# Generative AI in Enterprise Contact Centers Authors name: [Miriam Schröder](/content/blog/author/miriam-schroeder/index.html) August 16, 2024 --- Generative AI in Enterprise Contact Centers: A Complete Guide ## What Is Generative AI in Contact Centers? Generative AI describes a computer technology that can read and generate [natural language](/content/platform/cognigy-nlu/index.html). It can both discriminate and generate, meaning it can understand text, speech, imagery, and other forms of media to interpret intent, context, and sentiment. As the name suggests, Generative AI can _generate_ content in an array of different formats based on user prompts or automated criteria. In a contact center, Generative AI supports agents and customers with many of the more laborious or mundane tasks that involve text or speech. When combined with Conversational AI, the two act as a layer that sits atop your existing processes and listens, reads, and learns from all language-based activities. ### How Does Generative AI in Contact Centers Work? Before we go any further, we’re not suggesting you use Generative AI on its own in your contact center. Instead, you need a wider AI solution that incorporates Generative AI with other tech such as Conversational AI – like we do with our [Cognigy.AI](/content/platform/cognigy-ai/index.html) platform. #### How Generative AI works agent-side - The AI monitors agent conversations on voice and digital channels generating automatic transcripts and call logs. - Generative AI can interpret customer requests and create context-relevant information to aid the agent during a call. - The AI can interpret customer sentiment for each call and perform instant sentiment analysis to give agents deeper insight into customer satisfaction. - Contact centers can vastly improve chatbots and other mundane support processes by allowing Gen AI to create more natural and satisfactory responses. - Generative AI can improve live translation for agents during calls, allowing for [multilingual](/content/resources/showcases/agent-assistance-multilingual-voices/index.html) contact centers without the inflated costs of human translation. #### How Gen AI works for customers - Generative AI is an invisible capability that analyzes all customer input and creates responses designed to resolve queries, speed up mundane processes, or accelerate call priority. - By understanding customer language, the AI also empowers customers to quickly progress through self-service processes by following context-driven prompts. - The AI can identify when a customer’s requirements need to be escalated to an agent, helping to improve satisfactory outcomes and reduce waiting times. - Generative AI can also present call context and summaries to agents at the start of a call, meaning customers don’t need to repeat themselves and can solve their problems more effectively. ## Benefits of Generative AI in Contact Centers ### Saves Time One of the clearest, direct advantages of Generative AI in a contact center is the time-saving associated with call logs and other laborious text-driven tasks. Rather than forcing an agent to create a summary after each call, the AI will automatically create one in your predefined format. Call logs are only one such example – any text/voice-based task can leverage Generative AI to cut tasks from minutes to seconds. ### Provides Next-Gen Agent Assist Agents have nothing to fear from AI – it’s there to help them. Generative AI in combination with Conversational AI can provide cutting-edge agent support by understanding the context of a customer’s call or query. It can then automatically display the relevant supporting information, such as a customer’s return receipt or order information, all without the agent having to take any manual actions. ### Elevates voice and chat experiences Generative AI helps support smoother interactions, whether through text chat or voice, by building more natural responses to make customers feel more engaged. ### Accelerates bot building Chatbots existed long before AI, but the capabilities Generative AI brings to bot building are hard to ignore. Gone are the days of manually plotting out every process to create user flows. Generative AI can model processes in seconds and generate a variety of responses and text prompts to engage users. ### Improves Satisfactory Outcomes By cutting down on laborious tasks such as creating call summaries, improving agent support to minimize friction during calls, and supporting better customer engagement by voice or text, Generative AI helps improve overall results for customers and agents alike. Less time wasted, more queries resolved, and far happier customers. ## Generative AI Use Cases in Contact Centers ### Self-service One of the most compelling areas to use Generative AI is in improving customer [self-service](/content/solutions/digital-chat-ai-agents/index.html). Generative AI can use your existing call logs for example, or customer data and then used to build more efficient ChatBots and Virtual Agents. ### Live Agent Support Enhance your agents' capabilities by using AI-driven [Agent Copilot](/content/solutions/agent-assist/index.html). The AI can understand customer needs and generate relevant solutions or replies. ### Translation Use Generative AI to support agents in real-time with responses created in the customer’s language, avoiding the high costs of real human translation. ### Upselling Generative AI can improve successful [sales](/content/solutions/ai-agents-sales-marketing/index.html) by equipping agents with a customer’s existing information to create specific upsell opportunities. ### Reporting Generative AI, when combined with a Speech-to-Text (STT) service, can analyze sentiment or patterns from call transcriptions to improve reporting and insights into agent performance and customer satisfaction metrics. ## Best Practices for Generative AI in Contact Centers ### Know Its Limitations Generative AI needs to be part of a wider platform to function effectively and help your agents and customers. It must also be developed and deployed around your specific team’s processes and challenges. ### Avoid AI Mishaps Some Generative AI tools can be prone to misuse or may generate nonsense responses. Use platforms that mitigate risks. ### Create Real-World Use Cases Before implementing Generative AI, define use cases within your contact center to ensure the benefits outweigh the costs. ### Understand Your Privacy Requirements Data privacy is crucial. Public-facing tools often don’t offer the right level of security to protect sensitive user information. ## Frequently Asked Questions ### Will generative AI replace customer service? No – Generative AI is not a replacement for human agents. Instead, it supports agents during calls. ### Can Generative AI Answer Phone Calls? On its own, Generative AI cannot answer calls but can assist during them by generating text-based responses. ### What Is the Difference Between Generative AI and Conversational AI? Generative AI is a back-end tool that generates language, while Conversational AI is the customer-facing interface.