Since Open AI launched ChatGPT almost a year ago, companies from every industry have begun to explore how generative AI can enhance the efficiency and effectiveness of their customer experience offering. Although automation and other technologies have evolved to support customer interactions, generative AI and large language models (LLM) represent a ground breaking step forward.
What is generative AI?
Generative AI is a branch of artificial intelligence that can process vast amounts of data to create an entirely new output. It is designed to generate content, such as text, images, music, or even videos. It does this by learning from large datasets of existing content and then using that knowledge to create new, original content.
Why use generative AI in customer service?
Customers found bot-to-human interactions frustrating, so business executives resisted implementing automation solutions in the past. With sloppy, rules-based first-generation bots, this was a valid concern. But technology has advanced significantly since then.
The increased capacity of Gen AI chatbots to engage with humans simply and naturally makes using this technology in a customer-facing environment a no-brainer. Generative AI provides faster, better support, from improving the conversational experience to supporting agents with suggested responses.
How to use generative AI in customer service
Generative AI can be used in customer service to enhance various aspects of the customer experience. Let’s take a look at five examples.
- Automated Chatbots: Generative AI can power chatbots that can handle routine customer inquiries and provide quick responses 24/7. These chatbots can understand natural language and generate human-like responses to common questions, helping customers find information or resolve issues without human intervention.
- Personalized Responses: Generative AI can analyze customer data to personalize responses. For example, it can generate responses tailored to a customer’s purchase history, preferences, or previous interactions, making the customer feel heard and valued.
- Multi-language Support: Generative AI can be trained to understand and respond in multiple languages, enabling businesses to provide customer support to a global audience without the need for a large team of multilingual agents.
- Email Responses: AI-powered email response systems can generate personalized email responses to customer inquiries. This is particularly useful for handling a high volume of customer emails efficiently.
- Quality Assurance: AI can be used to review and suggest improvements to customer service responses generated by human agents. This can help maintain consistency and quality in customer interactions.
Conclusion
While the overall outcome of welcoming Gen AI to the new era of customer service is positive, it is essential to ensure that AI-generated responses are ethical and align with your company’s values and guidelines.
It is equally important to understand that while AI can handle many tasks, it’s still necessary to have human agents available for complex or sensitive customer interactions.
And lastly, we must understand that like any other technology, Generative AI requires continuous maintenance, so regularly updating and training your AI systems to improve their accuracy and relevance in customer interactions.
Generative AI has the potential to significantly enhance customer service by providing efficient, consistent, and personalized support. However, it should be used thoughtfully and in conjunction with human agents to deliver the best possible customer experience.
