2023 Trends: AI for Better Agent & Customer Experiences
Over the course of 2022, artificial intelligence (AI) became mainstream for contact centers. In 2023, it will become table stakes. As with cloud adoption, the promise of AI has become compelling enough that contact center leaders are no longer wondering if it has a place in their plans.
Unlike legacy technologies that are fully-formed when deployed, AI-based applications are iterative – they get better the more you use them. As such, the business value may take some time to be realized, so a bit of patience is required. In 2023, AI should be at the top of the list for contact center leaders, as the earlier deployments during 2022 will be more mature now.
This represents another important difference from legacy technology – AI evolves much faster, so the benefits will accrue in less time. There are many areas where emerging applications are poised to make a big impact during 2023, both for improving the agent experience (AX) and for making the customer experience (CX) smarter. To illustrate, here are three examples.
1. Noise Suppression
Automated speech recognition (ASR) is an important contact center use case for AI. This is a very specific use case for AI, and aside from being very practical, the benefits are easy to understand. Noise suppression blocks out audio that is not human speech. AI applications can recognize these distractions and supress them so agents can better focus on their customers. Essentially, noise suppression adds intelligence to block out background noise so human voices can be heard more clearly.
This improves the agent experience, especially for those working from home and might not have access to a quiet environment. McKinsey’s American Opportunity Survey found that 58% of American workers can work from home at least once a week; 87% said they take the opportunity to work flexibly when they have the chance. Remote work will continue to become more common in 2023. By suppressing audio that isn’t speech-based, speech recognition engines driven by AI – will be more accurate in capturing conversations, which will ultimately lead to better customer experiences.
2. Workflow Automation
Workflow automation is an important contact center use case for AI. This use case can take many forms, with self-service automation often coming to mind right away. Another important variation would be the automation of workflows. Whereas the former is entirely customer-facing, workflow automation is internal with the focus on streamlining operations and processes.
The intent is to minimize the need for agents to manually manage repetitive tasks or keep switching across various apps to retrieve and organize information during customer interactions. AI applications will access the relevant pieces from a customer’s history – chat threads, previous orders, unresolved issues – and pull them up on the virtual agent desktop so everything is in one place.
This form of workflow automation allows agents to engage more deeply and personally with customers, setting the stage for a much-improved CX. Without AI, agents wouldn’t be able to access all of this in real-time, let alone sift through all the data sets to focus on the right things. This is where predictive analytics come into play, and you can expect to see more of this in 2023. It’s also worth noting how workflow automation improves AX by freeing agents from tasks that take away from time spent with customers and making their workloads more manageable.
3. Virtual Agent
Workflow automation puts agents in a better position to serve customers more effectively, but the most important determinant of CX is what happens during customer interactions. The term “virtual agent” can mean many things, but there are two use cases in particular that can lead to better AX and CX.
First would be with chatbots, where AI enables virtual agents to take self-service further than legacy-based IVR. This is another form of automation. AI applications understand customer interactions and intent, and can engage further along in the process, reducing the amount of time agents need to spend with customers. At that point, the agent is only dealing with customers for the most sensitive or complex needs, where human judgment and empathy make all the difference.
A second virtual agent use case is assisting or coaching agents during the interaction with customers. This is where tools like sentiment analysis come into play, as AI can often ‘read’ the customer’s mood faster than agents can and provide agents with the right scripts or templates in real-time. Not only can this help mitigate a potentially negative CX, but also empower agents to hand difficult situations.
This form of virtual agent can improve AX in many other ways, especially around following scripts that AI tools predict will yield the best outcomes. Contact centers only just started down this path in 2022, and with the economy expected to be more challenging in 2023, interest in using virtual agents to improve CX should only intensify.