Imagine you’ve built an AI agent to help managers get answers to HR questions.
The demonstration looks promising. A manager asks about a policy. The agent finds the relevant information and drafts a response in seconds.
Then you think about the questions managers actually bring to HR.
Some are straightforward. Others begin with a policy question and turn into a conversation about someone’s health, a difficult relationship or a decision that could affect their career. Answering well means understanding the situation, knowing when to ask another question and recognizing when someone needs a conversation.
Before that agent becomes part of everyday work, someone has to decide where it can help, what context it needs and when a person should step in.
That is where AI Work Design begins.
It’s understandable that leaders start with the technology. A working demonstration makes the opportunity tangible. You can see something happening faster and imagine what that could mean across the business.
But follow that HR question a little further.
How did the manager know where to ask? Who keeps the policy current? What happens when two documents contradict each other? Who takes responsibility if the answer doesn’t fit the employee’s circumstances?
The agent sits within a larger flow of work. Improving one task means understanding what happens before it and what needs to happen next.
AI Work Design brings those decisions together: what work needs to be done, where human expertise matters, where an agent can contribute and how people and technology will work together.
It also creates room for a more useful question: if we were designing this work today, knowing what is now possible, how would we do it?
Perhaps the manager needs a faster answer. Perhaps the policy itself needs to be clearer. Perhaps the repeated question points to a problem worth fixing at its source.
The AI Work Design Blueprint explores this starting point: understanding the work before deciding what technology to deploy.
The people doing the work know where to look
A job description might tell you that someone “supports managers.” It won’t tell you which questions take five minutes, which require three conversations or which keep coming back because the underlying issue never gets resolved.
Those distinctions matter when deciding what to delegate to an agent.
The people doing the work can help make them visible. They know where information is hard to find, where handoffs break down and where experience changes the answer. They can explain why an apparently simple task sometimes requires careful judgment.
In our HR example, that knowledge could help distinguish a routine policy lookup from a sensitive employee matter. It could also reveal what the HR team needs when a question is passed to them, so the manager doesn’t have to start again.
Involving people in these decisions gives them a practical role in shaping how their work changes. It also brings the detail of everyday working life into the design.
Once the work is understood, the choices become more concrete.
An agent might retrieve the relevant policy and prepare a draft. A person might review the response before it reaches the manager. Certain questions might go directly to an HR colleague because they require a conversation or a decision the agent is not authorized to make.
Each arrangement creates different responsibilities. Someone needs to define them, test them and revisit them as the work changes.
This is why Work Architecture matters. It makes work visible at the task level, with enough detail to discuss ownership, dependencies and where an agent could contribute.
Reejig’s Work Operating System supports that foundation by mapping work at the task level. It gives leaders a shared view from which to make decisions about how work should change across people and agents.
Teams can then use that understanding to establish access, oversight and ways to handle exceptions. The AI Work Design Blueprint provides a starting point for bringing those conversations together across HR, IT and the business.
Now imagine the agent is helping with routine questions. What should that change for the HR team and the managers they support?
Perhaps the aim is to give HR colleagues more time for complex employee situations. Perhaps managers should spend less time searching for information and receive more useful support when they need to make a difficult decision.
Those are outcomes to design for and assess. They require choices about priorities, expectations and support.
If people spend less time retrieving policies, what should they focus on instead? Do they have the skills and permission to make that shift? Is the new process helping managers, or moving more checking and correction onto someone else?
These questions give teams a way to judge whether the change is making work better. They also keep attention on the people whose working day is supposed to improve.
For an HR Business Partner team, turning these decisions into a working process takes detail. Someone needs to connect the steps, define what an agent does, establish where a person reviews or decides, and explain how the team will use it.
A practical starting point can make that work easier. Teams can examine a defined workflow, understand the responsibilities within it and work through what needs to fit their own organization.
That’s the next step we’ll be sharing: a pre-release of Certified AI Workflows for the HR Business Partner role group, for teams to use as they put AI Work Design into practice.
The workflows will show how specific parts of the work can be supported by agents, alongside the steps people own. They won’t automate the entire workflow or replace the breadth of an HR Business Partner’s role.
The opportunity is to give teams something concrete to work with: a way to move from “we could use AI here” to understanding how it fits, what people remain responsible for and what needs to happen before the workflow becomes part of daily work.
Start with the AI Work Design Blueprint, and look out for the Certified AI Workflows pre-release to take the next step with your team.
What is AI Work Design?
AI Work Design means understanding and redesigning work across people and AI. It involves deciding what needs to be done, where human expertise matters and how tasks, decisions and responsibilities should fit together.
How does Work Architecture help with AI agents?
Work Architecture makes work visible at the task level, helping teams identify where an agent could contribute and what surrounds that task. That understanding informs decisions about ownership, handoffs and oversight.
Where should leaders begin?
Start with the AI Work Design Blueprint to understand how to approach redesigning work across people and AI.