Data / Machine Learning / Contributed

The Battle Between Unsupervised and Supervised AI

31 Dec 2020 6:00am, by
Kim del Fierro
Kim del Fierro is VP of Marketing of Aisera. Kim brings to Aisera a career spanning 22 years in leading, strategizing, delivering successful go-to-market initiatives.

Nothing can stop the momentum of evolution of artificial intelligence (AI). We are currently witnessing a digital transformation that enables the addition of AI capabilities to businesses’ existing IT Service Management and Customer Service Management tools.

Artificial intelligence, when applied to both internal and external service desk systems, helps users solve their problems autonomously, without requiring help from service desk agents — in fact, without any human intervention at all! This autonomy is the key to timely, high-quality service and increased productivity on both ends. Also, by relieving the service desk of low-level support needs and freeing agents to focus on critical, high-value tasks, AI reduces operational costs, improves service desk productivity, and provides users a prompt, satisfying self-service experience. The savings from AI can dramatically reduce business costs when applied to existing ticketing systems and knowledge bases leveraging the omnichannel (webchat, SMS, voice, and email).

Incorporating AI and Machine Learning (ML) today is not just an option but a crucial step to surviving and thriving in this digital economy. Today’s customers expect quick access to competent, informed support at all times. AI can meet such expectations in real-time around the clock. So, where and how should your business adopt AI technology?

Supervised vs. Unsupervised AI in Customer Support

If you are reading this, then you’ve most likely used a chatbot to try to get an answer to your service query. Usually, chatbot responses are built on a scripted set of inputs, which are mapped to outputs created by the brand. This supervised learning is limited and based on the questions that agents receive from customers. If a customer asks about A, then the script will “know” to take that customer to B. However, chatbots that don’t leverage AI cannot help if the customer requires assistance outside the limits of a chatbot’s supervised, guided flows.

To overcome the limitations of supervised learning, the industry began moving towards advanced (although more computationally complex) unsupervised learning. That’s because, in order to autonomously answer queries without depending on scripts, chatbots must be able to learn from the customer’s questions by using AI in an unsupervised manner. When unsupervised AI delivers self-service to users, the conversational interaction can leverage Conversational AI to become much richer and more natural.

Unsupervised learning embodies the intelligence and automation to work on its own and automatically determine information, structure, and patterns from the data itself. This capability enables unsupervised Natural Language Processing (NLP), with its demonstrable superiority.

Conversational AI based on unsupervised AI opens the door for support agents to take charge of more complex support requests. Agents can also contribute to an AI chatbot’s knowledge and engineering with reinforcement learning to identify and fill knowledge gaps. Most importantly, AI can help generate revenue by learning from and taking advantage of customer searches and queries to sell more products.

The Works of Supervised AI Chatbots

Supervised chatbots work on pre-written keywords in a conversation flow. When a customer types in a query, the chatbot responds according to the predefined script stored in its library. Every scripted chatbot command must be written separately, with a regular expression or other forms of string analysis. If the customer types in a query with no relevant keyword, then the chatbot will respond with a message such as, “I’m sorry, I don’t understand.”

The Works of Unsupervised AI Chatbots

AI-based chatbots, on the other hand, are intelligent. Aided by Natural Language Processing (NLP), they respond with appropriate suggestions on the topic; thus, AI-driven bots can “understand” the user’s language. When a customer interacts with an AI chatbot, that conversation approximates the experience of chatting with a human. This conversation is also recorded and used to refine and improve the capabilities of the AI chatbots. So, AI bots learn from interactions and become intelligent on their own.

Which Is Right for Your Business?

If you’re not interested in lowering the volume of calls and speed of resolution for your clients, then you can choose scripted chatbots. They are equipped with decision-free capabilities and start with the user asking a question. However, if you opt for an AI chatbot, you gain the ability to provide a unique, satisfying experience to your customers. If the AI chatbot reaches the point where it can’t continue the conversation with the user, it will quickly transfer the chat to a human agent. This type of chatbot allows you to provide far superior customer and employee conversational interaction.

Conclusion

Customers make or break every business, so they should be well-supported. They need a quick answer to their questions and problems, and a high-quality AI solution is the best way to give them the answers they need.

Our AI-driven, cloud-based solution lets you modernize your operations and your service desks, all the while scaling with you as your business progresses.

If you want to learn more about our AI Service Management offering, feel free to request a demo.

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