Businesses embrace virtual assistants, but lack of strategy and employee buy-in hinder success

Reposted from CX Dive. Authored by Rosalyn Page    

The pandemic and ongoing digital transformation efforts have driven more businesses to adopt intelligent virtual assistants to ease the pressure on customer service and support.  

The popularity of contact center intelligent virtual assistants shows no signs of abating. In 2022,  Gartner projected that 1 in 10 agent interactions would be automated by 2026 through voice, chatbots and digital channels. 

Now with new generative AI tools, there’s a renewed push for efficiencies and improving customer engagement, but without employee buy-in and a strategy built on robust metrics, it could fall short of expectations. 

For employees, new terminology for AI technology can present a barrier to adoption, according to a report by analyst firm  Valoir. It found terms such as “co-pilot” don’t positively resonate, whereas “virtual assistant” is viewed more favorably. 

Building trust is a key factor for effective adoption with individual users, the report noted. This entails clearly outlining policies and practices, and providing role-based explanations of the benefits. 

Navigating the risks and pitfalls 

While the benefits of intelligent virtual assistants are compelling, organizations risk wasting their investment and not securing employee buy-in if they fail to adopt a measured approach and organize internal systems, according to Gartner.  

This includes allocating sufficient resources to support proper data integration and features such as natural language understanding. Each particular call flow needs to be built out and then fine-tuned for improvements, the research firm said. 

“Implementing virtual assistants just to automate tasks won’t improve customer journeys or the employee experience,” said Samy Zachary, solution development architect at CX consultancy Alorica. 

Businesses need to use historical data to identify customer pain points to develop clear business objectives and help employees understand the desired outcomes, according to Zachary. 

However, given that AI is rapidly developing, investing heavily risks newer innovations quickly superseding adopted systems. 

The role of humans can’t be overlooked, either. With any platform, context and conversational exchanges are needed to train the models for suitable responses, which includes striking the right tone.  

“If it leads to insensitive responses not aligned with the brand’s values, it can cause reputational damage,” he said. 

Organizations want to avoid over-relying on AI and downplaying the importance of their employees, who need to be part of the process to help the models learn and respond to customers when their queries warrant it. 

“It’s vital to set boundaries on responses and know when to appropriately transfer to a CX agent,” he said. 

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