between Humans And AI Agents

Press RoomBy Press Room1 October 20266 Mins Read
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How To Divide Work Between Humans And AI Agents

Manu Khetan is Founder and CEO of Rolling Arrays, a LinkedIn ‘Top Voice’ Influencer and Creator of the R7 Framework.

How do I divide work between humans and agents? Every leader I meet is asking some version of that question. Usually it arrives dressed up as a technology question, which is why it goes wrong.

In Part 1 of this series, I wrote about the blind spot: On a spreadsheet, value and overhead are the same number. This piece is about the fix. How you actually draw the line between what agents can take and what stays human. I have spent 17 years implementing HR technology. My own 400-person, six-country firm is adopting AI right now.​

The Unit Is The Task, Not The Job

The first mistake is treating the job as the unit. A job is a bundle of tasks, and the tasks inside one job vary wildly. Some are routine. Some carry judgment. One or two carry the trust the whole role exists for.

So you cut roles by task, not people by salary. That single sentence is most of the method.

We did this to ourselves first. Our delivery organization has 18 roles, and we read them task by task instead of by headcount. Two people carrying the same title turned out to be doing quite different work. The title told us very little. The task mix told us most of what we needed.

Two Questions Per Task

In the R7 Framework, we read every task on two axes.

The first question is about the nature of the work. Is this task physical, cognitive or relational? Doing work, thinking work or work that runs through a relationship.

The second question is about ownership. Is this task execution, judgment or trust? Execution is the routine doing, gathering, drafting, reconciling, monitoring. Judgment is deciding what is worth doing when the playbook does not fit. Trust is owning the outcome and holding the relationship, putting your name on it.

Two axes, nine cells and every task sits in one of them. One clarification because it trips people up. Relational is how the work happens; trust is who answers for it. A templated check-in call is relational but carries no trust.

The allocation rule falls out almost by itself. Soft agents, meaning AI, take cognitive execution. Hard agents, meaning robots, take physical execution. Humans keep judgment and trust, and the relational core resists both. Relational execution never moves; agents reach only its edges. Trust stays because accountability cannot be delegated to a machine. Someone signs and carries the liability. Institution and law, not capability. Seven of nine cells stay human.

That is why we don’t start with the agents. We redesign the work and the roles first, then partner for the agent build itself. The build is what gets bought. The redesign is the part that gets skipped.

The Gate

Here is where the discipline comes in and where most programs skip a step.

An execution cell makes a task a candidate, nothing more. Every candidate has to clear a gate with two disqualifiers.

The first disqualifier is what we call a Parity Task, where the agent’s output is no better than the human’s at the point of value. Parity is about value, not capability, and automating one buys you nothing except fragility. The Klarna story from Part 1 is exactly this. The routine queries were not parity tasks, and that half worked. The emotional, multistep moments were, and the customers said so.

The second disqualifier is what we call a Below-the-Line Task. The agent is better, but the value gained is trivial against what the agent costs. My favorite example, an illustrative one: AI polishing the delivery note a customer writes for the parcel handler. The AI genuinely improves the text and saves the handler five to 10 seconds. The value never clears the cost of the call. Leave it alone.

One Role, Walked Through

Run it on one of our roles: the support-desk consultant who keeps client HR systems running after go-live. Every company has a version. Here is where the line fell.

Drafting the reply to a routine leave-balance ticket. Cognitive execution, and the agent is faster, more consistent and available at 3 am. Clears both gates. It goes to the agent, with a human on the loop.

The HR director whose payroll run has gone wrong twice and is angry. Relational. The point of value is a person who owns the situation. An agent answering this one is a Parity Task at best. It stays human. The agent’s job is to hand our consultant the full history before the call.

The decision to make an exception to our service policy. Judgment, edging into trust. The agent can prepare the case. A human decides and answers for it. Stays human.

Tidying the grammar inside the client’s ticket text. Below the line. Nobody touches it.

Four tasks, one role and the line is visible. The role does not disappear. It gets redesigned around the judgment, the trust and the relational moments, while the gated routine goes to agents. Cut the work, not the people.

Design, Not Debate​

Where to start is its own question. The honest answer is where the value concentrates, not where the automation is easiest. For us, that was delivery, the work clients pay us for, not the back office, which is the easier place to start.

One thing surprised me. We still hire fresh graduates into delivery. What changed is the job we hire them into. The routine output juniors used to produce is what clears the gate, so what is left is checking, correcting and escalating what an agent produced. That is a harder first job than the one I started with.

The bigger question, why so many companies bought agents and got nothing back, will be Part 3.

For now, a small exercise: Pick one role you know well—yours will do—and ask the two questions of its four or five biggest tasks. Most people are surprised by how much stays human and how clearly they see what should not.​

Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?

Manu Khetan
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