Conversational AI for World Class Monitoring

By PeterP.Giacalone,President,GiacaloneAssociates

As monitoring centers continue to evolve, understanding some essential technologies that are improving SLA’s is helpful to understand. Years ago, the industry experienced DTMF IVR technology. This technology presented automated interactions through DTMF telephone tones. Years later adoption of Natural Language Speech IVR’s improved the experience. This was a leap as it was all voice driven rather than touch tone. Although NLS IVR works well, it is narrowly structured and communications need to fall within that structure. It doesn’t have the ability to think or deal with anomalies or questions outside the tight structure. Enter – Conversational AI. This allows for true conversation and responses and actions based on many elements within or external from the monitoring center core.

Natural Language IVR systems rely on pre-programmed scripts to understand and respond to user queries within the monitoring automation systems. Although NLS IVR offer an intuitive interface, their capabilities are often limited to a predefined set of commands and responses. Users may encounter difficulties if their queries fall outside the system’s programmed parameters, leading to frustration and potential disengagement.

Conversational AI presents great progress. Powered by machine learning and natural language processing algorithms, Conversational AI systems possess the ability to understand, interpret, and respond to user inquiries in a more dynamic and contextually relevant manner.

Different than NLS IVR, Conversational AI learns from each interaction. This allows for more personalized interactions, enhancing the overall customer experience. Moreover, Conversational AI platforms can integrate with various data sources within and outside of the central station monitoring center environment, enabling access to pertinent information and provide more comprehensive assistance to users.

Natural Language IVR systems excel in handling high volumes of routine inquiries with minimal human intervention. By guiding users through structured menus, they can swiftly address common issues, reducing wait times and improving overall operational efficiency.

Conversational AI, offers superior accuracy and flexibility. Its ability to understand natural language nuances enables it to handle complex queries to fully resolve customer interactions at scale similar to a live agent, and adapt to shifting contexts seamlessly without the requirement of frustrating menus. As a result, users are more likely to receive accurate and relevant assistance, leading Conversational AI continued on page 23