According to a new study by Frost & Sullivan and SuccessKPI, two-thirds of customer service operations aim to integrate AI into their cloud-based Workforce Engagement Management (WEM) applications within the next three to five years. This move addresses growing skills gaps, rising costs, and limited resources, allowing agents to deliver enhanced customer engagement.
“In terms of AI, (it) really helps better predict the agent’s needs. AI is really helpful as it is more targeted and more personalized, which also is more humanizing. As an agent, I don’t need to waste time on something I already know, but at the moment, I might need some training on a specific task. Clearly, that’s why many businesses intend to move WEM to the cloud, focused on the supervisor helping their teams perform better,” said Alpa Shah, vice president of CX at Frost & Sullivan.
The survey highlights significant market demand for AI-powered WEM solutions that enhance the customer experience (CX). These tools extend beyond customer service calls, supporting comprehensive workforce management needs such as training and adapting to remote or hybrid workstyles.
Moreover, only 30% of enterprises believe that WEM features within Contact Center as a Service (CCaaS) platforms best fit their organizations. The remaining 70% cite the challenges of managing multiple CCaaS platforms alongside blended on-premise and outsourced operations, underscoring the preference for standalone AI-powered WEM applications.
From a vertical perspective, healthcare leads in AI-powered WEM adoption, excelling in categories like automation, AI-guided resolution, and speech/text analytics. Conversely, government and financial services lag significantly, with the government reporting the lowest use of contact centre automation (45%). Modernizing legacy systems remains a top priority for these sectors.
The retail and e-commerce industry performs well, especially in automation and proactive customer care outcomes. Meanwhile, Business Process Outsourcing (BPO) has seen strong adoption of cloud-based CCaaS but shows mixed results in automation outcomes.