The Pros and Cons of Using ChatGPT in Zendesk

In today's rapidly evolving customer service landscape, AI and chatbots have revolutionized the way businesses interact with their customers. One of the prominent players in this field is ChatGPT, a sophisticated language model developed by OpenAI. Many businesses have integrated ChatGPT into their Zendesk platforms to enhance customer support. In this blog post, we will delve into the pros and cons of using ChatGPT in Zendesk, exploring its capabilities and limitations. 

Pros of Using ChatGPT in Zendesk

1. Quick Responses

ChatGPT excels in providing swift responses to common customer queries. For instance, routine inquiries like order tracking, account information, and basic troubleshooting can be addressed promptly without human intervention.

2. 24/7 Availability

ChatGPT ensures round-the-clock customer service availability. This is particularly valuable for global businesses that cater to customers in different time zones, ensuring that customers receive assistance whenever they need it.

3. Scalability

ChatGPT can handle a large volume of customer inquiries simultaneously, making it an ideal solution for businesses experiencing fluctuating levels of customer interactions. This helps in reducing response time and preventing long customer queues.

4. Consistency

By following predefined guidelines, ChatGPT provides consistent responses to similar queries. This consistency helps in maintaining the brand's tone and messaging across various customer interactions.

Cons of Using ChatGPT in Zendesk

1. Limited Context Understanding

ChatGPT struggles with understanding complex or nuanced inquiries that require deep context understanding. It might misinterpret customer intent and provide inaccurate or irrelevant responses.

2. Lack of Empathy

While ChatGPT can mimic empathy to a certain extent, it lacks the genuine emotional understanding that humans possess. In situations requiring emotional support, ChatGPT's responses might come across as robotic.

3. Inability to Handle Unique Scenarios

Uncommon or highly specific scenarios might be challenging for ChatGPT to address accurately. It can't draw from personal experiences or unique insights, making it less suitable for handling specialized issues.

4. Potential for Miscommunication

ChatGPT might inadvertently generate responses that customers could misinterpret or find confusing, leading to frustration or dissatisfaction.

Introducing Stylo: Enhancing Zendesk with Intelligent Inferences

Stylo takes the integration of ChatGPT in Zendesk a step further by employing an intermediary language model. Unlike systems that directly connect Zendesk to ChatGPT, Stylo's approach involves using its own language model to analyze customer tickets before engaging ChatGPT. This intermediary step allows Stylo to make intelligent inferences about the ticket content.

For instance, consider a customer's ticket that delves into specific product details. In this scenario, Stylo's intermediary model shines by swiftly identifying these details and conveying them to ChatGPT. Armed with this contextual information, ChatGPT can then provide responses that are finely tuned to the product-related query. This strategic approach minimizes any potential of ChatGPT generating generic responses that fall short of addressing the precise nuances of the customer's query.

Better still, Stylo allows for a human customer support agent to provide input, in the form of a short bit of text, which can formulate the basis for what will be passed from Stylo’s model to ChatGPT. This allows for better understanding and handling of unique or new scenarios, because the understanding of the human looking at the ticket is being taken into account when generating the reply. 


Integrating ChatGPT into Zendesk offers numerous advantages in terms of speed, availability, scalability, and consistency. However, it also comes with limitations related to context understanding, empathy, and handling unique scenarios. Stylo's innovative approach of utilizing an intermediary language model, and empowering human customer support agents to include what they know about the ticket, addresses these limitations. This leads to more tailored and effective customer interactions, ultimately enhancing the overall customer support experience.