Automated quality management (AQM) is the use of artificial intelligence (AI) and automation to evaluate customer interactions, score agent performance and surface insights without manual review. It analyzes voice and digital conversations, flags quality issues and accelerates coaching. Unlike traditional sampling, automated quality management reviews interactions at scale so enterprises can improve consistency and compliance.
“Using insights generated from quality management can have a direct impact on improving agent performance and more. If an agent consistently struggles to comply with certain regulatory requirements, speech analytics will flag these instances and prompt managers to take corrective action.”
Rakesh Tailor, VP of Product Management for Workforce Engagement Management, Genesys
Enterprises often struggle with low-quality visibility because manual audits capture only a small fraction of interactions. Automated quality management uses AI-driven transcription and scoring to evaluate nearly every voice and digital conversation. Leaders gain accurate performance insights, reduce subjectivity and ensure compliance monitoring keeps pace with volume.
Managers traditionally spend hours searching for examples to use in coaching. Automated quality management identifies behaviors, trends and skill gaps automatically. Enterprises use these insights to personalize coaching, target training and engage employees with clear, consistent feedback that helps teams improve faster.
Regulated industries face high stakes when it comes to accuracy and adherence. Automated quality management detects compliance deviations in real time across all channels. Enterprises use this capability to mitigate risk, document adherence and intervene early before small issues become costly exposures.
Customer frustration often stems from inconsistent interactions. Automated quality management pinpoints patterns tied to customer effort, sentiment and resolution quality. Enterprises use this intelligence to refine workflows, improve knowledge resources and ensure experiences feel more empathetic and connected.
Quality teams frequently operate under resource constraints. Automated quality management removes manual bottlenecks by scoring interactions automatically and flagging outliers or opportunities. Enterprises gain operational efficiency, reduce time spent on repetitive tasks and reinvest capacity in strategic improvement initiatives.
