Generative AI Use Cases In AI Contact Centers
The capabilities of generative AI hold the key to contact center transformations like never seen before. Like a comprehensive upscaling of its scope, advanced AI models can be trained to produce text, translate language, craft diverse forms of creative content, and provide insightful responses to customer inquiries. The most significant impact is the ability to deliver personalization at scale, closely followed by the opportunity to leverage call data for business insights.
Here are a few significant use cases of generative AI in contact centers:
Virtual Agents or Chatbots
Use generative AI to create intelligent virtual agents or chatbots to handle routine customer inquiries, such as account balance checks, password resets, and FAQs. These virtual agents can engage in natural language conversations and provide 24/7 support, reducing the workload on human agents.
Automated Email Responses
Generative AI can draft personalized email responses to customer inquiries, ensuring timely and accurate replies. It can analyze the content of incoming emails and generate contextually relevant responses, practically automating the personalization of CX.
Voice Assistants
Implement voice-based generative AI assistants that can interact with customers over the phone. These assistants can provide information, process transactions, and offer troubleshooting support through natural language understanding and generation.
Multi-Language Support
Generative AI can assist in providing customer support in multiple languages, eliminating the need for language-specific agents. Translate customer inquiries and generate responses in the customer's preferred language. Multilingual support is not only convenient but also unlocks the possibility to target a much wider user base.
Quality Assurance and Compliance
Use generative AI to monitor and transcribe customer-agent interactions to ensure compliance with regulations and adherence to quality standards. Automate the identification of compliance violations and provide feedback to agents in real-time. Improving pitch adherence also ensures that your intended communication is delivered in a way you expect.
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Knowledge Base Creation and Maintenance
Automate the creation and maintenance of knowledge bases by generating FAQs, troubleshooting guides, and instructional content based on customer inquiries and agent responses. Knowledge bases are an important self-service aspect in the modern-day customer experience landscape.
Sentiment Analysis
Implement sentiment analysis powered by generative AI to gauge customer emotions during interactions. Use this data to identify and address issues proactively and provide personalized support. By implementing sentiment analysis at scale, your contact center can start objectively assessing agent-client interactions.
Call Summarization
Automatically generate summaries of customer-agent phone calls, making it easier to review and extract insights from these interactions. These summaries are valuable for long-term improvements in call quality and identifying positive and negative communication patterns.
Appointment Scheduling
Generative AI can assist in scheduling appointments or bookings, reducing the workload on human agents. It can send reminders and confirmations to customers. Freeing customers from such manual processes is good for both customer autonomy and resource utilization.
Script Generation for Agents
Generate scripts or suggested responses for human agents to ensure consistent and accurate customer communication. Assist agents in real-time by offering recommendations during calls or chats. Combined with Gen AI's ability to understand content with context, these scripts can continually improve with changing customer expectations.
To learn more ways through which Generative AI can enhance your contact center capabilities, check out our detailed blog: