Generative AI in Enterprise Contact Centers: A Complete Guide | Cognigy

Generative AI in Enterprise Contact Centers

Authors name: Miriam Schröder 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. 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 platform.

How Generative AI works agent-side

How Gen AI works for customers

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. 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. 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 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.