Bridging the Gap: Artificial Intelligence in the Contact Center

When it comes to contact centers, quality assurance, and monitoring are two critical factors impacting customer experience. However, despite their value, these processes have traditionally been labor-intensive and difficult to measure for managers and other leaders. Therefore, many organizations are faced with a dilemma– how can they manage the efficiency of agents’ workflows while still making sure they are productive and attuned to customers’ needs?

Enter artificial intelligence. During operation, contact centers generate many insights that are useful for understanding and enhancing the customer experience. By pairing these insights with AI, we can now utilize them to automate key processes and further enhance agent productivity.

For managers, insights powered by AI are imperative for quality monitoring and performance– saving time while quantifying feedback and finding opportunities for improvement in customer care.

In essence, AI can help agents to do their jobs better, more efficiently, and with less stress. A win-win for all. 

The Intelligent Customer Experience

Over the years, we have seen the integration of automated services into the contact center– for instance, chat assistants (not bots) who assist the agent with lower-level tasks– but the next step is understanding the practical benefits of enhanced automation across organizations. Thanks to the rise of large language models (LLM) and the popularity of remote work following the pandemic, we are now seeing the barriers to adoption significantly decrease, while agent and customer willingness to engage with automated services is on the rise.

The willingness of customers to engage with these services cannot be overstated. When it comes to customer pain points in the contact center, any agent or manager will tell you that call deflection is the first item that comes to mind. In the past, deflected calls often served as a major issue for customers and agents alike.

Customers felt like they were conversing with a bot who did not understand or could not handle their issues, and when calls escalated to the agent to be handled, agents interacted with frustrated individuals who had little patience remaining.

Now, with AI, call deflection can serve as a pivotal customer touchpoint that further enhances the agent’s ability to provide first time contact resolution, while the customer can provide helpful information that reduces their time-on-call. Virtual agents, powered by AI, function as an intuitive way to engage with the customer. Unlike pre-recorded prompts, these virtual agents can intelligently gather information, resolve requests, and elevate to a “real” agent if necessary.

Better yet, the voice capabilities of these agents have increased in sophistication and now produce very realistic, natural, flowing conversations. Virtual agents can also highly personalize a conversation and offer real solutions, rather than leading the caller down “dead ends” or giving them no option but to escalate to a live agent. With these receptionist services, the dreaded “hold time is XX” messages are eliminated, and you can cut down on the overall time employees spend answering simple queries that are best handled by an automated virtual agent.

The Quality Conversation

Currently, only about 3% of contact centers engage in quality monitoring (QM) processes, a statistic that severely limits how contact center managers can use this information. Often, few calls are sampled for QM and there is heavy bias implicit in these calls, as agents may interact with customers in a wide range of topics and situations. Complicating matters, managers must take the time and resources to sift through QM results– a labor-intensive process that is often too inefficient to be of much use.

Enter AI. Organizations can upgrade their quality monitoring protocols by layering this technology over customer-agent interactions. Advanced speech analytics can ascertain QM standards on friendliness, helpfulness, etc. while detecting certain keywords associated with customer satisfaction. Further, AI can evaluate every single call and take manual scoring out of it completely, enabling scorecards based on script and tone that are far superior to what exists today. This allows managers to spend more time tracking and addressing KPIs, such as average handle time, and implement performance improvement solutions where necessary.

Crucially, most, if not all, contact centers face pressure from the top down as managers are expected to do more with less while pushing their agents to do the same. By using qualitative insights, those in operations can make vastly informed decisions about how their agents are performing, what actions are needed, and avenues for potential cost savings.

The Path Ahead

For any organization looking to integrate AI in a contact center, it is imperative to understand where they are in their technology maturity journey. While barriers to adoption have dropped, there is still an investment of time and money needed to ensure integration happens in the right way– and for the right reasons. For many organizations, a jump from agent-staffed calls to a fully virtual experience is not the right move. Rather, you should ascertain whether your industry and operation are the right fit for these services, how you can start to gradually introduce them to your workflow, and find vendors that understand and are attuned to your company’s needs.

In the end, artificial intelligence is not a silver bullet for the contact center, but it is a meaningful step in the quest for enhanced quality assurance and customer service and maturation of your CCaaS solution. And, with the proliferation of vendors offering AI-enabled services, it’s no longer just massive corporations who can afford integration. For savvy organizations, the time is ripe to start looking into this technology– for the benefit of your agents, managers, and customers alike.

Gina is the lead product manager for CCaaS and AI at GoTo and a subject matter expert in the contact center space. She brings more than a decade of customer experience expertise to the role and works closely with product, engineering, and design leaders as well as customers, analysts and partners to drive contact center strategy and product development.