Workforce Management Featured Article
AI's Role in Call Center Training
Artificial Intelligence (AI) is a technology that’s seen rapid growth even just over the last decade. The ability for machines to understand and solve problems on par with human intelligence has applications across industries and is transforming business.
In fact, according to reports, the global artificial intelligence market reached $93.5B in 2021 and is expected to have a 38.1% CAGR from 2022 to 2030 as tech giants offer advanced technologies for automotive, healthcare, retail, finance and manufacturing.
In the contact center, the ability to better understand customer experiences and react in-real time to trends in customer data is improving call times, first resolution and strengthening brand loyalty.
One area where AI is now seeing strong use is for call center training. To take things a step further than the traditional use of AI to monitor live calls, listen for caller sentiments and offer feedback, AI is also being used to send out alerts that tell an agent that they should talk less and listen more, or even to send a note to call center managers with training intervention steps.
Brian Tuite, co-founder and CEO of Zenarate recently wrote about these advancements and how they are shaping the way call center agents are trained in an article for Forbes Council.
Tuite described the need he saw in the industry for solutions that addressed the increasing pressure on agents to become brand advocates and problem solvers for customers who are dealing with more complicated inquiries than ever before. Most importantly, to allow agents to train and become comfortable and confident to deliver on these advanced needs before they even get on a live call.
His company, Zenarate, uses technology in this area, AI conversation simulation, that he said is coaching agents in simulated environments to become top-performing talent for today’s call centers.
This technology works by creating a hyper-realistic scenario of voice or chat interactions using a combination of Natural Language Processing (NLP) and Natural Learning Understanding (NLU). It creates a real-time conversation between the agent and a customer where they can practice, learn, solve problems and build their skills and confidence in a realistic setting that doesn’t involve actual customers as the test dummies. Most importantly, it allows them to use their natural language to engage with customers in the most authentic way possible.
This low-risk training environment focuses on skills mastery and helps close the skills gaps in an industry that has historically been plagued by poor agent attrition rates and poor customer experiences.
Edited by Maurice Nagle
