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Guide to the Generative AI landscapeRevolutionize your customer interactions with generative AI

Download our guide now to learn what it takes to create the best possible experience for your brand, even with the most advanced AI models in the game.

Cover of the guide to the Generative AI application landscape
image generation examples from generative ai companies, showcasing uses of advanced generative ai models

The generative AI application landscape

Want to become a CX leader in your industry? Use large language models (LLMs) and generative AI to improve your brand’s efficiency and outshine the competition.

Generative AI and LLMs are transforming customer interactions, but they still depend on data and human influence. To make sure your generative AI applications are smarter, more efficient, and more domain-specific than ever before, you need to know the facts from fiction.

Download our playbook now to get ahead of the game.

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What you’ll learn in our guide

Training data is as important as ever

Generative AI and LLMs learn from public data sets, but don’t rely on just that generic data. To make sure your responses are domain-specific, you need to tailor your training data to your brand and customers. Our guide shows you how.

Generative AI applications aren’t action-based by default

Generative AI models can answer questions using natural language processing, but what about taking action? To create stellar customer interactions, you need to give bots the power to process returns, resolve issues, and more. Our guide reveals what’s missing and how to make it happen.

The human touch remains key

Generative AI is amazing, but when it comes to delicate situations and complex escalations, nothing beats the human touch. Our guide shows you where human agents shine in the generative AI market, from sensitive customer interactions to AI annotation.