According to Gartner, “Customer service and support technology (CST) vendors are adding new, Generative-AI-powered features to their solutions. This first wave of features using large language models (LLMs), a subset of Generative AI, will improve:

• Employee productivity by reducing average handle times (AHT)
• The quality and accuracy of interactions by creating reusable knowledge content
• Self-service containment rates through better conversational virtual agents.” 

To safely and swiftly capitalize on these cutting-edge capabilities, it's crucial to stay abreast of CST vendor roadmaps. 

In the world of Generative AI applications, ChatGPT has blazed the trail, sparking immense interest and curiosity in leveraging the technology of foundational LLMs for customer service use cases.

While the buzz around ChatGPT is certainly exciting, the recent advancements in LLM capabilities mark a significant turning point in CST applications. Building enterprise-grade applications powered by Generative AI might be challenging for many organizations. That's why a blended approach, incorporating existing AI methods and other software techniques alongside Generative AI, will deliver the most comprehensive and effective solutions.

As a leader in your organization, it's essential to evaluate the benefits, risks, and costs associated with deploying LLM-based applications like ChatGPT.