From scripted bots to generative bots and how to stay in control
Written by
Veena Nair, CEO
Post date
9 July 2024
Starting as simple, scripted bots designed to handle basic customer inquiries, they have transformed into sophisticated generative bots powered by advanced AI. These generative bots, often driven by large language models (LLMs), can understand context, generate human-like responses, and handle complex interactions. However, with greater power comes the need for greater control. After LLMs and GPTs do hallucinate, can be jailbroken and can make grave errors unacceptable in customer engagement.
Scripted bots, also known as rule-based bots, follow predefined rules and scripts to respond to user inputs. They excel in handling straightforward and repetitive tasks, such as answering FAQs or guiding users through simple processes. However, their capabilities are limited, as they cannot handle unexpected queries or understand context beyond their programmed rules.
Losing control to the generative bot was the hardest part of moving to generative bots.
Financial Services Customer Success ExecGenerative bots, like Oro, on the other hand, leverage AI and machine learning to generate responses based on context and user inputs. These bots can understand natural language, provide relevant and personalized responses, and adapt to a wide range of scenarios. They offer a more dynamic and interactive experience, which significantly enhances customer engagement.
One approach that's frequently talked about is the "kitchen sink approach". It refers to deploying a comprehensive, all-encompassing strategy to address customer needs and inquiries.
This approach involves utilizing a variety of tools, technologies, and methods to ensure that customers receive the best possible support. The term comes from the expression "everything but the kitchen sink," implying that nothing is left out.
The kitchen sink approach to generative bots
The "kitchen sink approach" to customer service, which involves using every available tool and method to meet customer needs, can be particularly effective when applied to generative AI bots. These advanced bots, powered by AI and large language models, are capable of understanding and generating human-like responses, making them a crucial component of a comprehensive customer service strategy.
- Modularity and Scalability
- Data Management
- User-Centric Design
- Designing the right Tools and Tasks
Integrating generative AI bots into a kitchen sink approach for customer service involves adhering to principles of modularity, robust data management, continuous learning, user-centric design, seamless human integration, performance monitoring, security, and flexibility.