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Augmented Intelligence In Customer Education

This article is a handy guide for Customer Education professionals to quickly learn some key terminology and concepts related to Augmented Intelligence (AI), as well as some links to helpful content related to this topic. Let's start with a discussion of the different levels of AI you likely will use when building out your program strategy.


What are the three levels of AI?


Chatbots

Most websites have a way to leverage an initial discussion with a customer. These prompts appear simple but increasingly they are handled by a bot, which uses natural language processing to understand, identify context, and respond to people's questions or further the discussion. The "work" for a program using chatbots is in building the library of conversations that will be in play for the chatbot to use. These skills may be built on a decision tree structure to direct the bot in the conversation.


At some point, the conversation may become too complex for the chatbot to continue. That is where the questions are handed off to the next level of support, which often is a real person or a link to a knowledge base resource. The possibilities are extensive, but require planning. For example, will the response be the same for interactions based on different languages or locations?


There are several low-code, or no-code tools available that can augment your learning tech stack. Many products now include technology in their toolkits, such as a “chat with Sales” or “chat with Support” button.



Voice

The next level of AI solutions that a learning program can expect to use relates to "Voice." Think of: Alexa, Siri, Bixby, and more. The underlying assumption with these technologies is that actions will be performed based on a prompt, such as adding an item to a grocery list or playing a Spotify playlist. For customer education, this can mean voice interactions in the courses or catalog, or the analysis of recorded voice or video when evaluating performance.


A great use case in action can be found in a solution called Bongo. This technology can automatically review a video provided by a learner and identify specifics words or compare the answer to an acceptance standard. Many people have used these kinds of technologies in job interviews. The candidate will be asked to record the answer to a prompt. Their replies are then delivered to the hiring manager. With Bongo, using AI allows a customer education team to skip the manual review and just get the results.



Search Algorithms

The third type of AI Customer Education leaders should consider relates to Search. The most common advancement in this area of technology is often referred to as "federated search" which is where a person is delivered results from multiple sources – education content in a catalog, knowledge base articles, support articles and forum discussions. These algorithms, just like the ones people use when browsing the internet, bring their own set of issues. The most prominent amongst them relate to consistency, equitability and validity.



How to use AI solutions in your learning programs

All of these tools, together, can lead to a true consumer grade experience. This diagram shows the various combinations available to build out different levels of collaboration and/or automation. The best place to be is the center of the Venn diagram, combining the cooperate and autonomous agents gives us collaboration agents – chatbots, or smartbots. Cooperation and learning combine to collaboration learning agents that feed potential learning opportunities through in app options, presenting learning in the flow of work. Autonomous and learning combine together to create interface agents, which could also be used in app to create the user interface to present the learning opportunities.

The point at which all of these technologies join, the center of the Venn diagram, is the perfect utilization of the technologies. It gives the consumer grade experience that is seen with Amazon, Netflix, and other streaming services. Basic definitions up front on user preferences, roles, geographies, and more, then present content that is viable for that combination. The system continues to adapt to learner preferences as they happen, which refines the content presented. The ultimate learner experience. Complete with federated search, to find content anywhere, and allow the learner to look for content outside the specifications of their profile.



9 resources for using AI in Customer Education

If you’re interested in more reading on the subject, check out the following links:


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