10 Ways Generative AI Can Improve Contact Centers

Generative AI can be used to develop your contact center operations and approach to providing industry-leading service.

Contact Centers have promising applications for generative AI.

Now that AI is more sophisticated, businesses are exploring potential applications for using AI for CX. Contact Centers have some of the most promising opportunities for generative AI. And most of the applications are early-horizon opportunities. That means:

  • Large amounts of data are readily available to train new AI models
  • The use cases align with existing AI applications and capabilities
  • The technology and data dependencies are well-understood
  • The risk is relatively low, even though the application is customer-facing. Business practices and rules are already in place to govern how customer data is used during interactions

Contact Center Use Cases

Contact Centers are already using AI and machine learning to automate and improve performance. So, there’s not much to lose by experimenting with generative AI—and so much to gain.

We see 10 no-regrets uses cases for generative AI in contact centers.

  1. Advanced knowledge management. Generative AI can use semantic search and text generation to empower human agents with better answers, faster. It can sift through policies, products, services, and customer history on the spot. With more information, even inexperienced agents can increase first-call resolutions.
  1. Script recommendation engines. Generative AI can provide real time messaging support to agents. It can use customer history, call trends, and other cues to generate scripts that connect with customers and create positive interactions with your brand.

  2. Interaction summarization. After a phone call or chat, generative AI can summarize the interaction and log the event in the company’s CRM. When summarization is automated, contact logs become more accurate, timely, and comprehensive—which the AI can use to learn and improve.

  3. Outbound follow up and sales. AI-generated contact summaries can also close the loop with customers. Since generative AI incorporates notes and phrases from the interaction, customers get a personal response—but faster than humanly possible.

  4. Chatbots. Right now, most chatbots are limited to information that resides on a company’s website or CRM. Generative tools will be able to gather information from more sources and modalities. That enables them to respond appropriately and naturally to more complex questions and issues. Modern chatbots can even adapt the formality or tone of their response to match the customers’.
  1. Voice bots. Right now, voice bots are commonly used to answer routine questions or relay specific information, like store hours or account balances. That hasn’t taken a lot off agents’ call logs—until now. Modern voice bots can synthesize audio—taking note of a customer’s tone, volume, and linguistics—and respond naturally to more customer issues.
  1. Predictive NPS. During a call, generative AI can evaluate the interaction and ascribe it a sentiment or NPS score. Agents can adjust their approach on the spot based on the current “mood.” Predictive scores can also be used to identify customer experience (CX) issues before they show up as bad reviews or performance dips.
  1. Quality assurance and compliance analysis. Today’s AI tools can ingest transcripts to verify interactions are compliant and meet quality standards. And they’re fast, so issues are caught and remediated quickly.
  1. Agent coaching. Each agent will be able to get real-time, personalized coaching, all the time. For example, a pop up can alert agents if they’re interrupting a customer too much. Generative AI can be trained to analyze tone of voice, cadence, and other conversational cues that prior generations of AI didn’t leverage as data. This also has implications for helping track specific customer service KPIs for your agents.

  2. Predictive routing. This is way better than “Press 1 for English…”. Advanced routing algorithms can match customers to specific agents based on call history and an agent’s experience, personality, and communication style.

The Payoff for CX

These use cases allow companies to scale their service operations. They can serve more customers, more efficiently, and with better resolutions. While those sound like company perks, the real payoff is the impact on CX.

With generative AI in your contact center, customers get faster and more accurate responses. And they can interact with your company through more channels, around the clock, on their terms—and receive a consistent level of quality.

Ready to give it a try? Contact NPSx to learn how generative AI can give your contact center a CX advantage.

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About the Author

Evan Brennan-Johnson

Communications Manager, NPSx | Evan manages external communications and engagement, helping business leaders develop their capabilities and drive customer experience in the third wave of CX. He loves roller coasters, yoga, and traveling the globe.