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Downsides of Chatbots

  • July 19, 2020
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Meet the Author : Mr. Bharani Kumar

Bharani Kumar Depuru is a well known IT personality from Hyderabad. He is the Founder and Director of Innodatatics Pvt Ltd and 360DigiTMG. Bharani Kumar is an IIT and ISB alumni with more than 18+ years of experience, he held prominent positions in the IT elites like HSBC, ITC Infotech, Infosys, and Deloitte. He is a prevalent IT consultant specializing in Industrial Revolution 4.0 implementation, Data Analytics practice setup, Artificial Intelligence, Big Data Analytics, Industrial IoT, Business Intelligence and Business Management. Bharani Kumar is also the chief trainer at 360DigiTMG with more than Ten years of experience and has been making the IT transition journey easy for his students. 360DigiTMG is at the forefront of delivering quality education, thereby bridging the gap between academia and industry.

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Chatbots have become more popular as a result of developments in artificial intelligence and machine learning. Their primary applications are in the sales and customer service divisions.

Customers love engaging with chatbots, which is one of the main factors for their popularity. Chatbots also carry out monotonous activities like gathering data from users and storing it in databases.

Customers have praised the bot's performance, while corporations are complimenting its efficiency and cost-effectiveness. But there are certainly darker aspects to these bots.

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Chatbot fails due to the following reasons:

Downsides of Chatbots


  • Security:

    When building a chatbot we gather a lot of sensitive data like the client’s data, confidential data, and even the customer’s data. If these data are not protected, then the data can be exploited by hackers and companies will have to face legal issues.

    Developers and Security professionals have to employ security protocols like identification, end to end encryption, authentication, destructive messages, and authorization. Also, while collecting the data only relevant information of the customers has to be saved.

  • Robotic Response:

    Though the chatbots give responses at any time, the responses will not have any humor and it will fail in understanding the sarcasm. They are not suitable for emotion recognition as well. It can sometimes become difficult to interact effectively with humans in some cases.

    By pre-defined conversations, we can find out the conversation flow. If there is a mismatch in a conversation flow then we might end up getting unexpected responses.

    We can build a sophisticated chatbot that will be trained on sentiment recognition, but it can’t be 100% perfect.

  • Not Vernacular:

    AI-driven chatbots function poorly in other languages since they are mostly developed on the English language.

    Machine translation was used by AI specialists and NLP practitioners to try to solve this problem, but it ended up misinterpreting the inputs and even losing some information. This might result in the bot giving the wrong answers and performing the wrong activities, misinterpreting the customer's question, and an inappropriate conversational flow.

  • Integration Flexibility:

    When it comes to the integration of the chatbot to different channels its not an easy task. Many chatbots are operated on the public platform. This will make the product and services accessible to multiple users. Also, the chatbot should interact inside the enterprise and external public services. So the challenging part here is to achieve all requirements and integrate on different platforms by maintaining the efficiency and correct operations. Here is the article on Advantages of Artificial Intelligence

    To achieve good integration, Rest API is used more often. But not all enterprises will go with API integration into sensitive internal systems. So, to overcome this enterprise gateway software, cloud-based platforms can be used to integrate with the internal enterprise without facing any security issues.

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  • Expensive:

    Without a doubt, chatbots will reduce labour costs significantly by continuously assisting several clients. The chatbots can't be generalised since each domain requires independent training, which raises the cost of initial installation. Instead, they are domain-specific. Investing in chatbots might be a bit hazardous if a last-minute change occurs because upgrading the bot would involve significant additional expenditures.

    Additionally, it will take a lot of time, effort, and money to automate a drawn-out or complicated operation. If a person is replaced instead of a bot, we might save a lot of money, time, and effort. Upkeep of the bots can also be time- and money-consuming.

    In other cases, compared to the expense involved in developing the bot, the necessity for the bot may just be for one person and a few clients. Therefore, perform a cost-benefit analysis first.


  • Inflexible:

    Since chatbots are designed to be domain-specific, it will give responses only to the questions which it is trained on. They can’t do anything more than what they have been taught. If there is a query that doesn’t relate to something which is not taught, it will not understand and the customers might get frustrated and will lose the sales.

    Also, there are situations where the chatbot can’t make decisions on the user’s input and may respond with unnecessary information. Hence, we need to make a chatbot that is optimized, and may not end up having a disaster.

  • Time-Consuming System:

    Chatbots are designed to increase consumer engagement and receive rapid answers. The updating process can occasionally be slowed down and made more expensive owing to a lack of data, hardware, or time. The chatbot may occasionally become confused if it receives several queries at once and be unable to assist even one consumer.

    The system will take longer to build when there are more ongoing queries and processing, which might delay company plans and increase costs.

  • Require Maintenance:

    Chatbots always have to be reviewed, maintained and it also has to optimize the information stored in them, so that they can communicate with the clients efficiently.

    Meaningful data has to be supplied so that it can be used to respond to the clients. They should be even capable of extracting important information and also have to address the problems faced by the customers.

    To achieve all the above tasks, the conversations of the bot has to be analyzed and identify the most frequently asked questions. Later the answers to those queries can be added to the data of the bot, but monitoring and analyzing the bot continuously is not a very easy task.

  • Bad at Improvisation:

    Chatbots work well for as long as the interaction flows inside the pre-programmed algorithm.

    The chatbots work fine as long as the bot follows the pre-written conversations. However, for developers, it is impossible to forecast all possible situations. So, it gets confused when a chatbot faces an unexpected behavioral scenario.

    Learning to deal with this and figuring out what a person is saying, leading questions are generated by a program. If the customer's answers appear to confuse the program, the program proceeds to answer the same clarifying questions.

    This may annoy customers and may also lose customers’ information. Click here to learn Artificial Intelligence Course in Hyderabad

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