Treating AI agent output as its own category of work, budgeted, measured, and planned for the way a company would plan for contractors or full-time staff.
Also known as Digital workforce, digital employees
Digital labor is the practice of counting AI agents as a distinct category of capacity, not just software, when a business plans headcount and budget. Instead of treating an AI subscription as a line item next to office software, digital labor frameworks ask questions usually reserved for people: how many tasks did this agent complete, what is the cost per unit of output, and how does that compare to what a person would cost to do the same work.
This is a framing more than a technology. Enterprise vendors have pushed the term specifically because it changes the conversation from “which AI tool should we buy” to “how much of our capacity should be digital versus human,” a budgeting and staffing decision rather than a procurement one.
Agency pricing models are built on hours. Digital labor forces a hard question: if an AI agent does in ten minutes what took an associate two hours, what is the agency actually charging for, the time, the output, or the judgment applied to it.
It reshapes staffing plans. Agencies weighing whether to backfill a departing coordinator or route more of that work through AI agents are making a digital labor decision, whether or not they use the term.
Clients are starting to ask the question directly. Some clients now ask agencies what portion of a deliverable was produced by AI versus a person, which means agencies need their own honest answer to the digital labor question before a client asks it in a review.
An agency’s operations director is building next year’s staffing plan and realizes she can no longer plan headcount without also planning digital labor. Data cleanup and first-pass reporting that used to require a full-time analyst now runs through an AI agent that handles the bulk of it, with a person reviewing exceptions. Rather than framing this as cutting a role, she reframes the department’s capacity plan around a mix, two analysts plus a defined amount of digital labor capacity, budgeted and reviewed quarterly the same way she would review a contractor’s scope, which makes the tradeoff visible to leadership instead of something that just happens quietly through attrition.
The automations and agents module of the workshop teaches you how to build AI workflows that compress the busywork without taking the craft out of the studio.