Call centers are likely to handle more routine contacts through self-service and use AI to route requests or assist agents. Human work is more likely to shift toward exceptions, complex questions, and cases that require context and judgment than to disappear altogether. In the United States, the Bureau of Labor Statistics projects a decline in customer-service-representative employment, but also expects substantial annual openings as workers leave or move to other occupations.
Will AI replace call-center agents?
Automation is changing the tasks involved in customer service, but the available evidence does not support a prediction that call-center agents as a whole will vanish. Self-service systems, mobile apps, and social media already let customers handle some simple tasks without an agent. The U.S. Bureau of Labor Statistics says technical advances may let these systems take on more tasks, while some companies may retain in-house service teams to help with complex matters such as account refunds or insurance coverage. The BLS outlook covers customer-service representatives across industries and channels, not call centers alone.
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The International Labour Organization’s 2025 global index finds that one in four workers are in occupations with some exposure to generative AI. That is an exposure measure across occupations worldwide, not a forecast that one in four jobs will be eliminated or a call-center-specific estimate. The ILO says job transformation is the likeliest impact because most occupations include tasks that still require human input. Its highest exposure category covers 3.3% of global employment; that figure should not be read as a call-center job-loss rate. Read the ILO’s 2025 index.
What do employment projections say?
For the United States, the BLS projects customer-service-representative employment to decline 5% from 2025 to 2035. It also projects about 289,500 openings per year on average over that period, primarily because workers transfer to other occupations or leave the labor force. The openings figure reflects replacement needs and does not mean the occupation is projected to grow. Both figures are for the broader U.S. occupation, which includes service by phone, in person, email, text, chat, and social media across industries.
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These projections describe a net change in employment, not the fate of every center, employer, or role. They also cannot be generalized to the global call-center workforce. The task mix may change even where people remain employed: fewer contacts may require routine handling, while more of the human workload may involve unusual, sensitive, or unresolved problems.
How is AI changing customer service?
Routine self-service
Automated systems can let customers complete simple tasks without waiting for an agent. As those systems improve, some interactions may be resolved before they enter a staffed queue. The practical value depends on whether self-service actually resolves the customer’s issue and offers a clear route to a person when it does not.
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Routing and agent assistance
AI can also support the work around a conversation—for example, directing a contact or helping an agent find relevant information. These uses do not remove the need for a person in every case. Their effect depends on what tasks the system handles, whether agents can override or question its suggestions, and whether the customer’s issue is resolved accurately.
Complex cases and judgment
When a request involves exceptions, competing needs, or incomplete context, a human may be better placed to interpret the situation and decide what to do. The BLS notes that some companies may keep in-house centers to differentiate themselves through help with complicated matters. That is one reason automation is better understood as a change in task allocation than as an all-or-nothing switch.
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What do contact-center workers expect from AI?
In Call Centre Helper’s 2024 survey, respondents described expected benefits: 38% thought AI would reduce manual work, 35% expected improved customer experiences, 32.6% expected improved team performance, and 29.2% thought it would give teams more time for complex work. These are survey respondents’ expectations, not measured results or proof that AI caused those outcomes. See the 2024 survey.
The survey also reported traditional ACD/call-routing adoption of 93.4% in 2024 versus 94.8% in 2023, and IVR adoption of 89.9% versus 93.3%. Those year-to-year differences do not establish that AI caused a change in routing practices. Adoption figures alone also say little about service quality, resolution, or the experience of workers and customers.
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What jobs and skills are likely to remain?
The evidence points to continued demand for people who can handle work that is hard to reduce to a predictable script. The exact mix will vary by employer and industry, but likely areas of human involvement include:
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- Explaining options and consequences where customers need context rather than a standard answer.
- De-escalating sensitive or frustrating interactions with empathy and sound judgment.
- Checking automated recommendations, correcting errors, and escalating cases appropriately.
- Helping customers navigate exceptions such as disputed charges, refunds, or coverage questions.
These are task areas, not a guarantee of specific job titles or future hiring levels. As automation takes over portions of routine work, employers may redesign roles, change training needs, or reduce staffing in some functions while retaining human support in others.
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Why does workplace design matter?
Automation does not determine working conditions by itself. The ILO’s broader discussion of algorithmic management says these practices can improve productivity and service quality, while also creating risks involving worker surveillance and job quality. Its findings cover workplaces across countries and are not specific to call centers, so they should be applied to contact-center management as a relevant consideration—not treated as a universal description of every center. The ILO’s discussion quotes report co-author Uma Rani saying that social dialogue and strong industrial relations help employers and workers mitigate possible harms to job quality and protect workers.
For a contact center adopting automation, the important questions extend beyond how many interactions a system can process:
Quick Recap
- Task scope: Is the system handling simple self-service, routing, agent support, or decisions about complex cases?
- Escalation: Can customers reach a person when automation fails or their issue is complicated?
- Service outcomes: Are resolution and customer experience being assessed, rather than automation volume alone?
- Worker effects: How do monitoring, workload, discretion, training, and job quality change?
- Local context: How do geography, regulation, industry, and the type of interaction affect what is appropriate?
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