AI in the Contact Center: Start with your Agent Experience
All innovations—whether they’re for individual or business consumption—go through a natural adoption lifecycle. Innovators and early adopters dive headfirst into the new technology while the majority and laggards sit by the side to see how things shake out.
This has proven time and again in the contact center space—in the last two decades with the move to the cloud and today with the adoption of artificial intelligence.
AI contact centers use machine learning and language processing to streamline the customer service experience. AI-powered processes can provide instant responses and real-time call assistance, providing appropriate responses to expedite resolutions. Yet, it’s unsurprising that DMG Consulting recently found that while 28% of contact centers adopted AI in 2023 and 37.1% plan to in 2024, 25.9% still have no plans to do so.
Nonetheless, many contact centers have laid the foundation for adopting AI-powered technologies and are ready to dip their toes into the AI pool, but find themselves asking, “Where do I start?”
I had the privilege of hosting a recent fireside chat with Sheila McGee-Smith, President and Principal Analyst of McGee-Smith Analytics, and Sharpen’s CEO, Charlie Newark-French, where they discussed how contact centers can prepare their CX for the AI future.
Both agreed on one point: You should start by incorporating usable AI into your agent experience (AX).
Let’s explore why.
What do we mean by usable AI?
Before we jump into the agent experience, lay some groundwork: What is usable AI?
In simplest terms, it’s using AI where it makes sense. It shouldn’t be hard to get value out of AI. We should focus on the value it can inherently bring and should never use AI just for the sake of using AI.
Usable AI in the contact center should be simple for both leaders and agents to use. You can customize it to fit any industry and cater to specific requirements.
Agents aren’t going anywhere
Despite initial fears, it’s quickly become clear that agents aren’t going anywhere. On the contrary, their roles are becoming increasingly critical. As customer self-service adoption continues to increase, the contacts that do reach agents are more complex and sensitive than ever. These contacts are more intellectually rigorous and require human problem-solving and critical thinking to resolve.
During the fireside chat, an attendee asked Sheila and Charlie the following question:
“How long before the agent is AI?”
Their answer: for 100% of use cases and scenarios, it won’t happen soon, if ever.
First, change is slow—even if the capabilities were there to support all use cases, it would take years or decades for organizations to adopt to the point of agent replacement. Additionally, though generative AI can and should be the agent in some scenarios—think conversational IVR—those are only a sliver of scenarios handled by contact centers. Instead of an “either-or” mentality, leaders should think of contact center AI as a human-led, “better-together” story.
Charlie referenced an interesting example to help paint this picture. Years ago, when radiologists began using AI to help them more efficiently and accurately detect cancers, some wondered if AI would replace radiologists. However, today, there are more radiologists in the United States than there were then, and the story has shifted from “When will AI replace radiologists?” to “When will radiologists who use AI replace radiologists who don’t?”
The same can be said for contact center agents. Contact centers that use AI to improve agent efficiency and engagement—and, in turn, their customer experience—will outperform those that don’t and eventually make the latter a thing of the past.
AX is the safest—and easiest—place to start
Anytime organizations introduce new technologies into their customer experience, there are learning curves and bumps in the road. Some recent generative AI concerns have been related to hallucinations, autonomy, and deepfakes. Think rogue chatbots saying inappropriate or off-the-wall things to customers.
Though organizations are successfully incorporating generative AI into their customer-facing interactions with safety guardrails, incorporating generative AI into your agent experience first is a safer choice for most.
First, you keep that human in the loop, reducing the potential risk. By keeping the agent in the loop, you can get many benefits without some of those possible concerns. A bad, one-off agent experience has lower negative consequences than a bad customer experience. If your agent has a rogue AI interaction, it’s still not great, but it’s better than if it happens to your customer!
Secondly, the agent experience offers enormous efficiency gains. Internal agent processes often cause bottlenecks, inefficiencies, and recurring issues in contact centers.
According to Gartner research, 30% of reps will automate a portion of their jobs by 2026. From using automated quick replies in text interactions to sophisticated contact wrap-up/summarization capabilities and predictive interaction guidance based on the customer journey, usable AI and automation can eliminate time-consuming, mundane agent tasks.
And, of course, by enabling your call center agents to do their jobs better and more efficiently, you’ll experience better overall business outcomes—more revenue, lower costs, higher customer satisfaction, faster handle times, and the list goes on.
AI in your AX: Use Cases
The opportunities for incorporating AI into the agent experience are wide and deep. Here are a few examples we’re seeing in contact centers today.
AI-powered agent assistants
Agent assistants, from agent scripts to screen pops, have been discussed for years. Still, AI makes them much more powerful, enabling agents to work with more precision and efficiency before, during, and after each interaction.
One such way is empowering agents with the right context at the right time through AI-powered interaction context. Most contact centers pop customer profiles to agents when a contact is delivered, but it’s usually an encyclopedia of that customer’s life—which isn’t particularly helpful.
However, AI-powered interaction context can surface a snippet with the most relevant information about the customer’s journey and relationship with your company to the agent. For example, this customer is trying to solve X problem; they’ve already reached out about this issue twice, and their tone is tense. This helps ensure that agents can empathetically jump right into the conversation—without the customer needing to repeat themselves or any downtime for digging.
Another way AI can help is by delivering agents the right answers at the right time. Generative AI can enable agents to ask questions using natural language to get immediate, relevant answers during customer interactions.
This is superior to today’s common practice of popping a knowledge base article and the agent skimming it to get the answer—or worse yet, requiring the agent to manually search for the knowledge base article.
For example, let’s say an agent is chatting with a customer who has a very specific tax-related question about their investment account. The agent could ask, “Are employer contributions to this plan tax deductible?” or “What’s the maximum contribution allowable to a SEP-IRA in 2024 tax year?” and get an immediate response. Now, an answer that could have taken four to five minutes to find is surfaced in seconds, improving the agent and customer experience and reducing handle time.
AI can also empower agents after the interaction with smart, automated interaction summarization. Rather than spending minutes on after-contact work (ACW) and scrambling to ensure they don’t forget anything that transpired during the interaction, AI can automatically transcribe and summarize the most important points and next steps, presenting them to the agent for validation, edits, and saving to their customer profile. This accelerates ACW, helps ensure nothing is missed, and enables the agent to confidently and quickly move on to their next interaction.
AI-powered knowledge management
AI-powered agent assistants empower agents with immediate answers in the moment of need, but AI can also improve contact center knowledge management to ensure that those answers exist in the first place.
Many contact centers struggle to identify where to focus their knowledge management efforts and curate their content for usable consumption. Today, large language models can index contact center conversations and data to create the sources that agent assistants can query—reducing the work required to get started and enabling the adoption of AI-powered agent assistance.
AI-powered agent onboarding
Today’s contact center is fast-paced and heavy on remote work. Gone are the days of classroom agent onboarding that lasted weeks to months. Nobody has time for that or wants to sit through it, especially the younger generations joining the contact center.
AI can tremendously accelerate agent onboarding time. Between AI-powered assistants and automation to guide them through interactions and workflows, we see agents handling customer contacts within hours. This matches the modern learn-by-doing expectations of younger employees and enables agents to handle interactions immediately rather than needing extensive training.
Supercharge your agents with AI and Sharpen
Adopting contact center AI isn’t a matter of “if” but “when” and “where to start.” Focusing on your agent experience first is a safe yet impactful place to begin. And remember—AI adoption is a journey, and your agent experience is just the starting point.
The Sharpen team will be with you every step of the way to help you implement new AI-powered capabilities and reap their full benefits to transform your contact center.
Gain more practical insights on using AI in your contact center. Meet with a Sharpen expert today!