As AI takes on more customer service tasks, CX leaders face a bigger challenge than automation: rethinking the roles, skills, and career paths that will define the future workforce.
For years, the conversation around artificial intelligence (AI) in customer service has centered on what technology might eventually replace. But as AI becomes more capable of handling customer interactions, executing tasks, and making recommendations, a more important question is emerging for customer experience (CX) leaders:
What should people be doing when AI is doing more of the work?
It’s a question that reaches far beyond automation. It touches workforce planning, job design, employee development, compensation, organizational structure, and the future of customer service as a career.
And the urgency is growing. According to Gartner research, 85% of customer service and support leaders say they are expanding human agent responsibilities as AI reduces contact volume and shifts work toward higher-value tasks. At the same time, 80% report being under pressure to make workforce changes because of AI.
The workforce isn’t necessarily disappearing. It’s changing shape. And organizations that recognize this early have an opportunity to rethink what their people contribute and how they prepare them for what’s next.
The Shift From Handling Contacts to Solving Problems
AI is increasingly capable of managing the routine work that has traditionally occupied much of an agent’s day: authentication, information retrieval, order-status inquiries, appointment scheduling, summarization, and even more complex transactions.
As those responsibilities move to AI, human employees are likely to spend more time navigating exceptions, resolving emotionally charged situations, interpreting nuance, and making decisions that require context and judgment. That doesn’t make the human role less important. It changes where its value lies.
Ebrahim Hyder, Vice President of Customer Service at Michael Kors, sees this as an opportunity to elevate the human side of customer service. “One of the biggest misconceptions about AI is that it will replace the human element in customer service. In my view, AI actually elevates the importance of distinctly human skills,” Hyder explains.
Michael Kors has invested in AI through initiatives such as Mia, its virtual assistant, which handles routine, transactional interactions. But when a customer is dealing with a missed delivery tied to a special occasion, the interaction requires something different.
“Where humans become even more valuable is when emotion enters the conversation. Empathy, judgment, relationship-building, and the ability to interpret nuance are skills technology still struggles to replicate authentically,” Hyder added.
The distinction is important. Customers don’t necessarily want a person involved in every interaction. They want the right kind of support for the situation they’re facing. For CX leaders, that means moving beyond how many agents AI can replace and considering what employees should do once automation removes work that no longer requires a person.
The Next Generation of Agents May Look Very Different
As AI becomes more autonomous, customer service employees may increasingly find themselves managing outcomes rather than simply responding to individual inquiries. Consider an AI agent that can investigate a billing issue, retrieve information from multiple systems, recommend a resolution, and initiate a transaction. The human employee’s role may be to oversee that process, recognize when something isn’t right, and step in when the situation exceeds the system’s capabilities.
That requires a different combination of skills. AI literacy and data literacy will matter, but so will critical thinking, communication, problem-solving, and the ability to recognize when an automated recommendation shouldn’t be trusted.
Some organizations may introduce entirely new positions, including AI trainers, conversation designers, automation analysts, knowledge managers, and AI governance specialists. Others may find that existing roles evolve. Quality leaders may begin evaluating AI interactions alongside human ones. Workforce managers may oversee blended teams of people and AI agents. Training leaders may focus more on teaching employees how to collaborate with technology and exercise sound judgment.
There’s also an important consideration that can get overlooked: AI may eliminate certain tasks while creating new ones. Someone still needs to validate AI recommendations, correct mistakes, provide missing context, manage exceptions, and monitor performance. IBM’s 2026 research found that 80% of CHROs believe AI adoption creates this kind of “invisible” work.
Organizations will need to recognize these responsibilities, define them, and determine how they fit into the workforce of the future.
Are We Creating Better Career Opportunities or a Training Gap?
One of the biggest challenges in workforce reinvention may be preparing employees for jobs that don’t yet exist while preserving the opportunities they need to develop the skills those jobs will require. Traditionally, employees built expertise by handling routine interactions before progressing to more complicated situations. Repetition, exposure, mistakes, and coaching helped them develop the judgment needed to manage difficult customer scenarios.
But what happens when AI handles many of those foundational interactions? If new employees rarely encounter straightforward problems, how will they learn to recognize unusual ones? If AI diagnoses an issue, how will employees develop the ability to diagnose it themselves?
This creates a potential training paradox. Organizations want experienced employees with strong judgment, but automating the work that once helped people develop that judgment could make expertise harder to build. It also raises questions about career development and compensation.
In the CX Agent Insights: Perspectives from the Frontline report, only 47% of agents said their organizations offer clear career paths and advancement opportunities, even though 67% said they plan to stay and grow in the field.
If employees are expected to take on more complex responsibilities, manage AI-driven workflows, and protect increasingly important customer relationships, organizations will need to reconsider whether traditional job descriptions, compensation structures, and advancement opportunities still make sense. AI could make customer service careers more sophisticated and attractive. But that outcome will require intentional investment in mentoring, training, career pathways, and opportunities to practice the skills that technology cannot replace.
Workforce Reinvention Can’t Be Just an IT Initiative
Another important consideration is who owns the workforce transformation.
AI adoption often begins within technology, operations, or digital teams. But redesigning work requires input from human resources, CX leadership, and the broader organization. IBM’s 2026 CHRO research found that 46% of organizations don’t involve the CHRO when defining AI strategy. Only 26% clearly define work across human-led, AI-assisted, and AI-executed activities.
That suggests a disconnect between technology adoption and workforce planning. HR needs to be involved before organizations start eliminating responsibilities or restructuring teams. Decisions about which tasks belong to people and which belong to AI will influence job architecture, compensation, skills development, career progression, and organizational design.
Ultimately, AI workforce strategy should be a shared responsibility across CX, HR, technology, and executive leadership. The goal isn’t simply to prepare employees to use new tools. It’s to determine how the organization itself needs to change.
The Customer Still Needs a Human When It Matters
There’s one more perspective CX leaders cannot overlook: the customer. As consumers become more comfortable interacting with AI, their expectations around human support aren’t necessarily disappearing.
Gartner’s 2026 research found that 50% of customers say interactions are easier when companies use generative AI. Yet 87% say companies using generative AI for customer service must provide an option to reach a human agent. Those findings aren’t contradictory. They point to an important distinction: Customers are willing to let AI handle an interaction when it makes the experience easier. They become less willing when technology creates another obstacle between them and a resolution.
The same principle applies to employees. AI should remove unnecessary work, improve access to information, and give people more capacity to solve meaningful problems. It shouldn’t simply increase monitoring, reduce autonomy, or make employees accountable for decisions they cannot control.
As Hyder puts it: “I believe the future of customer service isn’t AI versus people. It’s AI creating space for people to do more meaningful work. The more AI removes repetitive tasks, the more our teams can focus on moments that build trust, loyalty, and emotional connection.”
The Bigger Question: What Are We Building Around AI?
AI adoption can create enormous capacity, but capacity alone doesn’t guarantee better customer experiences or stronger business results. What organizations do with that capacity will ultimately determine the value of their investment. Will they simply reduce headcount? Handle more customer volume? Give employees more time to resolve complex issues? Create new career opportunities? Or pursue some combination of all four?
The answers will differ across organizations, but one thing is becoming clear: Automating work and reinventing the workforce are two very different challenges. CX leaders need to understand which activities should be automated, which should be AI-assisted, and which should remain human-led. They also need to rethink how employees are trained, evaluated, compensated, and prepared to take on greater responsibility.
Perhaps the simplest question to ask is this: If you turned off your AI tomorrow, would you know exactly what your people are uniquely responsible for? If the answer isn’t clear, your organization may have adopted technology faster than it has redesigned the work around it.
Explore the full article in our October issue of CX Insight magazine for a deeper look at how AI is reshaping the customer service workforce, including the evolving role of human agents, emerging skills and career paths, compensation considerations, and the organizational changes CX leaders need to start planning for.
