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Even though the first chatbot dates back to the 1960, a few years ago hardly anyone was having serious discussions about the power of Artifical Intelligence and its impact on our day-to-day functioning. Today chatbots and the AI are in the center of hyped-up speculation, making it tricky sometimes to separate facts from fiction. The AI remains a complex and thus vague subject, so it is only natural that it brings around myths and misleading ideas. So before implementing a chatbot in your enterprise, it may be interesting to debunk some myths around its intelligence. Let’s dig up some facts.

Myth #1: The AI only works well with routine actions.
Reality: Carefully trained, it will help solve more complex problems.

Artificial intelligence is not only suitable for blind automation of repetitive actions (although no doubts that it can be really good in this). Its prediction and classification skills allow it to act as a real time saver for company employees. Having analyzed a large block of data, AI can be able to assess a situation and propose quick solutions. Typically, a bot can stock a large amount of documented information and then retrieve a needed document upon a few key words demand within seconds. Or it can learn information from his conversational exchanges to propose new things in future talks. In a case of a support chatbot, for instance, if he encounters a technical problem he is not familiar with, he may ask the user for the solution and then use the information in his eventual conversations around the same topic.

Myth #2: Chatbots are the simplest form of AI.
Reality: Not quite.

A basic chatbot has no intelligence: it is a program that identifies keywords in the text and sends pre-prepared answers (if they are found in its database) based on mix and match logic. However, a chatbot can be way more sophisticated than that. To level up a chatbot it will be at least necessary to integrate technologies of natural language processing/understanding.

We can call a chatbot « intelligent » if it uses NLP/NLU bricks to analyze on different levels the demand he receives and if it runs on the basic machine learning bases. More complicated chatbots use more complex neural networks (frameworks using seq2seq models for instance) to actually generate answers all by themselves. Taking all of it into consideration, a chatbot that is running on the artificial intelligence logic can hardly be called « simple », and there are different levels of complexity when it comes to it.

Myth #3: It takes a huge amount of data to train a chatbot.
Reality: Not necessarily. 

You may need big datasets in the following cases:

– in the initial stages of training, when artificial intelligence is not yet capable of doing anything;
– when you want to teach AI to perform real complex activities such as driving a car.

If you want to adapt an existing AI to your needs, you won’t necessarily need a huge amount of data. Companies that implement artificial intelligence usually pre-train neural networks before integrating them within your systems. So all you have to do is just complete the bot with your specific business knowledge.

Myth#4: Artificial intelligence can learn independently.
Reality: Behind any bot, there should always be some supervision.

At the current stage of the artificial intelligence of chatbots, we are not yet in that happy place where we would leave the robots learn by themselves. The best example of it will be of course Tay, the notorious chatbot released by Microsoft, that managed to go racist and violent within hours after it’s been launched after having learned from twitter users. Just keep an eye on the process of bot learning. Show him what to learn and what to discard, otherwise, the efficiency and integrity of your bot can soon be compromised. That is even more applicable in the business context.

Myth #5: My company does not need to use AI technology.
Reality: Even if this is the case, you must first be sure of having studied the market and the AI capabilities that can be applied in your field. And the AI applications are vast.

Refusing to use AI for no particular reason may put your business at a competitive disadvantage. Rapid technology development leads to widespread automation, and AI is one of the ways to optimize company processes. Reducing the time-consuming task to make your team work on something with more added value to it is a real deal. Recurrent HR demands, recurrent support requests, automation of routine tasks, new tools training, onboarding of new employees, – the list of chatbot capabilities in a business field is endless and it grows in an exponential manner. So the question you should be asking yourself at that point is – have I studied all the possible advantages that implementing a chatbot can bring me?

Myth #6: AI technologies are not yet ready for industrial adoption.
Reality: Quite the opposite.

Lots of big companies have a problem with an enormous load on contact/support centers, and it’s becoming more and more difficult to cope with it. As the market of chatbot tools grow, business owners come to the realization that the integration of chatbots within their companies will help them optimize the two most important resources – time and money. From our own experience, we can say that the market is quite ready with the interest continuing to rapidly grow. This being said, we won’t deny that there is a huge room for improvement. But that makes things even more exciting.

What next?

The future of chatbots and automation in the business field remains quite challenging, but it is a new reality. Whether at your current stage you feel like you need or don’t need to implement the AI, the fact is that it’s always better to stay aware of all the possibilities it can bring you. Keeping up to date as the AI advances at a steady pace maybe not the easiest task, but it sure is rewarding at the end. The sooner you start implementing the artificial intelligence within your environment, the easier it will be for you to be on track with the AI expansion that will inevitably influence us all in one way or another.

Masha Isaeva, Learning & Chatbot hub manager at HubCollab