Top 10 Challenges to Chatbot Development – An In-depth look

 

Digitization is transforming our society, and chatbots are essential in this mobility-driven transformation. Industries like banking, e-commerce, retails, and many more use chatbots to stay connected with customers. Chatbots are a great way to be present and solve your customers’ queries without an actual human. This way, now, businesses can stay in touch with their customers even after their business working hours. It is one of the main reasons chatbot development services are so high in demand.

 

According to the leading sources, more than 50% of organizations will spend more on customized chatbot development rather than the traditional development of mobile applications by the year 2022. Considering all these, it is no real shocker that the global chatbot market has experienced a 24% annual growth rate and is expected to reach $1.25 billion by 2025.

 

What are Chatbots?

 

You must have probably interacted with chatbots at some point in your life, either while booking a cab ride or ordering a coffee from a nearby café. Most of the websites and mobile apps have chatbots embedded with them, so they must have helped you in some way or the other.

 

A chatbot is AI powered software that can chat with a user, just like humans, via messaging applications, websites, mobile apps, or telephone. This conversational AI can answer questions, perform actions, and make recommendations according to the user’s needs.

 

Several businesses are already using chatbot solutions. These digital assistants have a use in every industry vertical and understand human language.

 

Types of Chatbots

Task-oriented chatbots

 

These chatbots are designed to handle simple queries, which do not require too many variables. The responses of these chatbots are highly structured and scripted. They generate automated but conversational responses using pre-defined instructions, NLP, and very little Machine Learning. The use of these chatbots are especially in banking and financial institutions.

Data-driven and predictive chatbots

 

Also known as intelligent chatbots, they can do more like human conversations. Using Artificial Intelligence, these chatbots are self-sufficient to answer on their own. Along with monitoring data and intent, they can initiate conversations. These are the chatbots of the new generation, with enhanced features and commands.

Rule-based chatbots

 

These chatbots operate based on a pre-determined set of rules and responses. They are programmed to recognize specific keywords or phrases and respond with pre-set messages or actions. Rule-based chatbots are helpful for simple tasks such as providing basic customer service or answering frequently asked questions.

AI-powered chatbots

 

These chatbots use machine learning algorithms and natural language processing (NLP) to understand user input and generate responses. They can learn from past user interactions and improve their responses over time. AI-powered chatbots are more advanced than rule-based ones and can handle more complex tasks, such as booking appointments or providing personalized recommendations.

Virtual assistants

 

Virtual assistants are chatbots designed to perform user tasks, such as setting reminders, sending messages, or making phone calls. They use advanced NLP technology to understand natural language input and can perform tasks that typically require human intervention.

 

Social media chatbots

 

These chatbots are designed to interact with users through social media platforms such as Facebook Messenger or WhatsApp. They can be used for customer service, lead generation, or product sales.

Voice assistants

 

Voice assistants, such as Siri or Alexa, are chatbots that use voice recognition technology to interact with users. They can perform various tasks, including answering questions, playing music, or controlling smart home devices.

6 Ways Chatbots Are Being Used

 

Chatbots are becoming increasingly popular across various industries thanks to their ability to provide efficient, personalized customer service at scale. Here are six ways chatbots are being used today:

 

1. Customer service: Chatbot development services are increasingly used to handle customer service inquiries and support requests. By using AI-powered chatbots, businesses can provide 24/7 support to customers without the need for human intervention. It can help reduce wait times, increase customer satisfaction, and lower business support costs.
2. Sales and marketing: Chatbots are also used to generate leads and drive sales. Businesses can qualify leads, answer questions, and even make sales using chatbots to interact with potential customers. Chatbots can also be used to send personalized messages and promotions to customers, helping to increase engagement and drive sales.
3. Education: Chatbots are used in the education sector to provide students with personalized learning experiences. With the help of chatbot development, educators can provide students with immediate feedback, answer questions, and even provide personalized recommendations based on their learning style.
4. Healthcare: Chatbots are used in the healthcare industry to provide patients with 24/7 access to medical information and advice. By using chatbots, patients can receive personalized health advice and support without the need for human intervention. It can help to improve patient outcomes, reduce healthcare costs, and improve the overall patient experience.
5. Finance: Chatbots are used in the finance sector to provide customers with personalized financial advice and support. Using chatbots, customers can receive advice on investment strategies, manage their finances, and even make trades. Chatbots can also provide real-time updates on financial markets and investment opportunities.
6. Travel and hospitality: Chatbot development services are also used in the travel and hospitality sector to provide customers with personalized travel recommendations and support. Using chatbots, customers can receive information on travel destinations, make travel bookings, and even receive real-time updates on travel disruptions.

 

 

Chatbot Development Challenges You Cannot Ignore

 

Chatbots are one of the most robust and cost-efficient mediums for businesses to engage with multiple users. They are known to offer humanlike and personalized services to a large number of users at the same time and are certainly the most preferred way to connect with your users.

 

However, there are times when chatbots have not met expectations and have turned out to be failures. As chatbot development is still in its infancy, there are a few challenges that need to be controlled to implement a more robust messaging strategy for the future.

• Cold user experience
• Lacks engagement
• Lacks user experience
• Chatbot security
• No clear scope
• Multiple language support
• Weak memory
• Limited responses
• Lack of personalization
• Lack of emotions 

Let us see these challenges in detail:

Challenge 1: Offering Cold User Experiences

 

The major drawback of these chatbots is their conversational flow. Sometimes, the chatbot conversation may feel like a script and a bit robotic. Chatbot conversations lack personalization. A business must first empathize with it to understand the customer’s query. But this factor is lacking while chatting with a bot. At times, users do not feel they are being heard, as chatbots always give a system-generated reply.

 

However, many web development solutions have overcome this aspect using the following tips:

• Using a human voice instead of a robotic one would make the visitor feel familiar.
• Using emojis makes the conversation more interesting.
• Using simple language so that a layman would understand every bit of it.
• Injecting humor so that even if the resolution is not in favour of the consumer, he will go back with a smile,
• Slow down and do not shower the consumer with endless questions.
• Also, preparing the chatbot for an unanswerable question with a polite answer would enhance the customer experience quite effectively. For example, ‘Sorry, I could not understand you in this context.’ or, ‘I’ll try my best to answer you next time.

Challenge 2: Lacks Engagement

 

Chatbots follow a defined scripts, and sometimes, they cannot respond to commands outside the programmed sequence. This results in a repetitive and annoying situation. Also, chatbots are not always engaging; hence, people lose interest when there is no response or delayed response from the other side. Hence, the bot that quickly identifies and resolves the issues is considered the better one instead of the one that asks a plethora of questions before looking into the issue, resulting in a waste of time. Using the knowledge of AI software development, a chatbot developer can easily overcome this challenge.

 

For bots to get better, they need to be programmed with the ability to learn from the conversations they’re having with users. Initially, chatbots may face some difficulties due to a lack of information for the first time, but as time goes by, chatbots must be evolved to have engaging conversations with users. Hence, the business needs to start experimenting with technology to improve the experience incrementally.

Challenge 3: Lacks User Attention

 

Developing a chatbot that can hold the user’s attention until the end is quite challenging. Due to a busy lifestyle, everyone wants to resolve their query immediately without answering too many questions. In some cases, however, a machine wouldn’t always render the same empathy that a human could, and this is when a human replacement thing gets attention. Chatbots are not good at paying attention to every detail the user asks for. Even the most intelligent chatbots aren’t self-learning. However, it is suitable for the sake of human society that it has not developed or commissioned a machine yet or any entirely self-reliant chatbot. They should always require humans to supervise their learning. Here is where conversational UI plays its role.

Challenge 4: No Clear Scope

 

A chatbot needs a clear scope of the topic to get ready for the user’s answers. There is no satisfactory answer if the chatbot is being used at a broader level or for several topics. Hence, a clear scope is must for a user-friendly experience.

 

Also, there are times when what a user is trying to explain, but a chatbot is unable to understand, resulting in high dissatisfaction. Hence, businesses need to improve technology occasionally and keep their chatbot solutions updated. Businesses may also hire a dedicated development team to develop customized chatbot solutions per their business requirements.

 

Also, machine learning embedded chatbot solutions would work even better as they would keep on learning and helping the developers to update more smartly.

 

NLP modification

 

There exists a concept of natural language processing or Neuro-linguistic programming with which, if the chatbot is programmed, it can interpret, recognize, and understand the queries made by any user for the upcoming users. All this is a part of Machine learning and Artificial intelligence combined, and it can be improved with the help of adept AI and ML developers.

Machine learning and natural language processing must have the model set before their development.

Challenge 5: Chatbot Security

 

Users still do not trust chatbots easily; they may sometimes look like spam, and users try to avoid interacting with them. It is always advisable for businesses using chatbots to be transparent with their user, as there are times when users may take these bots as real humans, which is one of the main reasons users lose their trust in the company.

Also, businesses must focus on the security features of their chatbot solutions besides other aspects like features. Additionally, you need to ensure that the chatbot is secure so that no one can access your chats.

 

The solution to Chatbot Security

Challenge 6: Multiple Language Support

 

Chatbots are highly rigid in how they perceive the data and what they deliver. In the case of chatbots, the data is in the form of Natural Language Processing (NLP). NLP is a combination of Computer Science and Linguistics, which tries to make sense of the text in a way that can be easily understood. Hence, it is necessary to be specific while selecting the NLP for fixation.

 

From generative to retrieval-based models, a chatbot development company weighs all models to create an intelligent and interactive solution for your business. However, there are some limitations to NLP that it has some difficulties in not only adapting to different languages but also, different dialects and colloquial terms. It is where chatbot developers need to push their way and work on resolving this issue as soon as possible. Many chatbot development platforms are available to develop innovative and intelligent chatbots to overcome this problem.

 

 

Challenge 7: Memory

 

The major drawback of chatbots is their lack of human memory. Developers and software development companies should develop an improved memory for chatbots to provide better support and a more human connection. Designers should design chatbots in such a way that they can retain the previous conversation and other details. It will not only refrain these bots from asking the same questions repeatedly but will also help increase the engagement rate.

 

The key to the evolution of any chatbot is its integration with context and meaningful responses. It becomes challenging for companies to build, develop, and maintain the memory of bots that offer personalized responses. They must ensure that these virtual assistants do not interact in the same pre-defined old model.

 

Challenge 8: Limited responses

 

Limited responses refer to the inability of chatbots to understand and respond to a wide range of customer queries. The programming of chatbots is such as to respond to specific questions or statements, and the extent of the programming limits their ability to understand customer intent.

This limitation is a significant challenge for chatbot development services as it can lead to unsatisfied customers and negatively impact the business. For instance, if a customer asks a question that is not within the scope of the chatbot’s programmed responses, this may result in some frustration to customer It can result in losing trust in the chatbot and the business.

 

Solutions

 

Chatbot development services must focus on improving the chatbot’s natural language processing (NLP) capabilities. NLP is the technology that enables chatbots to understand and interpret human language. Enhancing the chatbot’s NLP capabilities enables it to understand a broader range of customer queries and respond appropriately.

 

Another solution to limited responses is to incorporate machine learning into chatbot development. Machine learning enables chatbots to learn and improve their responses by analyzing customer interactions. This approach allows chatbots to expand their knowledge base and provide more accurate and relevant responses to customer queries.

 

Challenge 9: Lack of personalization

 

Personalization is critical for any successful customer service strategy. Customers today expect a personalized experience that caters to their unique needs and preferences. However, chatbots often fail to deliver this level of personalization. Designers create chatbots to provide quick responses based on pre-programmed rules and scripts, but they lack the ability to understand and respond to customers’ needs.

 

For instance, if a customer seeks information about a particular product or service, a chatbot may provide a generic response that does not address the customer’s concerns. It can lead to frustration and a negative customer experience. Moreover, customers may lose trust in the brand and switch to a competitor offering a more personalized experience.

 

How To address the Challenge

 

To address this challenge, chatbot development services need to focus on developing chatbots that can understand and respond to customers’ individual needs. It requires leveraging advanced technologies such as artificial intelligence and natural language processing. By integrating these technologies, chatbots can analyze customer data, understand customer intent, and personalize responses based on the customer’s individual needs and preferences.

 

In addition to using advanced technologies, chatbot development services can also implement various personalization strategies to enhance the customer experience. For example, businesses can allow customers to customize their chatbot experience by selecting their preferred language, tone, and style. It can help create a more personalized experience and build stronger customer relationships.

 

Challenge 10: Lack of emotions

 

Emotions are a critical component of human communication. They play a crucial role in understanding context, interpreting meaning, and establishing relationships. A lack of emotions in chatbots can lead to a sterile and unengaging conversation, making users feel unheard and unimportant.

The lack of emotions in chatbots is a common problem due to artificial intelligence (AI) limitations. Designers create chatbots to respond to specific keywords or phrases, but they cannot always grasp the nuances of human emotions. They lack empathy, and their responses can be robotic or impersonal.

 

How to Overcome

 

To overcome this challenge, chatbot developers must integrate emotional intelligence into their chatbots. Emotional intelligence can enable chatbots to understand human emotions, respond appropriately, and provide personalized support. Integrating natural language processing (NLP) and machine learning algorithms can help chatbots recognize the tone, sentiment, and context of the user’s message.

One way to add emotions to chatbots is by using emoticons or emojis in the responses. Emojis can convey emotions like happiness, sadness, anger, or excitement, making the conversation more engaging and humanlike. Another approach is to use emotionally trained chatbots . Programmers program these chatbots to recognize and respond to emotions, thereby making them more empathetic and responsive.

 

Impact of the Chatbot Development Challenges

 

Chatbot development challenges significantly impact the success of chatbots in fulfilling their intended purpose. Here are some of the impacts of these challenges:

• User Experience: Chatbots that lack emotions or struggle to understand users can lead to a poor user experience. Users may feel frustrated or misunderstood, leading to a negative perception of the brand or product.
• Customer Satisfaction: Chatbots are often deployed to improve customer satisfaction by providing quick and efficient support. However, if chatbots cannot effectively address customer needs, it can lead to dissatisfied customers and a decrease in customer loyalty.
• Brand Image: The success of chatbots can impact a brand’s image. If chatbots cannot effectively address customer needs, it can lead to negative reviews and a decrease in customer trust.
• ROI: Chatbot development can be expensive, and if the chatbot does not provide value to customers, it can impact the business’s return on investment (ROI).
• Competitiveness: Chatbots have become increasingly common, and businesses that do not have effective chatbots may struggle to compete with those that do.

 

Addressing chatbot development challenges

 

Addressing chatbot development challenges can bring significant benefits for businesses, including improved customer satisfaction, increased efficiency, and cost savings. Chatbots that can effectively understand and respond to users’ needs can lead to a positive user experience, improved brand image, and increased customer loyalty. Additionally, chatbots that provide personalized support can increase customer engagement and higher conversion rates. Overall, addressing chatbot development challenges is crucial for businesses that want to leverage the benefits of chatbot technology.

 

 

Future of chatbots

 

The future of chatbots is promising, with many industries adopting chatbot technology to improve customer experiences and streamline processes. In the coming years, chatbots will likely become more advanced, with increased personalization and the ability to perform more complex tasks.

 

In the healthcare industry, chatbots can assist with patient monitoring, provide personalized health recommendations, and even diagnose conditions. Chatbots can provide 24/7 customer support and assist with financial planning in the financial sector.

 

 

With advancements in natural language processing and machine learning, chatbots are becoming even more intelligent, with the ability to understand complex human interactions and provide more accurate responses. The future of chatbots is exciting, and we can expect to see them playing a more significant role in many aspects of our lives.

 

Final Thoughts

 

If professional IT services are involved and there is strong trust between the project owner and the team, every challenge mentioned above can be resolved. Customer service chatbots are a white-hot topic these days as these are so effective .

 

Why wait for future stats, the most commonly used social media platform” Facebook” itself has over 500,000 chatbots on Facebook Messenger alone. One can replace human representatives with chatbots so that users can interact with whether through the website, mobile application, or even popular messaging apps and can expand the business to reach globally and provide service 24 hours, 7 days a week. Also, according to HubSpot, “47% of consumers are open to buying items by the mode of the chatbot.” In the near future, chatbots can offer businesses a new way to support their clients.

 

FAQs

 

What are the challenges for designing a chatbots?

 

There are many hurdles to designing chatbots that may provide beneficial, human-like interactions. Some key challenges consist of:

1. Natural language: Chatbots should comprehend complex consumer inputs with numerous grammars, spelling mistakes, slang and abbreviations. This calls for advanced herbal language processing and gadget studying.
2. Handling open-ended conversations: Chatbots cannot hold conversational context and keep in mind data discussed earlier. They often offer irrelevant or repetitive responses based on confusions.
3. Providing customized responses: Chatbots developed by artificial intelligence development companies lack the capability to conform responses primarily based on knowing the person properly. They have problem imparting personalized solutions appropriate for each user’s temperament, pursuits and dreams.
4. Giving convincing, human-like responses: Most chatbots nevertheless sound mechanical and awkward. Producing human-like, nuanced responses at scale stays a project.

What programming language is used for chatbots?

 

Here are some of the main programming languages used for building chatbots:

• Python – Python is one of the most popular programming languages for chatbots due to its numerous libraries for natural language processing, machine learning and AI. Frameworks like Rasa, Chatfuel and Dialogflow use Python.
• JavaScript – JavaScript is used widely with frontend frameworks like Node.js to build chatbots. It has libraries like Natural Node to implement natural language processing.
• Java – Java is an object-oriented language suited for building complex chatbot applications. It has APIs and libraries like Stanford NLP for natural language functionality.
• PHP – PHP is commonly used with CMS platforms like WordPress to quickly build basic chatbots. It can integrate with popular chatbot APIs.
• Ruby – Ruby has various gems or libraries that make it ideal for creating chatbots. Frameworks like Rutype, Chatty and Coconet are built with Ruby.
• Swift – Apple’s Swift language can be used to build chatbots for iOS apps and Siri Shortcuts.

 

What technology chatbot development uses ?

 

The technology used for growing chatbots are natural language processing, device getting to know, expertise bases, and synthetic intelligence. These paintings together to enable a chatbot to apprehend language, reply accurately, hold conversations, and improve through the years.

Natural language processing permits the chatbot to interpret human language input by means of analyzing syntax, detecting entities, and figuring out intent. It is the foundation for most chatbots. The use of machine learning strategies like supervised studying, reinforcement gaining knowledge of, and deep learning is to build additives like purpose classifiers and conversation managers that may enhance mechanically. Knowledge bases store statistics, policies, and facts the chatbot can question to generate relevant responses. They provide the content that drive conversations.

Technologies developed by artificial intelligence development companies like deep gaining knowledge of and neural networks, allow for extra sophisticated capabilities. Chatbots powered by using AI can mimic characteristics of human intelligence throughout conversations like reasoning, mastering from enjoy, and adapting to unique contexts.

 

Other associated technology encompasses APIs that allow chatbots get right of entry to outside records, gear for sentiment evaluation that permit the bot to hit upon emotions, and speech popularity systems that permit voice-based totally interactions. Dialog management structures decide how a communication have to development based totally on person utterances.

 

What is the use of a chatbot?

 

The use of Chatbots is to offer automatic customer service and information to users through textual content-based conversations. They are increasingly more used by companies to answer product related questions, cope with order requests, provide technical support, greet internet site visitors, and manipulate easy transactions. 

Basic chatbots use canned responses and regulations-based totally algorithms to reply to user messages, whilst more superior chatbots make use of system learning and natural language processing techniques to automate conversations that mimic how a human could interact. Overall, chatbots goal is to make interactions brief and handy, It is to be 24/7 available to potential customers through messaging systems like Facebook Messenger, WeChat, or web sites.

 

What are the challenges of chatbots in customer service?

 

Understanding complex customer queries is difficult. Chatbots struggle to comprehend nuances in customer language, contextual implications and subtle issues raised. This limits their ability to resolve customer problems.

Maintaining the context of long customer conversations is a challenge. Chatbots often forget details from earlier in the interaction, leading to confusion and providing irrelevant responses. This hinders their effectiveness in solving customer issues.

Providing personalized responses to different customer needs and temperaments is hard for artificial intelligence development companies. Chatbots typically provide generic, one-size-fits-all responses. They lack the ability to tailor responses based on individual customer characteristics.

Interacting with customers in a human-like manner is an ongoing struggle. Most chatbot responses seem mechanical and artificial. They have trouble replicating the empathy, nuance and emotional intelligence of a human agent. This reduces customer satisfaction.

Building knowledge bases covering all potential customer queries is resource intensive. It requires vast amounts of data and effort to train chatbots to handle the myriad of issues customers may face.

 

What problems can chatbot solve?

 

Chatbots have the potential to help solve a variety of business and customer service problems:

• Repetitive customer service tasks – Chatbots can handle high volumes of simple customer service requests that follow predefined steps. This frees up human agents for more complex issues.
• Routine information requests – Chatbots can reliably provide answers to common questions from customers or employees. This saves the time of human agents for non-routine queries.
• Scheduling and appointment making – Chatbots can help schedule appointments, meetings and events by interacting with customers’ calendars and finding available times that work.
• 24/7 support – Chatbots can be available at all hours to answer basic questions and point customers to self-service resources. This provides customers with around-the-clock support.
• Data retrieval – Chatbots can quick retrieve records and records from databases, information and understanding bases. They can deliver customers with the facts they want at the moment they need them.

Chatbots can help remedy problems like repetitive customer service tasks, recurring information requests, appointment scheduling, supplying 24/7 aid, retrieving statistics, processing basic transactions and freeing human dealers for extra precious duties. With advances in generation, chatbots will likely take on a fair extra trouble-fixing function inside the destiny.

 

What are the 4 types of chatbots?

 

1. Rule-based chatbots: These are the maximum fundamental form of chatbots. They use if-then rules and patterns to healthy consumer enter and offer a response. They can deal with easy, structured conversations but lack the flexibility and intelligence of greater advanced chatbots.
2. AI-based totally chatbots: These chatbots utilize technology developed by artificial intelligence development companies like system learning and natural language processing to automate conversations. They can adapt and enhance through the years based on interactions with users.
3.  Context-based totally chatbots: These chatbots depend on contextual statistics like user history, place, alternatives and extra to provide personalized responses. They use context to apprehend person queries higher and offer applicable solutions.
4. Hybrid chatbots: These are the most advanced chatbots that combine a couple of technology to offer human-like interactions. They usually have a mixture of rule-based responses, gadget learning competencies, contextual information and integration with external information sources. Hybrid chatbots intention to obtain the satisfactory of all the chatbot kinds.

In summary, the 4 fundamental forms of chatbots from basic to advanced are: rule-primarily based, AI-based, context-based totally and hybrid chatbots. The kind of chatbot constructed relies upon on the specified project complexity, personalization, degree of intelligence and finances.

 

What is the advantage of chatbot?

 

Here are the main blessings of chatbots:

• Available 24/7: Chatbots perform across the clock because of these customers have access to information and guide whenever. AI development company can improve convenience and customer pleasure.
• Speed: Chatbots can reply much quicker than a human agent, regularly in seconds. This improves the person enjoy and efficiency.
• Reduce costs: Chatbots don’t require salaries, breaks or different employee costs. This can extensively lessen the value of customer support and provider.
• Handle repetitive duties: Chatbots are true at managing high volumes of repetitive duties like answering FAQs, processing transactions, and so on. This frees up human sellers for extra complicated duties.
• Gather records: Chatbot interactions generate big quantities of facts that can offer insights into consumer conduct, options and issues. These statistics can be of use to improve marketing, income and support.

 

Is it difficult to develop a chatbot?

 

Yes, developing effective chatbots is very difficult for several reasons:

• The main challenge is natural language understanding. Chatbots must be able to recognize meaning from complex human speech with ambiguities and nuances. This is still very difficult for AI.
• Developing robust conversational models is hard. Chatbots need to maintain coherence over long conversations and switch topics intelligently. This requires sophisticated algorithms.
• Training chatbots requires a massive amount of data. Developers need large datasets of tagged conversations to teach chatbots. But acquiring and labeling data at scale is expensive and labor-intensive.
• Generating appropriate, natural responses is a major hurdle. Most chatbots respond in unnatural, robotic ways that frustrate users.
• Handling open-domain conversations is challenging. Chatbots work best when limited to a narrow domain. But general-purpose chatbots developed by AI development company that can discuss any topic remain elusive.
• Integrating chatbots with enterprise systems is complex. Chatbots need to access and modify backend databases, triggering additional technical difficulties.

 

What are the main challenges in conversational AI?

 

The biggest challenge is understanding natural language. Human speech is complex, nuanced and ambiguous. Conversational AI solutions struggle to:

• Understand complex sentences, idioms, slang and sarcasm. This often leads to misunderstandings.
• Handle misspellings, grammatical errors and “noisy” text that is common in conversations.
• Interpret the full meaning and context behind what users say. They rely on matching keywords but miss subtleties.
• Continue a coherent conversation over time. They lose track of context and provide inconsistent responses.
• Adapt to different languages, accents and dialects. 
• Recognize emotions conveyed through language. They tend to be “tone deaf” and fail to adapt responses appropriately.

Chatbots’ inability to truly understand and converse like humans, their need for large training datasets, difficulties generating proper responses, memory limitations, integration challenges, performance evaluation issues, bugs and lack of common sense all contribute to make AI chatbots developed by conversational AI companies inadequate substitutes for human agents in most cases today.