What Is Contact Center AI? Your Complete Guide

The hottest topic in service today is AI agents, especially when it comes to contact center AI. The contact center is where customers can turn to for questions or help – by phone, chat, email, or self-service portal where they can take matters into their own hands.

AI agents are poised to improve efficiency and productivity within the contact center. According to our research, 95% of decision makers at organizations with AI report cost and time savings, and 79% of service organizations are investing in AI. Service leaders are excited about the potential for the exciting third wave of AI: agents.

Already, 49% of service professionals are using some form of contact center AI, while another 30% are experimenting with AI. Adoption of AI and AI agents will only continue to grow next year and beyond. So let’s look at what contact center AI is, its benefits, and three ways you can use contact center AI today, along with example use cases.

• What is contact center AI?
• What are the benefits of AI in the contact center?
• Let autonomous AI agents serve your customers
• Support service reps with assistive AI agents
• Use AI to monitor and manage the contact center
• Get started with contact center AI

First the basics: an AI-driven contact center uses technology to automate and enhance multiple components of customer service and support. These contact centers use AI to handle customer inquiries, manage interactions, and improve overall productivity and efficiency.

With AI, you can turn traditional contact centers into seamless, customized experiences for every customer. AI agents like Salesforce’s Agentforce give customers fast, accurate responses that are context-appropriate and conversational. They can understand a customer’s inquiry, come up with a plan, and even take action to resolve the issue. Or, when the issue is out of its purview, the agent can seamlessly hand-off the interaction to a service rep.

Contact centers play a major role in customer experience. Often, they’re the first place a customer goes to seek support. And if the contact center is difficult to use, impersonal, or slow, that’ll directly – and negatively – impact the customer’s experience.

One benefit of AI in the contact center is that it can be used to create a more personalized service interaction. Another benefit is improved efficiency and productivity. A third benefit is reduced operational costs. And finally, a key benefit is improved service delivery. With fewer manual processes and tasks to worry about, reps can spend their time on more complex cases while staying focused on the customer.

Here are 3 ways you can use contact center AI now.

Your contact center provides multiple ways for customers to reach out to your business — from phone to email to chat to SMS and potentially more. While many customers still use the phone, 53% now prefer to use digital channels. Your service reps staffing these digital channels need to give accurate and relevant information, reply in a timely manner, and resolve the customer’s issue quickly. After all, customers are often in a hurry – our research finds that 78% of service reps say customers seem more rushed.

So how can AI help? With autonomous AI agents. These act as independent members of your team. They work to resolve cases, deflecting them from ever reaching a service rep, or seamlessly handing off to a rep when the inquiry is out of scope. AI agents use advanced AI technology like natural language processing (NLP) to parse what a customer has said, come up with a plan to help, and take action on that plan.

Let’s look at an example for a fictional internet company we’ll call Nation-Wide Web.

Jane is a Nation-Wide Web customer and notices an unusual charge to her bill. Jane opens up a chat on the company’s website and is soon connected to Nation-Wide Web’s autonomous AI agent, Netta.

Jane shares her concerns about her bill with Netta, the autonomous AI agent. Apparently, Jane went over her data package for the month. The AI powering Netta is able to understand Jane’s concern, and quickly review her account status and history. Next, Netta generates a personalized message that explains this charge in an empathetic tone, but also that it’s within company policy to waive the fee given the circumstances.

From there, Netta is actually able to take action to remove the charge from Jane’s account. Jane is happy she got a quick and easy solution.

Assistive AI agents act like personal assistants to your service reps. They can streamline work for reps in a myriad of ways. Here are a few:

• Case summaries and wrap-up. Before the service rep jumps into an interaction, Agentforce summarizes the conversation so far – whether that conversation occurred with an AI agent or a different service rep. Agentforce can then spin up a quick recap, so the customer doesn’t need to repeat information. After the case is resolved, Agentforce can generate a summary of the case, saving the service rep time.
• Suggested replies. Agentforce can generate context-appropriate, suggested replies to the customer, right in the flow of work in the service console. The service rep can edit the reply or simply post as suggested.
• Knowledge articles. Your knowledge base articles contain important information that is specific to your business. Customers access these articles through your self-service sites, and your reps use them to resolve cases. Now, knowledge has an additional purpose: training your AI! Connecting your AI model to trusted sources of information like your knowledge base teaches the AI to be more specific to your business and more accurate, through a process known as AI grounding. So get those knowledge articles into shape! Agentforce can help by generating the first draft of new knowledge articles for you. (Of course, always have a service rep review and edit the article.)

Let’s return to our Nation-Wide Web example, but change the scenario just a bit.

Let’s say that Nation-Wide hasn’t authorized Netta, its autonomous AI agent, to waive data use overage fees for customers. For a variety of reasons, Nation-Wide prefers that its service reps authorize fee waivers.

In this case, when Jane reaches out and explains the problem to Netta, the autonomous agent recognizes that Jane’s inquiry is out of scope. The agent lets Jane know, then hands the interaction off to a service rep.

That service rep is Katie. Before Katie jumps into the chat with Jane, Agentforce spins up a quick summary of the interaction. Katie reads the summary, and feels confident to move forward. She joins the chat. For the customer, the transition is seamless.

Katie is up to speed on the issue, and the Agentforce assistive agent is ready to help her solve it. Right in the flow of work, Katie sees a suggested reply generated by Agentforce. All Katie has to do is review the message, press send, and waive the fee from Jane’s account. In the meantime, the Agentforce reasoning engine is using the data from the message thread and the actions that Katie took in Jane’s account to generate a case summary.

After the conversation with Jane is complete, Katie can read over the proposed summary, adjust some details, and save it to the case record. Reducing after-call work helps Katie move on to help other customers faster.

Now let’s look at a different example with Nation-Wide Web to see how AI assistive agents help the service rep close out a case when a customer surfaces a completely new problem.

Nation-Wide’s customer Austin has slow internet and calls to troubleshoot. He’s connected to Tawni, a service rep who asks for his router and modem details. Tawni runs through a few common scenarios based on similar cases, but none work for Austin’s setup.

Tawni decides to try something new. She asks Austin to do a full-system reboot through the Nation-Wide Web mobile app. Tawni can focus all her attention on Austin, because Nation-Wide has incorporated voice as a digital channel into the Salesforce platform. That means Tawni gets real-time call transcription, so she doesn’t have to take notes.

Tawni’s new solution works. After the full reboot, Austin’s internet speeds are back to normal and the case is closed. Agentforce generates a case summary with all the key information, including Austin’s router and modem setup, and how Tawni solved this issue with a reboot.

Because this was a unique case, Agentforce uses the details of Tawni’s conversation with Austin and the context of Austin’s issue to generate a new knowledge article. Tawni reviews the draft, adds some extra detail and pushes it into the approval queue. And boom – AI makes knowledge management a lot easier.

Customers and service reps aren’t the only ones who benefit. Contact center AI can also bring incredible insights to help managers understand service operations performance, and improve it. With AI, you always know how your contact center is performing, in real-time. And you can quickly spot and diagnose any issues in terms of reasons for calls, negative sentiment, or long wait times.

Let’s return to our fictional internet company, Nation-Wide Web, for a final example.

It’s the first of the month, and Nation-Wide’s contact center manager, Maria, wants to get a better understanding of how her team – both AI agents and service reps — is doing so far today. Maria refills her cup of coffee, sits down in front of her console, and asks Agentforce for some call center analytics. Here are her first few questions: “How many customers are on calls right now? What’s the average hold time? What’s the channel mix at the moment?”

Agentforce quickly summarizes key contact center stats, and Maria sees that average call length time is a little up today. She wants to know why. So Maria asks Agentforce to let her know if any calls are taking longer than average. Agentforce identifies one, with a new service rep, Emilio. It’s only his second day on the job.

Maria wonders if Emilio needs help, but she wants a bit more information. She asks Agentforce to summarize Emilio’s current, ongoing interaction with the customer. The summary reveals that Emilio’s customer, Patricia, is dealing with slow internet – just like Austin recently did. However, Emilio tried the full reboot, and it hasn’t worked for Patricia. In fact, it looks like this customer has uncovered a new type of connectivity issue that Nation-Wide hasn’t seen before.

Maria realizes Emilio could probably use some help. She pings him in Slack to see if he’d like her to join the call.