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Report 13 Apr 2026

Improving Contact Center Efficiency Through AI-driven Automation – InBrief Analysis

This report examines how AI-driven automation is beginning to reshape contact center operations beyond earlier waves of scripted automation. It highlights the potential of large language model-based systems to improve efficiency, service quality, and workforce capacity while pointing out that outcomes depend heavily on the surrounding operational environment.

  • Contact centers remain the main interface between organizations and customers; however, inefficiencies such as high agent attrition, inconsistent service quality, and rising interaction volumes continue despite earlier automation efforts.
  • AI-driven automation offers a more structural shift. Rather than relying on scripted deflection, it can orchestrate more complex interactions at scale and, in PAC’s view, has real potential to reduce average handling time, improve first-contact resolution, and rebalance cognitive workload across the workforce.
  • Value realization, however, depends on demanding conditions. Data quality, process clarity, and governance maturity strongly influence outcomes; organizations that overlook these factors often see pilots stall or weaken in production.
  • PAC advises organizations to treat adoption as a gradual build-out of operational capability rather than a one-off transformation project, recognizing that integration effort and change enablement usually account for a large share of total cost.

Recommended advisory: PAC Leadership Session – Agentic AI Adoption – Opportunities and Challenges

 

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Jennifer Jonat

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