Jan 26, 2023

An AI chatbot answering different employee questions.

The battle of the chatbots

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By now, you probably have heard plenty of times the words chatbot, AI, virtual agent, conversational AI: you might feel overwhelmed by these strange words, or maybe you are wondering how are all these related but also different at the same time. They affect your work, your life, the way you shop and search. And you are clearly wondering how they could alter your everyday work experience within your IT department, help you out or optimize the way you interact with employees and support them.

Maybe you are familiar with these technologies, and you are already considering adopting such a solution. Even so, it would be very helpful to break them down, and understand exactly what they are, how they work, their benefits and how they could optimize your job, so that you choose the best solution.

So, what is a chatbot?

A chatbot is a computer program that simulates and processes human conversation (either written or spoken), allowing people to interact with digital devices as if they were communicating with a real person. You can interact with a digital platform by typing in or voicing your questions, and then get answers. You connect with chatbots through a chat window. For example, by clicking on a "live chat" button on a company website and asking for customer support.

Chatbots can be as simple as elementary programs that answer a simple query with a single-line response, or as sophisticated as digital assistants that learn and evolve to deliver increasing levels of personalization as they gather and process information. And this is where it starts to get complicated, and you get inundated with all these “strange” words.

Wait, are “virtual agent”, “chatbot”, “conversational AI chatbot” all the same?

Basic chatbots use rule-based programming to match user queries with potential answers - they are trained to answer only a specific set of questions. So, while superficially useful, they are restricted in their range of operation, in both input and output. They require more than just keywords as input, so that they may parse the complete sentence for its proper semantic context, and then map the parsing to a known - and often limited - set of actions. But queries are usually fragmentary, and often misspelled - two characteristics that cause chatbots to fail in their effect. Where basic chatbots show their limitations is if they receive a request that has not been previously defined; they will be unable to assist, and spit back a “Sorry, I don’t understand.” response. Hence, they are usually helpful for just answering FAQs.

And this is where conversational AI comes in. It powers chatbots and enables them to become smarter and more capable. Conversational AI is the sum of the AI technology tools behind conversational experiences with computers. It refers to a host of artificial intelligence technologies used to enable computers to converse ‘intelligently’ with us.

With conversational AI you can go beyond just translating content into simple chatbot responses. You can actually mimic human behavior, and provide human agent-like experiences but without human involvement.

Conversational AI primarily works thanks to two functions. The first is machine learning, which is the technology that “learns” and improves the more it’s being used. It collects information from its own interactions and then uses it to improve itself as time goes by. The result is a system that will work better as time passes. The second is called natural language processing (NLP). This is the process through which artificial intelligence understands language, user intent and context – it will understand the way we naturally speak, with slang, abbreviations, mispronunciations and so on. Once it learns to recognize words and phrases, it can move on to natural language generation and go far beyond just answering simple queries based on pre-defined topics. Unlike rule-based programming, you don’t need the exact correct syntax for a chatbot to understand you.

So, the difference between a chatbot and a Virtual Agent (or Intelligent Virtual Agent or Conversational AI bot) is the use of conversational AI - not all chatbots are powered by it. There are the simple rule-based chatbots and the latter which are AI-based.

And how can I use chatbots in IT support?

Chatbots can help optimize your work in employee IT support: from answering simple questions originally addressed to your IT team, to giving information to employees about where to find what they are looking for, to automatically resolving their IT requests without you or your team getting involved. For example, imagine an employee asking you to reset their password because they forgot it – how would you feel if you deployed an AI-based chatbot on the employee communication platform (Slack or Microsoft teams) which would automatically reset it? And you wouldn’t have to deal with this request ever again?

Depending on how sophisticated the chatbot you deploy is, it can help minimize the number of employee IT tickets you manually handle, by providing answers to their requests. It can sync with the ITSM platform you use, to automatically “transfer” the IT tickets created so that they are handled by the right IT/helpdesk agent if needed. A chatbot will definitely simplify the actions needed by employees to perform tasks and at the same time reduce manual work for your team.

Hmm, then which type of chatbot do I need?

It really depends on your business goals and the cases for which you want to use it. If you are just looking for a bot to answer simple questions from employees, then you can definitely go for a traditional chatbot. However, if you are looking to improve user satisfaction and reduce the workload of your team by automating support across multiple platforms, then conversational AI is the right choice: it will help auto-resolve and auto-fulfill a very high % of the employee IT requests and repetitive tasks, and it will get better over time, meaning even less manual work for you and happier employees. Traditional, rule-based bots lack contextual sophistication and they deflect most conversations to a human agent. This will not only increase the burden of unresolved queries on your human agents but also nullify the primary objective of deploying a bot.

AI-based chatbots can have an omnichannel presence, and thus can be deployed across all your platforms. They are also highly scalable: as the company’s knowledge base and data are updated, so is the conversational AI interface, whereas you need manual maintenance for a simple chatbot. The deployment also is easier, as AI-based chatbots can be integrated with existing databases and applications with no need for time-consuming and complicated building processes.

There is no wonder why the volume of interactions handled by conversational agents increased by as much as 250% in multiple industries since the pandemic. By 2030, the global conversational AI market size is projected to reach $32.62 billion.