Since the arrival of AI in the contact center, the industry has talked about technology as if it would eventually solve the hardest parts of customer experience. Self-service, automation, digital channels, and AI have all been positioned as ways to create faster service, lower costs, and more efficient operations.
Inside CX operations, the frontline agent remains one of the most important positions because they are closest to the customer experience. They are the people hearing the frustration first, dealing with broken workflows in real time, and often trying to recover the experience after multiple systems or channels have already failed the customer.
There is an obvious answer the market keeps circling around: headcount decrease. Some of that is happening, and it will likely continue in certain environments. But the bigger operational reality is not as simple as replacing agents with technology.
The theory right now is that AI will pick up the easier tasks, the easier call types, and the interactions that can become more self-service or automated. There is also a lot of talk about the agents who remain needing to be higher-level agents who can handle the more complex or more important work. That may become true in some environments, but we are still early. There is not enough mature operational data across the market to act like every organization already knows what this model will look like long term.
What we are seeing right now is that agents are getting stuck using a lot of new technology, and the companies they work for are not always deploying it well. Tools that were supposed to deflect volume from the voice channel can end up creating more calls, more customer frustration, and more pressure on the frontline. In those situations, the experience becomes the opposite of better.
The Agent Role Is Changing Because the Work Is Changing
Frontline agents are not just handling the same work in a different system. The work itself is changing. If simpler interactions move into self-service, digital support, chatbots, or automated workflows, the interactions that reach a human often carry more friction.
Customers may already have tried to resolve the issue before they reach the agent. They may have searched the website, used a bot, started in chat, or moved through another channel that did not solve the problem. By the time the interaction reaches the frontline, the customer may already be frustrated, confused, or tired of repeating themselves.
That matters because the agent is no longer just responding to the original issue. They are responding to the issue plus the experience the customer had before reaching them. If the customer has to start over when moving from one channel to another, that is not a seamless experience. It is still what most consumers deal with every day, and the agent is often the one left trying to make the experience feel connected.
This is where many organizations are still behind. They may have added channels, tools, or automation, but they have not fully redesigned the agent role around the work that now reaches the frontline. The agent is still measured and managed like the old environment, even though the interactions are often more complex.
Technology Can Support Agents, But It Can Also Create More Work
One of the more interesting realities right now is that AI is not only replacing or deflecting work. In some cases, it is supporting the agent directly. Copilots, agent assist tools, speech analytics, and guided workflows can make more difficult interactions easier for the frontline to manage when they are connected to the right data, knowledge, and workflow.
That is why the blanket assumption that frontline agents will automatically need to carry more pressure because of AI is not always accurate. AI is also supporting the agent. A well-designed tool can help surface information, guide the next step, reduce searching, and give the agent more confidence during a complicated interaction.
The problem is that many organizations are still deploying tools without fixing the operational environment around them. If the knowledge base is weak, the workflow is unclear, the systems do not talk to each other, or the escalation path is poorly designed, technology will not remove that complexity. It may simply shift the complexity back to the agent.
This is why leaders have to ask a more disciplined question before adding more technology. If it is not returning on the P&L and it is not improving customer service, why are we doing it? The point is not to avoid technology. The point is to make sure the technology is actually making the operation better.
Coaching and Performance Management Are Still the Gap
When organizations talk about AI-assisted environments, the conversation often moves quickly to the tools. But the bigger issue in many operations is still coaching. The biggest problem is often that the coaching is not happening at the level it should.
Contact centers are recording more interactions than ever. Years ago, even a solid quality assurance program may have only reviewed a small sample of calls 1-2%. Now organizations can record and analyze far more of the customer experience. The problem is not always lack of data. The problem is that no one is using the data in a meaningful way.
That becomes a major issue as the agent role changes. If frontline employees are handling more complex customer situations, interpreting AI-supported information, managing escalations, and navigating incomplete workflows, then coaching cannot stay limited to basic call correction or script adherence.
Agents need coaching that helps them understand decision-making, judgment, escalation handling, and how to use the information available to them. They need leaders who can look at the interaction, the workflow, the data, and the customer experience together. Without that, organizations may have more technology and more recordings, but still no real performance management environment.
Redefining the Role Is a Workforce Issue
When new tools are introduced without redefining the frontline role, it creates workforce risk. Poor deployment not only affects the customer experience. It affects the people expected to use the tools every day.
One of the biggest risks is turnover, and turnover has a real dollar figure attached to it. The cost is not only the job posting, screening, interviewing, onboarding, and training. It is also the knowledge that leaves with the person. In more specialized environments, that knowledge can include customer patterns, internal process awareness, escalation experience, and the practical understanding of how the work really gets done.
This is why leadership, communication, education, and involvement matter. If agents are expected to work differently, they need to understand the why behind the change. They also need support that matches the new expectations being placed on them.
Good change management is not just a project plan. It is how the organization protects the customer experience and the workforce at the same time. When agents are involved, trained, coached, and supported through change, adoption has a stronger chance of becoming operationally useful instead of another layer of frustration.
The Operation Has to Catch Up to the Agent Role
The agent role did not shrink. It changed faster than the operation. That is the real issue many customer experience centers are dealing with right now.
The role has moved from simple execution toward more judgment. It has moved from script adherence toward decision-making. It has moved from handling contacts toward managing outcomes. Agents are often correcting errors, interpreting information, navigating incomplete workflows, and managing escalations that technology did not resolve.
The operation has to be rebuilt around that reality. Role clarity has to be redefined. Coaching models have to reflect hybrid workflows. QA has to account for interactions influenced by automation, agent assist, self-service, and AI-supported tools. Performance metrics have to align to the work agents are actually doing, not only the work the operation used to measure.
This is also where AI maturity connects back to the frontline role. AI exposes gaps in workflow design, knowledge management, performance systems, and leadership accountability. Without operational alignment, AI does not automatically create consistency. It can amplify inconsistency and leave the agent carrying the burden.
The future of the contact center is not simply about how much work technology can take over. It is also about how well organizations rebuild the human role around the work that remains. Frontline agents will continue to shape customer experience in the moments where the customer is confused, frustrated, escalated, or unable to resolve the issue alone.
Organizations that understand this will be better positioned for what comes next. The agent role is becoming more complex and more critical. If the operation does not redefine the role, support the workforce, and align performance systems around the new reality of the work, the result will be stalled performance, workforce strain, and limited return from technology investments.
If your operation is navigating these shifts, the work does not have to stay stuck. CH Consulting Group works with CX and healthcare leaders to strengthen contact center operations, rebuild workforce performance systems, and align the work around what the frontline is actually doing today. Learn more about how we support contact center operations.
