Managing a workforce that isn't human: When AI becomes digital labor

The definition of labor, as it relates to the workplace, has traditionally referred to humans performing tasks. But as companies increasingly use artificial intelligence to create business value successfully, this description is now only partly true.

While automation traditionally performed only tasks predefined by a human, AI now routinely plans, makes decisions and interacts with multiple systems and processes. Organizations must now actively decide which workflows are best served by AI agents and which need human judgement. As a result, AI can now function as a team member alongside human employees in certain roles.

In just a few short years, AI has fundamentally changed the relationships between humans and technology. The RSM Middle Market AI Survey 2026 found that 91% of respondents agreed that humans and AI systems will work together as integrated teams over the next two to three years. As a result, many important AI decisions are no longer only IT decisions; they are now workforce design decisions about where human judgment adds value and where it does not.

AI provides an opportunity once thought impossible: to grow a company without increasing human capital. Employees can now create a digital extension of themselves that can work, research and accelerate their expertise. As a result, organizations can use a digital labor model to scale in ways once out of reach. However, organizations see these results only when data quality, governance, identity management, permissions, change management, process redesign and workforce trust are in place.

The evolution from tool to assistant to digital labor

As organizations become more willing to invest in digital labor, a key question emerges. Should AI be treated as a tool, an assistant that augments employees or a standalone digital employee?

Most organizations currently view AI primarily as a tool that performs isolated tasks when asked, similar to customer relationship management or enterprise resource planning systems. While this approach provides productivity benefits, it’s challenging, if not impossible, to use AI only as a tool and achieve large-scale business growth. Businesses of all sizes across industries that have attempted this feat have struggled greatly, leading many to realize they need a new approach to gain true business value from AI at scale.

Businesses are beginning to adopt a model in which AI functions as an assistant that may perform some autonomous tasks at the direction of a human worker, with the worker integrating AI into their processes throughout the day instead of using it for an occasional task. In this model, AI agents work under a human supervisor, collaborating with the employee and revamping work processes. Employees and leaders also become comfortable with outsourcing AI for autonomous tasks on a limited scale while improving their skills.

AI provides an opportunity once thought impossible: to grow a company without increasing human capital. 

Businesses that take AI to the next level by viewing AI as a digital employee gain the biggest benefits and set the stage for wide-scale use. The distinction between an assistant and a digital employee is about the level of work, autonomy, management and accountability the organization assigns to digital labor. The digital employee transition begins when AI owns parts of the job itself, such as agentic workflows and orchestration and is evaluated on outcomes and quality instead of productivity alone. AI may also recommend, prioritize and assign work, but managers remain responsible for people leadership, performance management and business decisions.

Digital labor is a new category of worker

While organizational leaders are typically comfortable outsourcing roles, tasks and even departments to agencies or other companies, outsourcing tasks to digital employees instead of human resources often feels uncomfortable at first.

However, digital labor provides many benefits over outsourcing to human-staffed agencies. Traditional outsourcing means paying to access someone else's workforce, while digital employees give businesses greater access to their own workforce, just without the headcount or additional expense. Digital labor creates opportunities to capture organizational knowledge, distribute it across agents and preserve expertise inside the company rather than letting it leave with individuals or sharing it through outsourcing.

With key foundations such as governance and change management in place, AI agents are increasingly embedded in daily workflows, working alongside employees and creating continuity that is not possible with traditional outsourcing models. For example, the accounts payable team might use an AI agent to extract invoice data, match invoices to purchase orders and route exceptions to the appropriate employee. In this scenario, the AI agent saves significant time by automating repetitive administrative work; it functions as an assistant because it is performing tasks that remain under human oversight. On the other hand, the accounts payable team can use an AI agent to manage the invoice processing workflow end to end, such as validating purchase orders and resolving routine discrepancies.  Instead of performing tasks assigned by humans, the AI agent owns a significant part of the workflow and makes autonomous decisions, elevating its role to digital labor.

When companies began outsourcing tasks and projects to an external workforce, they created new processes and roles to manage this type of labor effectively. As companies move toward digital labor, their processes must change to incorporate AI into the organization’s operational model, including onboarding agents and laying off underperforming agents.. The processes created to manage digital labor also help businesses estimate AI’s value accurately and make smart decisions regarding tokenization.

Human judgment becomes more valuable

With AI as an assistant or digital employee, workers need to understand that their human insights are just as valuable, if not more, than the insights AI brings. While AI brings significant subject matter expertise from vast amounts of data, humans provide a critical check and balance.

By reviewing AI output, human employees make sure the AI work actually makes sense in the context of the task or workflow. For example, an AI agent reviews large volumes of customer data and recommends which customers to prioritize. The agent may recommend discounting the relationship with a low-margin customer based on current financial reports. However, the human employee involved may override this recommendation because the customer provides access to a new market and may generate new opportunities in the future.

Organizations should also evaluate work processes to determine where human capabilities excel and which tasks can be performed by digital labor. Because the answer varies by person and by digital labor, businesses must evaluate each workflow and human individually. By creating workflows that allow each type of labor, human and digital, to work with their strengths, organizations can improve quality, productivity and human employee satisfaction.

When AI joins the organization chart

Many organizations already use a form of AI as digital labor. However, most have not created the necessary governance, process and cultural shifts required to manage the new workforce effectively. Organizations that view AI primarily as a technology tool may see some productivity gains, but only those that build the foundations and then redesign their workforce for digital labor can fundamentally change how work gets done.

Without these adjustments, companies risk not only missing out on the benefits of AI at scale, but also slowing business growth by managing the change ineffectively. As AI evolves in organizations from a tool to an assistant to a digital employee, leaders must proactively make the shift from managing technology to workforce design and development.