Getting an artificial intelligent conversation going for your organisation is a significant first step on the path of implementing better user experience, increasing your sales and decreasing your cost. However, doing it at scale is a different kettle of fish.
Imagine having a conversational front office talking through a hand full of channels to your customers while a marketing effort is undertaken to promote a Christmas offer. This offer then has to be included in your conversational technology for a limited amount of time without interrupting the other conversations. This example causes all sorts of issues.
Incorporating temporary technology
When you have a conversational AI, and you need to, for various reasons, temporarily change the content of it, common enterprise software management issues start to play a role. Keeping track of your changes and version to retain old behaviour while easily making changes is just one of them. An excellent conversational AI platform enables you to test your CAI and route users, even temporarily, to another engine allowing you to incorporate these changes with ease.
IT Function separation
The big monolithic system is no longer the best solution to developing large-scale systems. These days it is more collaboration between methods and functions stitched together by sophisticated routing solutions. Your conversational AI architecture will look similar when growing. Most AI development platforms seem to support the whole chain at the expense of your flexibility. Consider if "going vendor lock-in" is the best long-term strategy for your organisation. Consider the speed at which CAI technology is still changing and improving.
Separating roles internally
Where your organisation has separation of roles between functions within your organisation, your CAI will have to reflect those responsibilities as well. When a customer is talking to your organisation's AI, they will not distinguish between specific roles. Internally an AI conversation between your customer and you covering financial transactions will most likely not be handled by the operations people in your organisation. Make sure that your platform enables you to separate support of specific functions of your AI.
Conclusion
These are just three essential aspects of managing an artificial intelligent conversation at enterprise scale. Zwerm provides you with a solution, a direction and freedom when it comes to your organisation's AI strategy.