GenAI accelerates call center training, boosts agent skills: McKinsey
NEW YORK, UNITED STATES — Generative AI-based simulations are transforming contact center onboarding, making it nearly training-free and tripling performance indicators, according to McKinsey & Company.
This breakthrough comes as people in the call center industry often undergo outdated, expensive training, leaving those who ultimately interact with customers under-equipped.
Traditional call center training is inefficient and costly
Current training methods in call centers are slow, expensive, and fail to prepare agents for real-world interactions. It takes four to six months for new hires to reach peak performance, which costs companies 5% to 10% of their total expenditure on agents.
Most of the training is generic, not tailored to individual skill gaps, which results in poor performance and stagnant metrics. Agents are often ill-equipped, and learning in the classroom usually fails to translate well to handling live calls.
Moreover, performance gaps are exacerbated by the fact that during recruitment, essential skills such as empathy and the ability to handle customers in real-time are rarely examined.
Formal evaluation, especially in a remote working environment, can be challenging in terms of monitoring the progress made by new employees, which managers may struggle to assess.
AI-powered simulations deliver faster, smarter training
The AI platforms provide agents with an opportunity to train in a secure environment on various customer scenarios, offering immediate feedback and enabling agents to refine their work. This type of practical training may accelerate the learning process and establish trust before working with real calls.
Automated evaluations monitor primary indicators, such as first-call resolution (FCR), average handle time (AHT), and adherence to best practices.
One of its instances involved a technical help desk that utilized AI simulations, resulting in a 33% increase in positive interactions and a 28% decrease in interruptions.
Additionally, approximately 80% of coaching duties were automated. This data-driven approach enables constant improvement, while minimizing the need for manual monitoring.
