Customer service is most effective when it solves problems quickly and without a fuss. If someone comes to the support team with an issue—concerns about a bank account, a healthcare portal, or a mysterious internet outage—that customer wants smart, fast, customized answers. And service agents want to deliver.
That’s not always easy. As technologies grow more complex, finding quick solutions to problems can sometimes be its own problem. Our 2023 Work Trend Index report found that 62 percent of people spend too much time scouring for information in their workday. Every service agent is under constant pressure to dig for answers while remaining friendly, calm, and focused—even when a customer is losing their cool.
Fortunately, generative AI and other technology can lighten the load and help service agents meet the growing demands of their job. Here’s how new capabilities—from smarter chatbots to AI-powered task assistance to real-time recommendations—can give your team’s intelligence a boost, drive modernization, and improve processes across the board. Think of these advances as support agents for your support agents.
Helping Clients Help Themselves
Frustrated by automated prompt trees, customers sometimes mash the zero key or repeatedly shout “Agent!” into the phone until one shows up on the line, with the customer already frustrated and angry. But first-contact experiences—the initial step in your customer service journey—don’t have to be this way.
The challenge: Your team wants speedy resolutions for customers, and that means quickly identifying who’s calling, what’s wrong, and how to fix it. Not all issues—whether surfaced through voice, email, text, chat, or other channel—require an actual human agent. But how can you understand what the customer needs and make it a smooth transaction so they don’t feel like they’re stuck in a maze of menu options?
The solution: AI-powered voice and chat tools use conversational language to authenticate callers and suss out thousands of customer intents. (“Oh, you’re calling to refill a prescription? Let me help.”) Those assists make interactions easier and more satisfying for customers. By providing clear information and internal documents, like knowledge base articles or videos, intelligent chatbots can address routine and complex inquiries automatically, cutting down customer wait times.
“With new chatbots, in a few very quick cycles, we get to, ‘Based on where you are and what you’ve said, we think this is the problem you’re having, and here’s how to solve it,” says Geoff Maxwell, General Manager for Microsoft’s Customer and Digital Experience.
When customers have access to more intelligent chatbots, it gives human agents more time and energy to focus on cases that actually need their attention and expertise.
Meeting Customers Where They Are
Chatbots can shoulder some of the burden, but they can’t handle every call. When a complex query, sensitive issue, or high-value transaction comes in, AI can smooth the transition to that human support the customer requires.
The challenge: For someone looking for help, nothing is more frustrating than being bumped to a new level of care only to have to rehash what they already typed in or told a chatbot. Whether dealing with a live human or an AI assistant, callers want to pick up where any previous contact left off. And they want to keep their personal details safe.
The solution: Intelligent routing is a smarter way to avoid the dreaded, “Tell me again why you’re calling?” Based on the emotions and needs detected in a natural speech conversation, sentiment-based routing finds the right agent for the right call. (Yes, AI can sniff out when someone needs to speak with a manager.) Meanwhile, advanced biometric authentication in tools like Nuance Gatekeeper can scan for fraud based on how callers sound, what they say, and how they act.
As the agent takes over the call, AI-powered Copilot in Dynamics 365 Customer Service can provide a concise recap of what’s been shared already, including the person’s name, reason for the call, and case history. Agents can respond more quickly, without digging for information, and, most importantly, the customer feels seen.
Showing Them You Know Them
As ambassadors for a brand, agents have to know their company’s products and services. But they need to know their customers too. How can they bring more know-how and personalization to each call?
The challenge: An agent has been matched with a customer to detail the finer points of a mortgage application, let’s say, or check up on the details of their medical insurance. Now it’s time to tailor their recommendations and maybe even predict what the customer needs before they know to ask for it.
The solution: Personalize care with a 360-degree view of a customer on the agent’s screen.
Consider sentiment analysis, which helps agents understand how customers feel in real time. Say an agent is going over optional features with a customer who’s dissatisfied with the credit card they’re using. AI can follow the conversation or live chat session using natural language cues to flag the customer’s sentiment as they review different options together. That helps an agent redirect the conversation to the products most relevant to the customer.
AI takes customer service deeper too: Copilot can offer you proactive recommendations, knowledge base articles and documents, or suggest relevant apps and offers. It can also give contextual responses, offer quick case summaries, or draft emails based on what’s been discussed in the interaction. For tricky cases, an agent can call on colleagues to “swarm” and gather a virtual cluster of experts until they find a resolution.
When customers get in and out quickly, agents can help more people—and their jobs feel more rewarding too.
Making the Process Better for Next Time
AI learns as it goes, and that means the support experience is constantly improving and innovating—for customers, for businesses, and for your team.
The challenge: As AI and better technology help agents with specific tasks, how can your organization scale what it’s learning and build smarter processes?
The solution: Using AI in customer support doesn’t just make individual calls go faster or result in more five-star agent ratings. It does those things, yes, but something bigger is at work. By collecting and analyzing data, and putting those learnings into practice across all your calls and channels, you create a better system overall.
Agent coaching can identify best practices and replicate them throughout your contact center, reducing training time. Resolution insights, backlog trends, and historical comparisons can tackle inefficiencies in your system and identify opportunities for automation and improvement.
Take the example of a service agent who needs to ask for supervisor approval a few times a day to get deeper access to a customer case file. Using tools for process mining, you see that each manual approval slows productivity, leaving both the customer and the agent feeling discouraged.
“If you grant the agent three approvals a day without asking, it not only empowers the agent, it improves morale and supercharges the customer experience, without much of a risk,” Maxwell says. In short, the organization can learn from an experience, automatically, so agents aren’t jumping through the same hoops each time.
Takeaway
Generative AI and other new tools are not just about efficiency; they’re the architecture of an expanding knowledge bank that’s transforming the experiences of customers and agents alike. AI helps organizations streamline service operations, improve collaboration, and boost productivity. Agents can deliver more personalized service that eases customers’ hassles—and that can prevent frustrations on their end too.
