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Empowering Agents Is the Best Use Case of AI in Contact Centers

Empowering Agents Is the Best Use Case of AI in Contact Centers

Uthaman Bakthikrishnan

Uthaman Bakthikrishnan

Executive Vice President

How often have customers used your self-service channels like chatbots and wanted to talk to an agent to resolve their queries?

This leads to customer dissatisfaction as customers feel their time was wasted on the self-serve platform and could take it out on the agent. Besides, you also have duplicated costs associated with self-service and assisted service.

How often have you approached a brand’s social media handle with an issue only to be directed to contact the call center?

The most helpful reply I received on a Twitter handle was to send my phone number to an email address, and I can expect a call back from them.

I’d much rather call the contact center than go through this roundaboutly.

What if I don’t contact the call center after this interaction? You have created a data silo, and there is no way you can capture my needs.

Adding channels without determining how they would be handled internally as part of your customer experience function creates more complexity than you can imagine.

Meeting Customers Where They Are

“Meeting customers where they are” was a catchphrase in the 2000s. Initially, when contact centers started mushrooming, the only channel was telephony, and contact centers were focused on handling phone calls better.

This resulted in improved customer service, and the customer satisfaction scores peaked.

When email and chat became commonplace, organizations also started offering customer service and support through these channels.

The customers could get in touch with the organization through multiple channels. But the channels weren’t integrated, and agents in one channel did not know the customer’s interaction in other channels.

This started creating data silos for the organization.

Every time, the customers had to repeat themselves. Customers did not like this experience, and the customer satisfaction scores fell.

Adding channels doesn’t ensure success.

Organizations understood that every additional channel would mean additional investments and resources. They started looking at an omnichannel infrastructure to ensure agents have a single view of the customers across all channels.

Is Artificial Intelligence (AI) The Cure for All Problems?

Here is the doomsday headline:

AI will take over the human race and will replace human beings.

Would this become a reality?

I doubt it very much.

The first vertical to adopt AI applications is contact centers. The contact centers began with chatbots to streamline customer interactions and provide customers with self-service options. However, in their haste to adopt AI, the focus has been more tactical than strategic. 

I have looked at some AI-powered videos where the AI platform makes a sales call for a car and keeps it conversational. It was amazing.

The video’s common sentiment was that AI would replace salespeople. Is this the beginning of the end for salespeople?

I also doubt this, as it may not understand the context of customer queries and may not be empathetic towards customers.

What Are the Correct Use Cases for AI in Contact Centers?

The most important understanding is that not all of your organization’s requirements can be addressed by a single AI application. Besides, AI would add complexities to your contact center operations by adding data siloes.

So, wouldn’t you find benefits from AI in a contact center environment?

AI can be pretty effective in contact centers. It can be used for routing, sentiment analysis, and agent guidance, but it doesn’t go deeper than that.

Besides these, it can answer transactional queries and handle all repetitive and mundane tasks, freeing the agents to address complex questions requiring empathy.  

AI can be used to process complex information. It can make sense of a humongous amount of data and create insights that the agents can use in their customer conversations.

AI doesn’t have to be 100% correct when it tries to assist agents – it can lead agents in the right direction or provide the right options. Agents would be able to provide the most appropriate resolution to customers based on the insights provided by AI.

Without proper planning, AI can cause havoc, resulting in dissatisfied customers due to increased calls, errors, and agent burnout.

When left unsupervised, AI can be a problem as it may not understand the context and would find it challenging to provide authentic answers.

It would be best to look at AI as an assistant to agents and self-service platforms, not as a replacement for agents. 

AI-Assisted Customer Experience

AI can enhance self-service options by giving customers quick and accurate responses to routine queries. This reduces the need for human agents, allowing them to focus on more complex and nuanced interactions.

AI can assist agents by offering real-time suggestions, relevant information, and recommended responses during interactions. This will help you provide more consistent, efficient, and effective support.

As a customer experience function, you can offer the choice to the customers to choose between AI-assisted self-service for routine matters or interacting with a knowledgeable agent when the situation requires more in-depth assistance.

The idea of using AI in customer experience should be strategic, considering the needs of the customers and agents.

Leveraging AI to enhance self-service capabilities and agent capabilities creates a comprehensive and responsive customer service ecosystem that contributes to a positive brand experience.

AI is here to stay and will help you do your jobs better.

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