Global Call Center Employment Declines as AI Raises Questions for Receivables Industry

Global call center employment has declined for eight consecutive quarters, according to new research from Revelio Labs, raising questions about how artificial intelligence and automation could reshape staffing, operations and workforce development across the accounts receivable management (ARM) industry.

The report, published Oct. 6, 2026, found that worldwide call center headcount is 5.3% below its December 2023 peak, reversing more than a decade of sustained employment growth.

Although the research examines call centers across industries rather than debt collection specifically, its findings have implications for receivables management companies that rely on contact center employees for consumer communications, payment arrangements, account servicing and collection activities.

Call Center Employment Falls After Years of Growth

According to Revelio Labs, global call center employment has experienced year-over-year declines for eight straight quarters. Of the 70 quarterly observations recorded since 2009, those eight quarters were the only periods showing annual employment declines.

The contraction began in higher-income countries before spreading to middle- and lower-income economies, where outsourced customer service operations have traditionally benefited from lower labor costs.

Revelio Labs reported average hourly wages of $22.52 in high-income countries, compared with $5.44 in upper-middle-income countries and $2.32 across six lower-middle-income countries.

Historically, these wage differences encouraged companies to offshore call center operations. However, the latest findings suggest that lower labor costs are no longer sufficient to sustain global employment growth in the sector.

By the fourth quarter of 2025, call center employment was declining across the income groups examined, although individual countries, including China and Nigeria, continued to show growth.

For receivables management companies operating domestic and offshore contact centers, the findings raise questions about how traditional labor-cost advantages may change as automation becomes more widely available.

AI Adoption Could Be Contributing to Workforce Declines

The report identifies artificial intelligence as a potential contributor to declining call center employment, particularly as businesses introduce chatbots, automated customer support systems and AI-powered communication tools.

Researchers found that before ChatGPT’s November 2022 launch, call center employment generally followed trends in other office and administrative occupations across 12 middle-income countries.

After its introduction, call center employment stagnated or declined while other white-collar occupations continued expanding.

The researchers cautioned that the findings do not establish a direct causal relationship between AI adoption and job losses. Post-pandemic hiring adjustments, higher interest rates, and corporate cost-cutting may also have contributed to the decline.

However, the divergence between call center employment and other office occupations suggests that technological changes may be affecting contact center staffing differently.

Major contact center operators are already pursuing AI-related efficiency improvements. The report noted that TP, formerly Teleperformance, is targeting annual savings of 150 million to 170 million euros through an AI and cost-reduction initiative. TaskUs leadership has also indicated that agentic AI could reduce customer support costs by 25% to 50%.

These developments illustrate the financial incentives encouraging companies to evaluate AI-supported customer interactions and automated workflows.

What AI Adoption Means for Receivables Call Centers

Within the ARM industry, artificial intelligence is increasingly relevant to how collection agencies, creditors, and third-party servicing companies manage consumer interactions.

Potential applications include automated account inquiries, payment reminders, call transcription, conversation summaries, quality assurance reviews, and agent assistance.

AI systems may also help employees retrieve account information, identify applicable procedures, and document consumer communications more efficiently.

For receivables call centers, these technologies could reduce the amount of employee time required for repetitive administrative activities while allowing human agents to concentrate on more complex consumer situations.

However, the Revelio Labs findings should not be interpreted as evidence that debt collection employment specifically has declined by 5.3%, or that AI is directly responsible for workforce reductions at collection agencies. The research covers the broader global call center workforce.

The industry’s regulatory obligations also distinguish debt collection operations from many general customer service environments.

Companies implementing AI-supported communication tools must consider the Fair Debt Collection Practices Act (FDCPA), the Telephone Consumer Protection Act (TCPA), applicable state collection laws, and requirements governing consumer privacy and information security.

Automated communications, particularly those involving AI-generated voices or outbound calling, can introduce additional compliance considerations. The Federal Communications Commission has confirmed that AI-generated voices fall within the TCPA’s restrictions on artificial or prerecorded voice calls.

As a result, staffing decisions involving AI must account for regulatory compliance, consumer experience, and the continued need for human oversight.

Reduced Hiring Appears to Be Driving the Contraction

One of the report’s findings is that declining employment appears to be driven primarily by slower hiring rather than a surge in workers leaving call center jobs.

Across the 12 middle-income countries studied, the rate of workers entering call center employment fell from 25.1 to 17.2 per 100 workers since November 2022.

During the same period, the exit rate declined from 22.3 to 18.5 per 100 workers.

Because hiring fell faster than departures, the workforce contracted even without a corresponding increase in employee separations.

This distinction is relevant for receivables management employers evaluating how automation could affect future staffing requirements.

Rather than immediately eliminating existing positions, organizations may be able to reduce hiring needs through improved employee productivity, automated workflows, and changes in workforce allocation.

The report does not establish whether receivables call centers are following this pattern, but it identifies a potential staffing model for employers evaluating AI investments.

Workforce Transitions Present Additional Challenges

The research also found that call center employees leaving the industry frequently struggle to transition into higher-paying technology and customer relationship positions.

Among workers tracked across the 12 middle-income countries, only 10.8% moved into technical support, customer success, or software and data occupations.

Approximately 49.7% transitioned into other customer service, sales, office or human resources positions.

Meanwhile, several higher-paying occupations continued expanding. Software and data employment increased 8.9% over the previous year, while customer success and client relations grew 7.2%. Technical support employment increased 2.6%.

These findings suggest that employers introducing AI technologies may need to consider additional employee training and career development opportunities.

For collection agencies, potential workforce development priorities include compliance oversight, dispute resolution, complex account servicing, quality assurance, and supervision of automated systems.

Such roles may become increasingly important as organizations incorporate AI into existing collection and customer service processes.

Receivables Industry Faces Operational and Compliance Decisions

The findings provide broader labor market context for ARM companies considering investments in AI-powered contact center technology.

Automation may offer opportunities to improve productivity, manage operating costs, and support employees handling large account volumes. However, the extent to which these improvements translate into reduced staffing will depend on each organization’s technology, operating model, and compliance requirements.

Receivables management companies must also evaluate whether automated systems can consistently handle consumer inquiries, recognize disputes, support appropriate escalation, and maintain accurate records.

Human involvement remains particularly important when interactions require judgment, individualized assistance, or regulatory interpretation.

The International Labor Organization has also examined how generative AI could affect entry-level office employment, particularly in economies where call center positions have historically provided pathways into formal employment.

For the receivables industry, the broader trend suggests that AI adoption may increasingly influence hiring, training, and contact center investment decisions.

While the Revelio Labs research does not measure AI-related employment changes within debt collection, its findings highlight the importance of monitoring workforce trends as automation becomes more deeply integrated into consumer financial communications.