Automation is usually evaluated by what an organization gains: lower costs, faster processing, fewer errors, and greater scalability. But Julio Avael III points to a less visible question that becomes increasingly important as artificial labor takes over routine responsibilities: what does an organization lose when people stop doing the work altogether?
The answer is not necessarily jobs alone.
Organizations can also lose institutional knowledge, practical judgment, developmental opportunities, and a workforce’s understanding of how operations actually function. Those losses may not appear on an automation project’s initial business case, yet they can become increasingly important over time.
The most sophisticated automation strategy, therefore, is not simply about identifying work that machines can perform.
It is about understanding which human capabilities are developed through that work, and what happens when those opportunities disappear.
Work Has Always Been a Form of Organizational Education
Many tasks that appear repetitive serve a second purpose: they teach people how an organization operates.
An employee who begins by handling routine administrative processes may gradually learn:
- How customers move through the organization
- Where operational bottlenecks occur
- Which exceptions require judgment
- How different departments depend on one another
- Why certain policies exist
- What problems repeatedly frustrate customers or employees
The task itself may eventually become automated. The knowledge gained from performing it may be much harder to replace. This creates an important distinction between task value and learning value.
A task can be inefficient as a use of human time while still being valuable as a source of organizational knowledge.
The Entry-Level Work Problem
One of the clearest examples appears at the beginning of a career.
Organizations have traditionally relied on entry-level responsibilities as a training ground. New employees perform relatively straightforward work while developing familiarity with systems, customers, processes, and organizational expectations.
Automation can remove many of those tasks. That may be beneficial in the short term.
But it raises a longer-term question:
How does someone develop operational judgment if the organization removes the experiences through which that judgment was traditionally learned?
An employee cannot simply be given a senior-level decision-making role without understanding the environment in which those decisions occur.
If foundational work disappears, organizations may eventually discover that they have fewer opportunities to develop people who understand the business from the ground up.
Efficiency Can Remove More Than Repetition
The business case for automation often focuses on repetitive work.
A process may involve hundreds or thousands of similar transactions, making it an obvious candidate for technological intervention. But “repetitive” does not necessarily mean meaningless.
Repetition creates pattern recognition.
Employees who repeatedly encounter the same type of issue may begin to notice anomalies that are difficult to capture in formal procedures. Over time, they may develop an instinct for identifying when something does not look right.
That judgment can be difficult to encode into a system because it may involve context rather than a single measurable rule.
Automation can eliminate the repetitive task while also eliminating the human exposure that helped employees develop that intuition.
Institutional Knowledge Is Often Hidden in Routine Work
Institutional knowledge rarely exists entirely in manuals.
Some of it lives in the experience of people who have worked through unusual situations.
An experienced employee may know:
- Which problems tend to appear during specific periods
- Which requests require additional verification
- Which processes frequently create downstream complications
- Which seemingly minor errors can become expensive later
- Which departments need to be involved before a problem escalates
Much of this knowledge develops organically. It is accumulated through exposure.
When a process becomes automated, the organization needs to consider whether that knowledge is being captured before the human experience disappears.
Otherwise, automation can create a paradox:
The organization becomes better at performing the process while becoming less knowledgeable about the process.
Healthcare Makes This Tradeoff Especially Important
Healthcare operations provide a useful example because many administrative functions are highly repetitive and therefore attractive candidates for automation.
Scheduling, eligibility verification, claims workflows, documentation support, and other administrative activities can consume significant amounts of staff time.
Automation can reduce that burden. But the people performing those functions may also develop an understanding of how patients, providers, payers, and internal departments interact.
That operational understanding has value. If the technology handles every routine interaction, newer employees may never experience the underlying process directly.
This does not mean healthcare organizations should avoid automation.
It means they should think carefully about how operational knowledge will be developed and preserved after automation.
The Supervisor-of-the-System Problem
Automation can also change what it means to be an employee.
Instead of performing a task directly, employees may increasingly monitor a system that performs the task. That can be an improvement. But it can also create distance between the employee and the underlying operation.
Someone supervising an automated workflow may see alerts, dashboards, and exception reports without experiencing the full range of situations that originally shaped the process.
Over time, that distance can affect judgment. The employee understands what the system reports. The employee may understand less about what happens outside the system.
This distinction matters whenever the organization encounters circumstances that fall outside normal operating conditions.
Automation Can Change How Future Leaders Are Developed
Leadership development is another potential hidden consequence.
Strong leaders often develop their judgment by moving through different layers of an organization.
- They learn how customers experience a service.
- They see how frontline employees deal with operational constraints.
- They understand how systems interact.
- They encounter problems that cannot be solved through a standard procedure.
Eventually, those experiences inform strategic decisions.
If automation removes too many of the experiences at the bottom of that progression, organizations may have to rethink how future leaders acquire practical understanding. The leadership pipeline does not necessarily disappear. But it may need to be redesigned.
The Solution Is Not to Preserve Every Human Task
Recognizing these risks does not mean keeping people in inefficient roles simply because those roles provide learning opportunities.
That would defeat the purpose of responsible automation.
Instead, organizations can deliberately separate work that should be automated from experiences that should still be taught.
For example, a company might automate transaction processing while ensuring that developing employees still gain exposure to:
- Customer interactions
- Exception handling
- Process mapping
- Quality control
- Cross-functional operations
- Problem diagnosis
- System auditing
The work can become more efficient without making the learning environment thinner.
Designing Apprenticeship Into an Automated Organization
As routine work disappears, organizations may need to become more intentional about how employees learn.
Rather than assuming that people will naturally develop operational knowledge through their jobs, companies can create structured opportunities.
That might involve:
- Rotational assignments that expose employees to different functions.
- Exception analysis where employees study cases the automated system cannot resolve.
- Process reviews that teach how workflows operate from beginning to end.
- System audits that help employees understand how automated decisions are produced.
- Cross-functional projects that connect technology, operations, and customer experience.
These activities can preserve the developmental benefits that routine work once provided.
The Knowledge Transfer Question
Before automating a process, leadership should ask more than whether technology can perform it.
A stronger set of questions includes:
- What do employees currently learn by performing this work?
- Which parts of that knowledge are documented?
- Which parts exist only through experience?
- Will employees still have opportunities to develop the same judgment after automation?
- How will future leaders learn the operational realities of the organization?
These questions do not necessarily change the automation decision.
They improve the quality of the decision.
The Difference Between Removing Work and Removing Capability
This distinction may ultimately become one of the most important issues in the transition toward artificial labor. Removing unnecessary work can make an organization stronger. Removing the capabilities associated with understanding that work can make it weaker.
The challenge is determining where that line exists. An organization might automate a process and retain its institutional knowledge. Another might automate the same process without preserving the experience, documentation, or training required to understand it.
The technology could be identical. The organizational outcome could be very different.
A More Complete Definition of Efficiency
Efficiency is often measured through time saved, labor reduced, cost lowered, or output increased.
Those metrics matter. But organizations also need to consider whether they are maintaining the capabilities required to operate effectively in the future. A process that costs less today may create a knowledge gap tomorrow.
A workforce that performs fewer routine tasks may become more strategically valuable, but only if employees are given alternative ways to develop judgment and expertise.
Automation should therefore be evaluated across two horizons:
- Immediate efficiency: What resources does the organization save?
- Long-term capability: What knowledge, judgment, and organizational resilience does it preserve or develop?
The strongest automation strategies consider both.
What Organizations Should Preserve
The goal should not be to preserve human involvement for its own sake.
It should be to preserve the human capabilities that remain valuable after the work changes.
That means identifying which responsibilities require judgment, which experiences build expertise, and which forms of institutional knowledge cannot easily be reconstructed once lost.
Organizations can then automate aggressively where appropriate while deliberately protecting the capabilities that technology does not automatically create.
The future of work will not be determined solely by how much human labor organizations can eliminate. It will also be determined by whether organizations understand what human experience was contributing beyond the task itself.
When artificial labor takes over routine work, the visible benefit is efficiency. The less visible challenge is capability. And organizations that recognize that distinction early will be better positioned to automate without accidentally hollowing out the knowledge and judgment they need to remain effective.