The corporate workplace is gaining a new kind of colleague, and it does not need a desk, a salary or even a physical body.
Image Courtesy : amtecsolutionsgroup.com
AI agents are increasingly capable of handling administrative tasks, communicating with customers, analyzing information, operating software and making decisions with limited human intervention. At the same time, physical robots and collaborative machines are moving into warehouses, factories, stores and other workplaces. As these systems become more deeply embedded in everyday operations, companies are facing a problem that traditional information-technology departments and human-resources teams were never designed to solve: how do humans and machines work together when the machines themselves are becoming active participants in the workflow?
One possible answer is a new corporate function sometimes described as “Robot Relations.”
The phrase may sound futuristic, but the underlying organizational problem is already being discussed seriously. Brookings senior fellow Darrell M. West argued in July that organizations adopting AI agents, robots, collaborative robots and other forms of physical AI may eventually need dedicated “robot relations” functions to manage the interactions between employees and increasingly capable machines. His analysis points to a convergence of responsibilities traditionally divided between HR, IT, operations and management.
The concept does not necessarily mean that corporations will suddenly begin opening departments with signs reading “Robot Relations” outside the door. In many companies, the function is more likely to emerge gradually through new responsibilities added to existing jobs. An AI operations manager, automation specialist, robotics supervisor, HR technology manager or AI governance professional could end up performing pieces of what a future Robot Relations department would handle.
The underlying shift is significant because AI is moving beyond being something employees simply use.
For much of the generative-AI boom, businesses approached artificial intelligence as another software tool. Employees were given access to chatbots and copilots that could summarize documents, write emails, generate code or analyze information. The human remained clearly responsible for the work, while the AI operated primarily as an assistant.
Agentic AI changes that relationship.
An AI agent can be designed to perform a sequence of tasks, interact with business software, communicate with other systems and pursue an objective with less continuous supervision. Instead of asking an AI to draft an email and then manually sending it, for example, an organization could eventually give an agent responsibility for handling an entire workflow involving communication, scheduling, data retrieval and follow-up.
That creates a new management question: Who is responsible for supervising the machine?
The answer cannot always be IT.
IT departments traditionally focus on infrastructure, security, software deployment and technical reliability. They may be able to determine whether an AI system is functioning properly, but that does not necessarily tell them whether the system is interacting appropriately with employees or changing how work is distributed.
HR has the opposite problem.
Human-resources departments are built around people. They handle workplace policies, employee concerns, training, compensation, performance management and organizational culture. But many HR professionals are not equipped to investigate why an AI agent made a particular decision, how an automated system was configured or whether an algorithm is producing unexpected outcomes.
Robot Relations sits in the space between those responsibilities.
A future team performing this function could be responsible for determining how employees interact with AI systems, establishing escalation procedures when automated decisions go wrong, coordinating training and ensuring workers understand what AI systems are permitted to do.
It could also become the place employees go when they believe an AI system is treating them unfairly.
That scenario is already becoming increasingly relevant as companies use algorithms for scheduling, productivity measurement, hiring, performance assessment and other employment-related functions. When a human manager makes a questionable decision, an employee can generally identify who made it and ask for an explanation. When an algorithm produces the decision, determining who is accountable can become considerably more complicated.
The problem becomes even more complicated when the AI system is not simply making recommendations but actually taking actions.
Imagine a workplace where an AI system schedules employees, distributes assignments, monitors workflow and recommends changes to staffing. An employee who believes the system consistently gives them undesirable shifts might have a legitimate workplace complaint, but the organization now has to determine whether the problem originated with the employee's manager, the AI's configuration, the data used by the system or the way the organization instructed the system to optimize its objectives.
That is a management problem as much as a technical one.
Brookings describes this emerging challenge as a need to rethink traditional HR functions because employees may increasingly have concerns involving AI agents, collaborative robots, chatbots and other automated systems rather than exclusively human colleagues. The organization argues that companies will need people who understand both the technology and the human consequences of deploying it.
Physical robotics adds another dimension.
A software agent can make an erroneous recommendation, but a physical robot can potentially create an operational or safety problem. Collaborative robots, warehouse machines and increasingly sophisticated humanoid systems can interact directly with people and their surroundings.
That means companies may eventually need supervisors who understand not only robotics but also workplace behavior and organizational processes.
The traditional factory supervisor was responsible for human workers and machinery. The emerging supervisor may have to manage humans working alongside autonomous machines that can perceive their surroundings, adjust their behavior and perform tasks without continuous human control.
That is a fundamentally different management relationship.
Research into employee-robot relationships is already examining how workers perceive machines as workplace participants. A 2026 study published through Emerald/ScienceDirect identified several types of employee-robot relationships, including collaborative, competitive, supplementary and complementary relationships, based on interviews and experimental research involving service-industry workers.
That research points toward an important reality: people do not necessarily experience robots as ordinary pieces of equipment.
When a machine works alongside a person, responds to the environment and performs tasks autonomously, employees can begin treating the machine as a distinct participant in the workplace. That does not mean workers believe the machine is a person. It means the machine's behavior becomes part of the social and operational environment employees have to navigate.
Companies therefore have to consider more than whether a robot can complete a task.
They have to consider how humans respond to it.
A robot that makes employees faster may be welcomed. A robot that constantly interrupts workers, changes assignments unpredictably or monitors their movements may create frustration even if it technically improves a productivity metric.
The same issue applies to AI software.
An automated assistant that saves employees several hours a week can be viewed as an advantage. An AI system that continuously evaluates their performance may be perceived very differently, particularly if workers do not understand how its conclusions are generated.
This is where transparency becomes a central part of AI workplace management.
Employees need to know what an AI system is doing, what information it is using and what authority it has. They also need to know when a human can override its decisions.
Without those safeguards, organizations risk creating a workplace in which employees are technically managed by systems they cannot question.
The emerging Robot Relations function could therefore involve establishing clear boundaries around machine authority.
An organization might determine that an AI agent can recommend a staffing change but cannot implement it without human approval. A robot might be allowed to reorganize inventory but not alter safety procedures. An automated performance system might identify unusual patterns but be prohibited from making disciplinary decisions without human review.
Those distinctions could become as important as the original technology itself.
The question is not simply whether AI can perform a particular task.
It is whether the company should allow AI to perform that task autonomously.
That distinction becomes especially important as businesses experiment with AI agents capable of performing increasingly complicated work. Organizations are discovering that deploying an agent is not simply a matter of purchasing software. Someone must determine what the agent is allowed to access, what it should accomplish, how its performance will be measured and what happens when it encounters an unfamiliar situation.
A recent analysis from the Swiss Institute of Artificial Intelligence similarly argues that companies adopting AI need to develop organizational capabilities around machine labor management, the economics of AI use and the architecture of AI-dependent workflows. The analysis suggests that simply creating a new job title does not solve the deeper challenge of determining how much work should depend on AI and when humans should intervene. (Gordon Institute)
That could make the future Robot Relations professional considerably different from a conventional HR specialist.
The role may require technical literacy, organizational psychology, operations knowledge, data analysis and an understanding of AI governance.
One day, that person could be investigating why an AI scheduling system repeatedly assigns undesirable shifts to a particular group of employees. The next day, they could be working with engineers to change the system's behavior. Later, they could be training workers on how to interact with a new AI agent.
In a factory, the equivalent professional might oversee how employees interact with autonomous robots and determine when a human supervisor needs to intervene.
In an office, the job could involve coordinating dozens of AI agents that perform administrative tasks across different departments.
In a customer-service organization, the role could involve determining which customer interactions are handled entirely by AI and which must be transferred to a human.
This could also create an entirely new category of workplace conflict.
Historically, employee disputes have generally involved people, policies and organizations. In an AI-intensive workplace, disputes could involve humans, algorithms and automated decision systems.
Who gets credit for work performed jointly by an employee and an AI agent?
How should performance be evaluated when an employee's output depends heavily on an automated system?
What happens when an AI system makes a mistake but the employee is blamed for accepting its recommendation?
Should employees have the right to challenge an AI-generated performance evaluation?
Who is responsible when an autonomous system violates company policy?
These questions do not have universal answers yet.
Different companies will likely establish different rules depending on their industries, technologies and risk tolerance. But the need to answer them is becoming more apparent as AI systems move deeper into organizational decision-making.
There is also an economic dimension.
Companies are adopting AI because they expect it to improve productivity, reduce costs or allow employees to accomplish more. But an AI system can introduce costs that are harder to see on a software invoice.
Employees may need training. Managers may spend time reviewing AI output. Security teams may have to monitor additional systems. Errors may require correction. Workers may need to adapt their processes. Organizations may have to redesign entire workflows.
That means the real cost of AI is not necessarily the price of the software subscription.
It is the cost of changing the organization around the technology.
This may ultimately become one of the most important responsibilities associated with AI management.
A Robot Relations team would not simply keep humans happy around machines. It could help determine whether an AI deployment is actually producing the expected business value.
If an AI agent completes a task in five minutes but requires a human employee to spend 20 minutes checking its work, the apparent automation benefit may be smaller than expected.
Likewise, a robot that increases production but creates enough additional maintenance, training and supervision costs could produce a different economic result than the headline productivity figure suggests.
This is why the future of Robot Relations may ultimately be less about robots and more about organizational design.
The companies that successfully integrate AI may not necessarily be the ones with the most advanced models or the largest number of robots. They may be the companies that figure out how to divide responsibility between humans and machines effectively.
That could produce a new corporate hierarchy in which AI systems are treated almost like a new category of workforce resource.
They would not be employees in the legal sense, and they would not possess human rights or workplace identities. But organizations may increasingly manage them through concepts that resemble workforce management: assignment, supervision, performance measurement, permissions, training, auditing and retirement.
An AI agent could be deployed, monitored, upgraded and eventually replaced much like an organizational resource.
That creates an interesting reversal of the traditional corporate structure.
For decades, technology departments adapted computers to human organizations. In the emerging AI economy, organizations may increasingly adapt themselves to systems that can perform portions of human work.
The result could be a workplace where every team has both human employees and machine workers.
The human employees would have managers.
The machine workers would have owners, supervisors or administrators.
And someone would have to make sure the two groups can operate together.
That is the fundamental idea behind Robot Relations.
It may never become a formal department at most companies. The responsibility could instead be distributed among HR, IT, operations, cybersecurity, legal and AI governance teams.
But the function itself is increasingly difficult to ignore.
The more autonomous AI becomes, the less useful it is to think of deployment as simply installing another software product.
Companies are beginning to confront a more complicated question: How should an organization operate when some of its work is performed by systems that can make decisions, interact with people and act without continuous human supervision?
The answer will likely take years to develop.
What is already becoming clear is that the AI workplace will require more than engineers who can build intelligent systems. It will require people who can manage the relationship between those systems and everyone else.
That could make “Robot Relations” one of the strangest-sounding corporate concepts to emerge from the AI revolution—and potentially one of its most practical.