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Common challenges in Chatbots

A chatbot (also known as a conversational bot, chatterbot, interactive agent, conversational interface, Conversational AI, talkbot) is a computer program or an artificial intelligence which conducts a conversation via auditory or textual methods. By 2020, it is predicted that 85% of consumer interactions will be held without a human agent (Chatbots Life, 2019). 21. 80% of businesses are expected to have some sort of chatbot automation by 2020 (Outgrow, 2018). Following are some of the common challenges in Chatbots implementation.


Threats for Chatbot implementation can include events such as Repudiation, Spoofing, Tampering, Information Disclosure, Denial of Service, Elevation of Privileges etc. A Chatbot solution can become vulnerable and open to attacks when it is not well maintained, has poor programming or lacks protection. Fear for security is very vital Chatbot as they may bring new dangers, however, companies should be taking better security measures to ensure that users’ information is safe.


  • End-to-end encryption integration
  • Secure Protocols:HTTPS is the web protocol ensuring the privacy and integrity of our data.
  • Robust user identity authentication and authorization
  • When sensitive information is being transmitted, the message with this information will be destroyed after a set amount of time.


Context Integration

Making sense in responses is very important for chatbots. Integration of context into the chatbot is the first challenge to conquer. In integrating sensible responses, both the physical context and the linguistic context must be incorporated. For incorporating linguistic context, conversations are embedded into a vector, which presents a challenge. Contextual data, location, relationship, time, date, details about users, and other such data must be incorporated with the chatbot.


AI provides a greater sense of conversational awareness. It helps you create human-like conversations by decreasing the chances of misdetected entities. This considerably increases the performance of your entity detection. During a chat, bot is learning as much as possible from the flow, the user answers, the vocabulary choice and contextual references. By doing such an analysis, it is capable of forecasting the answers at all times, hereafter understanding them much better.

Nub8 - Challenges In Chat Bots Context

Exit Strategy

Chatbots are not that good at keeping up a conversation. Their pre-established number of answers and reactions is limited. So when Chatbot is stuck in finding solution to user problem, exit strategy is required.


When Chatbot fails to understand user thought process, there is a need to have a exit strategy to avoid bad experience of users as:

  • Always make guaranteed there’s an choice for your user to shift to a human operator
  • Most of the time, when Chatbots don’t understand , they simply take your text and turn it into a web search. With intelligent A.I., we’ll need an elegant way to send people to a system that can understand them when they’ve exhausted our possibilities.

Nub8 provides analysis, design, research and consulting services to assist you determine the best strategy for your business to implement a chatbot. We have strong skills with the various platforms, technologies, and bot frameworks which are available. Our team can guide you on your journey for successful chatbot implementation.