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Contact center vendors across the market are introducing AI as a feature of their platforms. From chatbots to predictive analytics to interactive voice response, the possibilities appear endless. With the abundance of AI in the contact center, one has to wonder, is the technology actually solving the concerns of customers and agents?
"Sometimes customers want something very straightforward that doesn't even need AI. Others want the full power AI brings," said Jafar Adibi, head of data science and AI at Talkdesk. "A good AI system makes three things possible: gathering data, providing context and inferencing."
With every vendor claiming to offer AI in the contact center, it can be difficult to separate true innovative AI features, like voice fraud detection, from AI as a buzzword. According to Adibi, vendors are focusing on five trends to drive adoption of contact center AI.
1. Optimization. Vendors are using AI to streamline the contact center experience. AI can collect information, provide context for interactions, and ensure a faster call time and a better customer experience by allowing agents to get directly to the call's purpose.
"If a flight is canceled, for example, and a customer calls the airline contact center, AI can provide context taken from the flight number and give the agent information, such as that the flight was canceled, where the flight was headed and when the next available flights are," Adibi said. "All of this is done without the customer having to provide additional information during the interaction."
Contact centers can also use the context provided by AI to route calls to the agent with the appropriate skills to quickly resolve an issue.
2. Automation. Automation plays a vital role in both customer experience and agent retention. Automation through chatbots has seen a surge in popularity due to the changing demographics of contact center customers. According to Adibi, millennials are more likely to choose text-based communication, so having sophisticated chatbot AI is essential to their customer experience. By automating with AI chatbots, more issues can be solved without the aid of an agent.
In the case of a canceled flight, a chatbot might be able to use the customer's flight number to automatically offer new flight suggestions and make it easier for the customer to reschedule.
Jafar Adibihead of data science and AI, Talkdesk
Likewise, AI being able to autofill forms post-call is another way to lessen the workload placed on agents. Adibi said automating workflows leads to happier agents who stay longer in their positions.
3. Prediction. AI in contact centers is often focused on predictive behavior, such as analyzing data sets to estimate how many calls are expected in an upcoming shift to dictate how agents need to be scheduled. Vendors are taking the technology a step further by developing predictive analytics that can tell agents what the calls will be about.
For example, if a company has a new product launch, the AI could predict what customer calls will be related to the new product and agents can adjust their interactions accordingly.
4. Recommendations. AI can also be used to manage agent performance by monitoring agents during a customer interaction and making recommendations. Using voice analysis, for example, AI can recognize indicators that a customer is stressed and provide recommendations to the agent in real time to assist in handling the call.
Some AI in contact centers can go as far as recommending that agents go grab a coffee if it recognizes a dip in efficiency or performance. Vendors are particularly interested in AI recommendations, as they can directly affect the customer experience.
5. Discovery. One of the more useful trends in AI in the contact center is AI-enabled discovery and analytics. Contact centers can find value in AI that can comb through call data and determine how effective an interaction was and how the interaction could be replicated across the contact center.
Discovery AI in contact centers offers the ability to recognize patterns and locate any fraudulent activity. AI that discovers and analyzes patterns, whether in customer behavior or agent responsiveness, can be used to implement new tactics and practices across organizations, which Adibi said can lead to a better customer experience.