Distinguishing between chatbots and conversational AI

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There exists confusion when it comes to differentiating between chatbots and conversational AI.  Most people, use chatbots and conversational AI interchangeably to mean the same thing. However, these two solutions have vast differences in the business world based on their origin and specific purposes. However, both tools have emerged from technological innovation and advancement in recent years. 

Chatbots operate based on the limited and predetermined flow that can activate a psychotherapist’s conversation using a script. Chatbots usually carry out conversations by deploying a specific pattern that gives users an illusion of understanding on the part of the program. However, chatbots do not have an inbuilt framework for contextualizing events. Chatbots entail communication between humans and machines. In this case, humans tend to believe they are conversing with a fellow human. Chatbots are usually ideal for small-medium businesses or even big organizations that seek to fulfill a single task. 

On the other hand, conversational AI operates in a completely opposite manner compared to chatbots. For chatbots, they follow a rigid structure with a predetermined conversational flow while conversational AI is flexible. To meet its target, conversational AI is powered by Natural Language Processing, Natural Language Understanding, Machine Learning, Deep Learning, and Predictive Analytics. The result is always more dynamic and less constrained. 

The standard make-up of the conversational AI usually entails an automatic speech recognizer (ASR), a spoken language understanding (SLU) module, a dialog manager (DM), a natural language generator (NLG), and a text-to-speech (TTS) synthesizer. In this case, the ASR puts into account raw audio and text signals and puts them to words later relayed to the SLU. The SLU then captures the underlying semantics based on a specified sequence of words. 

The next step entails analyzing and identifying the dialog domain, then the DM interacts with users and assists them. It also overviews the needed semantic representation and decides the system’s action. The DM also has access to the knowledge database to retrieve the information the user is seeking. Furthermore, the DM also comprises the dialog state tracking and policy selection to help in making robust decisions. 

Conversational AI is ideal for companies that deal with data-heavy like healthcare. The tool is also more convenient for companies with many moving parts that need integration to meet consumer needs. Worth noting is that Conversational AI emerged from chatbots, but they are more developed. Conversational AI is bound to evolve along the way, considering there is continued innovation in artificial intelligence, machine learning, and natural language understanding. Notably, both solutions are still relevant, with 69% of consumers preferring chatbots for quick tasks. Elsewhere, another 70% prefer to use conversational AI as virtual assistants.

In general, the two-way intuitive interaction of conversational AI engages the users and delivers accurate feedback within a short time-span. Since conversational AI holistically interprets the end-user, it becomes easier to understand consumers and improve business strategies.

Advantages of conversational AI over chatbots 

Conversational AI also comes with several advantages, like being omnichannel. For chatbots, they only operate via text commands, but conversational AI uses both voice and text. The capability makes conversational AI the solution for companies that have multiple digital channels.  

Chatbots usually depend on a pre-written script to meet the user’s needs. Elsewhere, conversational AI relies on Natural Language Processing and Understanding (NLU). This capability is powered by linguistics, computer science, and artificial intelligence to understand user input easily. The main catch for Conversational AI can interpret, recognize, and get the nuances of human language. 

Another advantage of conversational AI is the ability to support different sources like websites, text corpora, databases, and APIs. Whenever the source is updated, the modifications are automatically applied to the conversational AI interface. However, chatbots need constant manual maintenance, which can be costly and time-consuming. 

Most importantly, with both chatbots and conversational AI still relevant, their implementation varies. The choice of any solution is based on the specific requirements of companies, size, sector and business models.

Tips on getting started with Conversational AI

There are several means any enterprise can get started with conversational AI. In most cases, it is advisable to start small before scaling up. Here are some tips for getting started:

  1. Consider the greater goals of your organization. Review your business objectives and how you plan to achieve them. The next step is to consider how conversational AI can support those goals?
  2. Consider your audience. Any business usually serves a broader audience both internally and externally. Your audience can include; employees, consumers, patients, families, or suppliers. Once you have segmented your audience, determine which group would be best served with the benefits of conversational AI. At this stage, be specific to avoid losing sight of your goals. 
  3. The end goal. Once you know what your end goal needs to look like, you can start to build out your conversational AI platform. It is also essential to plan a series of sprints towards the ultimate goal. This allows you to gather customer feedback at each stage and it will broaden the project’s scope if required and provide proof points to ensure internal stakeholders are as enthusiastic about the development as customers.
  4. Team selection. This is the vital stage in rolling out your Conversational AI platform. Determine who is going to help you during each step of the process. Note that if you opt for your current IT team, review if they have enough resources and capabilities. Furthermore, if you plan to outsource, what are the right questions to ask so that your end goal remains intact. In general, do your research about the people you will involve in this process. 

Conclusion 

The benefits that Conversational AI and chatbots bring to any business, when implemented correctly, are significant. However, it is vital to research which technology is ideal for your business based on your end goal and available resources. When you adhere to the laid down guidelines, and best practices, Conversational AI and chatbots become easier to implement in your organization.


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Last Updated on May 25, 2021.

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