AI, Customer Service Transformation, Large Language Model, Voice

The Game-changing Characteristics of AI Copilots for Customer Service

Taking Customer Experience to the Next Level with AI Copilots for Customer Service 

Good customer service is often a means for a company to stand out amongst its competitors, build loyalty, and retain customers. However, with over 80% of organizations (according to a recent Gartner survey) expecting to compete mainly based on customer experience, why are customers often far from satisfied by the support they receive?

Providing excellent customer service is far from easy. Agents are often overwhelmed, undertrained, and don’t necessarily have enough information to resolve a customer issue quickly and easily. At the same time, customer expectations are increasingly demanding on accuracy,  immediacy and empathy. Fear not, however.  The recent emergence and adoption of generative AI and large language models (LLMs) in customer service and contact center operations, are fueling a new paradigm for superior customer experience. 

In this blog, I’ll address the concept of “AI copilots”,  powered by large language models (LLMs) and generative AI. These AI copilots act as intelligent assistants that automate and streamline various parts of the customer service process, making it easier for agents to perform tasks more efficiently and accurately, thereby reducing the time, effort and costs involved in resolving customer issues. Their impact not only eases the pressure on contact center agents but also enhances customer experience. What’s not to love about these AI copilots!

What are AI Copilots Powered by LLMs?

AI copilots are AI-powered assistants that help customer service agents by automating different process tasks, making agents more efficient and arming them with the relevant information they need in real time. LLMs (such as GPT 4, Claude, BERT, LamBDA, and others) enable these copilots to understand, generate, and process natural language, offering contextualized, human-like responses during customer interactions. Instead of replacing agents, these AI copilots augment their capabilities by handling repetitive tasks, retrieving information, and providing real-time support, allowing agents to focus on higher-level problem-solving and customer interactions.

8 Game-changing Characteristics of AI Copilots that are Transforming Customer Service

1. AI Copilots work across Multiple Channels, including:
   • Voice: In real-time voice conversations, copilots can transcribe, analyze sentiment, and suggest responses to agents.
   • Web and Messaging: In web chats or messaging platforms, AI copilots can autonomously handle basic customer queries, escalate complex ones, and provide real-time summaries to human agents.
   • Email: Copilots can scan emails for intent, automatically suggest responses, and even handle simple inquiries without agent intervention.
2. Intent Detection and Routing: AI copilots can detect the intent behind a customer’s query—whether it’s a complaint, a request for information, a technical issue, or a transaction-related question. Automatically this allows for routing the issue to the right agent or offering appropriate self-service solutions quickly.
3. Access Relevant Knowledge: AI copilots can glean a wealth of key information and data by analyzing customer conversations in real-time across various communication channels, such as voice, chat, email, and messaging. This can be used to flag important customer issues, anomalies, or frustrations to the agent. They can also quickly search through knowledge bases to provide agents with concise and accurate answers.
4. Generate Real-time Conversation Summaries: LLMs can automatically summarize long chat or call transcripts, offering agents an overview of key points, reducing the time spent reviewing previous interactions.
5. Automating Routine Tasks, for example:
   • Document capture and verification: Automating document handling tasks like ID verification or capturing required forms.
   • Payment processing: Automating payment collections or transaction processing in the course of customer service interactions.
   • Performing administrative tasks such as generating post-call notes and summaries, documenting follow up actions, and updating customer records in backend systems of record or CRMs.
6. Anomaly Detection: AI Copilots can identify unusual patterns in customer behavior or account activity in real time, flagging potential issues.
7. Insights on Customer Sentiment: By evaluating the tone and emotion behind customer interactions, AI copilots can determine whether a customer is frustrated, satisfied, or neutral and suggest next steps.. This helps agents tailor their responses to the customer’s emotional state.
8. Perform Compliance Checks: AI copilots can also ensure that conversations or transactions follow necessary regulations, reducing legal risks. Compliance checks can be made on agent responses or conversation histories, allowing potential compliance issues to be flagged to the agent.

The Return on Investment in AI Copilots for Customer Service

Given all the characteristics of AI copilots and how they can assist customer service agents, it is clear that they are becoming a crucial part of today’s customer service organizations. Their ROI can be measured in terms of:

Self-Service Routing and Reduced Average Handle Time (AHT)

By identifying the customer’s need and classifying their intent early in the interaction, customers can be directed to the appropriate resource or agent. This helps increase opportunities for customers to self-serve without the need for human intervention. It also improves the routing of requests to the correct agents who can best address and resolve the customer’s issue, avoiding frustrating handovers and lengthy AHT.

By taking over tasks such as knowledge retrieval and document processing and highlighting key information in conversation summaries, AI copilots drastically reduce the time it takes agents to respond to queries, thereby reducing average handle time (AHT). 

Improve First-Call Resolution (FCR) Rates

Since routine inquiries can be handled faster or even autonomously, costs are lowered, and agents are more available for more complex issues. This also translates to improved first-call resolution (FCR) rates, which enhances customer satisfaction and reduces operational costs.

Scaling Customer Service without Staff Increases

AI copilots can handle high volumes of requests, allowing businesses to scale customer service without proportional increases in staffing. This allows contact centers to meet peaks in demand without necessarily having to add more agents. 

Enhanced Customer Experience

AI copilots for customer service, powered by generative AI and LLMs, can handle a variety of tasks across different communication channels—voice, chat, messaging, and email—ensuring that customers receive consistent, fast, and relevant service no matter how they engage. Real-time support ensures faster resolutions, better personalization, and improved overall customer experience.