Authored by Jon Arnold from J Arnold & Associates
Artificial Intelligence (AI) has become the dominant trend in tech now, and while little-understood, it cannot be overlooked by businesses. The underlying technologies may be complex, but more importantly, AI-driven change is happening quickly and on a larger scale than we’ve ever seen before. Voice is just one of many applications being impacted, and when considering all the various tools we use to communicate, the entire communications experience is being transformed now by AI.
Voice applications will evolve on their own in this new landscape, but it’s also important to recognize the bigger changes when tied to the broader communications experience. To make good business decisions about AI, the benefit should not be viewed in terms of making incremental improvements to what you’re already doing. Rather, AI is an agent of transformational change; these capabilities are large-scale by design, and will create new applications for voice that could not have existed before.
At face value, it’s easy to view AI as a way to increase automation and reduce costs. These outcomes are perfectly reasonable, as all businesses can stand to have more of both. While these can easily be sufficient for supporting a business case, AI needs to be use case-driven; so instead of the “what” for where it can be of value, decision-makers should focus on the “how”. That’s how you can truly tap AI’s potential, and business leaders need to think bigger about transformational use cases and voice applications that break with traditional ideas based on legacy technology.
In terms of the overall communications experience, the possibilities for AI-driven voice go well beyond how we think about voice today. That thinking has largely been telephony-centric, and while that use case isn’t going away, new forms of voice are emerging that add new value in the workplace as well as the contact center. To illustrate, here are two prime examples, one for the workplace, and one for contact centers.
Increasingly, voice is becoming part of a broader suite of communications applications that generally fall under the UCaaS umbrella. Prior to UCaaS, voice was primarily used on a standalone basis – via the PBX phone system - making it a standard point application. As cloud adoption expanded, UCaaS emerged as the platform of choice to integrate all communications – especially real-time channels like voice and video – into a singular interface where workers could seamlessly shift from one mode to another.
UCaaS has become the cornerstone for workplace productivity, largely based on providing an easy-to-use experience, regardless of whether working in the office, at home or on the go. That’s a pretty strong value proposition, but note that voice’s role is largely telephony-centric, supporting person-to-person communication.
AI is a more recent development, and while it can make UCaaS more “intelligent”, it is also taking voice into the realm of person-to-machine or machine-to-person applications. In this context, voice is being used more to drive new applications – both to increase automation and drive out cost – than to support person-to-person conversations.
This brings us to digital assistants – sometimes called meeting assistants – which is basically a new type of chatbot that serves as a virtual secretary. Workers typically engage with these chatbots using voice, but text can be used as well. Voice, however, is more immediate and intuitive than text, and once dialog is established between worker and chatbot, things start happening quickly. On a basic level, this use case for voice is similar to Siri or Alexa, which is primarily voice-based search.
Today’s AI takes things a few steps further. Not only is voice now being used to automate workflows – especially routine tasks – but also to proactively help manage your schedule, such as reminders for upcoming meetings, or offering to help set up a conference call with your team.
Aside from making workers more productive and giving them more control over managing their time, these capabilities help make work itself more satisfying. From there, it’s not a large leap to see how digital assistants can improve performance – both individually and for teams – but also employee retention – all of which support business-level outcomes that are important to decision-makers.
AI is the enabler for all this, especially Machine Learning and Natural Language Understanding. These are the underlying technologies that have elevated speech recognition to where it can be trusted for workplace use. Not only is it good enough for digital assistants today, but speech recognition will continuously “learn”, allowing more complex tasks and workflows to be automated, and taking productivity to newfound heights.
This is a very different use case scenario, but one that can equally be transformed by AI. Instead of each worker having a digital assistant, each contact center agent can now have a virtual agent assistant. Agents can use these assistants in similar ways – namely to direct them with voice to manage workflows. With agents being under steady pressure as they deal with customers in real-time, voice is a highly effective channel for getting tasks done efficiently.
Without AI, agents would be typing out requests to do things, and likely spending a lot of precious time simply searching for the relevant information. Virtual assistants, on the other hand, “know” the agent’s workflow, bringing a level of automation to the desktop that agents never had before. As with the workplace, these capabilities make the agent’s workload more manageable, freeing them up to focus more on customers. When agents can perform better, their job satisfaction increases, as does customer satisfaction, both of which are key KPIs for contact center leaders.
There’s a second, transformational contact center use case for AI, namely having better chatbots for self-service. Call volumes continue to rise for most contact centers, and automated forms of self-service are playing a larger role to manage this. It’s not practical or economically feasible to just hire more agents, so the spotlight falls on self-service, which has long been a feature that customers embrace and a pain point for contact centers.
Legacy systems still dominate the contact center landscape, and this includes IVR, which by today’s standards is woefully inadequate for today’s customer expectations. With so much riding on improving customer service, AI-driven chatbots represent a major step forward from IVR as a more modern way to provide self-service.
First generation chatbots have had limited utility in this capacity, but recent advances – especially conversational AI – create a more natural voice experience where today’s chatbots can have a deeper engagement with customers. Not only does this form of service automation take some pressure off agents, but as customers become more comfortable with “intelligent” chatbots, more inquiries can be handled solely via self-service.
AI is finding its way now into both the workplace and the contact center, and business leaders need to pay close attention. The technologies may be complex, but AI’s impact will be transformational, and goes beyond replicating what you’re already doing. There’s a much richer value proposition when using AI to enable new capabilities, and voice-based applications are one of the more exciting opportunities.
Voice will continue having great utility for telephony and other forms of person-to-person communication. However, with recent advances in areas such as conversational AI or ChatGPT, AI brings more intelligent and engaging forms of voice-based interaction that help automate workflows and customer service.
We’re just at the beginning for what’s possible, but these outcomes can bring new business value today, and there’s much more to come. There is no need for IT decision-makers to take a wait-and-see approach with AI; the benefits are here now, and voice is a great place to get started.