AI Chatbot Development Challenges & Its Future

We all are familiar with chatbots by now. A chatbot is a software application whose primary purpose is to conduct an online conversation via text or text-to-speech as an alternative to providing direct contact with a live human agent. A chatbot can automate conversations and interact with users through various platforms.

Different kind of chatbots

There are various kind of chatbots that we use in our daily lives today. Here are the broad three categories and types of chatbots you should know about:

1. Simple Chatbots

Simple chatbots have limited capabilities. They are rule-based and task-specific. The best way to understand simple chatbots is by comparing them to IVRS technology. IVRS refers to Interactive Voice Response System, a technology that enables users to interact with a computer-operated phone system by asking numerical inputs from the users via their dialpad. Simple chatbots function similarly.

It will pose the user with predetermined questions, and the user can choose one of these questions that closely resembles their problem. The chatbot would provide the user with troubleshooting solutions or guide regarding the option chosen by the user. Such chatbots do not draw inferences from previous interactions and are best suited for straightforward dialogues. They do not have much utility, but they are easier to build and train too.

For Instance — Ordering Pizza

Consider yourself to be a customer. You are interacting with a chatbot to order pizza. The flow of conversation would be predetermined. The chatbot would ask you questions just as an operator would over the call. There would be certain parameters to order the good pizza that you want. It would ask you your preferences for the size, toppings, crust, and cheese quantities. Once you have customized your ideal pizza, it would then move on to asking your delivery address and contact information. And voila! You have your pizza order ready.

2. AI Chatbots

AI-enabled chatbots are designed for stimulating human-like interactions with customers. Such chatbots can have free-flowing and more open conversations with users. They can also understand intent, sentiment and language through constant learning. They function on machine learning technology, through which they can constantly learn and improve. They self-improve from the interactions they have with various users as well. AI chatbots can be considered smart chatbots as they’re built with advanced technology and have the potential to provide excellent user experience, help, and ease to their users.

For Instance — Virtual Assistants

Everyone knows Siri and Google Assistant as their smartphone assistant technologies. With one command of ‘Hey Siri’ or ‘Ok Google, you can operate many functions related to your smart devices without ever touching the phone, using only your voice. These AI chatbots learn from every human interaction. Apart from providing utility features, they can also engage in small informal talks where they can draw inferences from previous messages, creating dialogue. Such AI chatbots have a lot of potential, limitations and benefits for every sphere of our lives.

The Current Scenario of AI Chatbots

AI Chatbot Stats from different sources

1. Businessinsider predicts the market size for AI chatbots to increase from $2.6 billion in valuations in 2021 to $9.4 billion valuations by 2024.
2. Outgrow found out that 56% of users prefer using chatbots over calling customer support.
3. VentureBeat pointed that Facebook AI Bots have already crossed a staggering number of 300,000 monthly active bots.
4. Oracle realized that over 50% of customers expect businesses to be available and open 24/7.

How AI Chatbots assist Customers

Artificial Intelligence has been widely adopted in our everyday life and business spheres as well. However, we are just at the starting line of the potential AI for improving business and everyday activities. AI-powered chatbots have achieved certain milestones for helping customers with their requirements. Here are some of the best ways AI chatbots assist customers:

1. By utilizing contextual information

As we discussed above, simple chatbots work on a list of pre-determined questions and provide a standard list of menu options to solve the anticipated queries users might have about their services. AI helps to remove such limitations. AI empowers chatbots to engage with the customers contextually by utilizing various tools to monitor visitors’ journey from google search or organic navigation path that got them here. A chatbot can more or less adjust their conversations with users as per the content they get access to from your company’s site.

For instance — if a user visits your website and spends a lot of time reading and navigating through one service that you provide, the chatbot can infer that the user is mainly interested in that particular service and is looking for a solution same. Based on this, it can prompt a conversation with content relevant to that service. In contrast to the reactive approach of simple chatbots, this proactive approach helps websites capture the visitor’s attention right from the start. This helps in a better user experience compared to making them go through a list of available options and finding the one they want an answer for.

2. Filtering and Routing Important Inquiries to Appropriate People

Irrespective of the business’s size, if you have a product/service that is in demand and you start gaining popularity as one of the best businesses in your niche, you will be flooded with curious inquiries. Your support teams will be overworked with handling, filtering and sorting out genuine inquiries and sending them to the appropriate people who can convert those inquiries to leads. Not only is this process labour-intensive but also time consuming. By the time your support team sends one important inquiry to the appropriate representative, and they see the inquiry, it might already be too late, and that potential customer might have found an alternative solution elsewhere!

AI chatbots can help you overcome this limitation as well. AI-powered chatbots can be equipped with NLP — Natural Language Processing tools, which can help determine the need behind any inquiry. With enough learning and constant development, it will understand what the user is looking for and the information they will need for the inquiry to be resolved. Based on this, it can determine which support agent to redirect that specific inquiry to. You can also train the chatbot to send inquiries to different individuals based on the inquiry’s complexity. If it is a simple inquiry, it can be sent to someone new on the team, and so on. This would help you better manage your customer support and keep proper track of each agent and their productivity.

3. They work as an effective tag team partner with your agents

Many people wrongly assume that chatbots need to automate the customer support process entirely. There are many instances where chatbots can unison with the agents, helping the agents improve their productivity and filter out spams to save their time. Often, chatbots are only utilized to greet and engage with the customers in the initial stages of the conversation. Then they pass that customer along to a human support agent for further inquiry.

You can use AI chatbots to capture information about the visitors in the beginning phase of the communication. AI chatbots can ask for necessary details like account number, payment details, order number and more so that the human agent already has information on the customer’s query and can address it in a better way.

Limitations of AI Chatbots

While there are several benefits of integrating AI chatbots in our daily lives and business operations, there are certain challenges and risks also that we should be aware of. Let us discuss a few of them:

1. AI chatbot security risk

Data is one aspect that always seems to be at risk when it comes to doing anything online. Customers trust online websites and tools with their precious sensitive and important information, and they expect the data to be protected from misuse. Hence creating AI chatbots that have security measures is not only advantageous but a must.

Your AI chatbot should collect only the visitors’ necessary information and transmit it securely over the internet. Additionally, you need to invest in your AI chatbot to make it hack-proof as well.

2. The ability to understand the sentiment and emotions of visitors.

We already have conversational AI platforms and general AI platforms that can use previous conversations to hold a dialogue with the visitor. Most of these AI-powered chatbots can understand the sentiment and emotions of the visitors to an extent too. However, they are still at an early phase and the chances of them missing is as good as them being accurate. Interpreting human emotions with those chances is a gamble because if your AI chatbot misinterprets human emotions, there can be huge negative impacts on your business. For overcoming this challenge, you need to train your chatbot rigorously constantly.

Acceptance of AI Chatbots in Industries

AI-powered chatbots have affected and helped many businesses across all industries reduce their operating costs, which has led to its market size increasing significantly over the years. Chatbot marketing, payment processing and services are different niches chatbots can be useful in. Some of the biggest advancements in AI chatbots in recent years have been in perception and cognition. We still have ways to go for mastering voice recognition. However, Google, Apple, and Amazon have made significant progress with Google Assistant, Siri, and Alexa.

Machine learning techniques are being used to make trades in Wall Street and predict customer actions like clicking on a particular ad, increasing efficiency on both customer and business ends. Apart from being revenue generators, chatbots also serve as research bots or lead generation and brand awareness for businesses to save money. Since each conversation with a customer helps AI-based chatbots improve their understanding of user intent, they self-teach and only improve over time.

Microsoft released a service that allowed different firms to develop their chatbots back in 2019. They gave different firms the tools needed to alleviate administrative tasks using chatbots, which helped Microsoft earn the top spot in the healthcare market. As per Juniper Research, AI can automate 73% of health admin tasks, and the adoption of AI chatbots could help the banking, healthcare and retail sector $11 billion annually by 2023.

We can see AI-based chatbots have been gaining widespread acceptance ever since 2017 based on this study conducted by Statista:

AI Chatbot report 2017 according to statista

AI Chatbot Development Challenges

So far, we have realized the importance of AI chatbots in different business spheres and how they have revolutionized the way customers interact with businesses. We still have a long way to implement the worldwide adoption of chatbots, and there are many roadblocks and pitfalls we should be prepared for. However, there are many chatbot development tools available; firms currently tend to overlook some of the critical aspects of chatbot development. These are the biggest challenges concerning AI Chatbot Development.

1. Limited User Attention Span

Users have got used to the lightning-fast web experience, and with every passing day, the standards of response time is increasing greatly. These users have very limited attention and period for their queries to be answered and expect instant replies. This requires developing chatbots with extraordinary abilities and functionalities. For such requirements, conversational UI plays an important role to mimic human-like conversations, which lead to better customer experiences. Their way of interacting is more social than technological. Hence chatbots need to be natural, creative and emotional for attending to customers successfully. In some cases, AI-based chatbots also fail to render or matching the same empathy a human can. Hence, knowing when to switch to a human agent is crucial in developing a successful AI chatbot.

2. Providing context in chatbots

For any AI-based chatbot to be successful and effective, it needs to be integrated with context and meaningful responses. If an AI-based chatbot has conversations without context, it would be vague and of no use. Building such chatbots can be incredibly challenging for companies as they need to develop and maintain bots’ memory to offer personalized responses efficiently.

To solve such challenges, we leverage machine learning or NLP, which helps the bots understand a conversation’s depths to an extent. NLP comprehends the databases and data sets if the bots are structured in a predefined sequential order, and it converts that into a language that the user can understand. The issue with this solution is that humans do not necessarily interact in a defined order. For this chatbot, developers need to provide intelligent slot filling to effectively store the regular users’ preferences and maintain the bot’s memory.

3. Ensuring the viability of data

Having an abundance of data to train your chatbots is not enough; with quantity, data quality also matters significantly. If you feed your chatbot an abundance of poorly structured data, it works against the desired outcome and makes your chatbots inefficient. With the increasing demand for chatbots to be more efficient by the day, chatbot developers need to develop technologically advanced chatbots, are fed quality data and equipped to deliver the brand identity of the business to their target audience.

Here is an efficient checklist for you to check the viability of your chatbots:

• How is it different from other chatbots available in the market?
• Are your virtual agents delivering to the right audience?
• Does it offer business goals uniquely?

4. Need for chatbot testing

The biggest challenge in chatbot development is the need for continuous and rigorous chatbot testing. Chatbots continuously keep evolving as they work on natural language models. Hence it becomes important for chatbot developers to test and run chatbots for checking their accuracy now and then. How you test a chatbot depends on what kind of method you want to experiment with.

1. Automated Testing of Chatbots

The first method involves automated testing of chatbots. There are many available platforms for automated testing of chatbots, such as Bot Testing, Dimon, Zypnos and more. These platforms allow developers to get detailed reports and results and code test scripts that can be used for all the test cases.

2. Checking the Conversational Logic

This method is used for testing the efficiency of the conversational logic of chatbots. Here a close group of testers conduct manual testing by acting as users and checking the bot for all the possible slots. This method is undoubtedly time consuming and somewhat accurate.

5. Building affordable chatbot solution

Though most businesses have started adopting chatbot technologies to some extent in their daily practices, most small scale and medium scale businesses still shy away from using chatbots due to the high-cost factor. If we talk about chatbots globally, in many countries, chatbots are still considered as a money-sucking feature that is only accessible to the leading brands. Though this perception is slowly fading away, chatbots are still considered a considerable investment.

6. Ensuring chatbot security

Some chatbots on websites look like spams that users will, at all costs, avoid interacting with. This shows the need to focus on chatbots security features just as much as other aspects. However, there are many factors to consider for ensuring overall chatbot security. This makes chatbot development a challenging task.

These are some considerations you should have in mind for boosting Chatbot Security.

• Always run beta testing before launching your chatbot live for use on your website.
• You need to ensure to train chatbot from answering questions that leak critical business information of the company.
• Ensure to use the https protocol for your chatbots as it reassures users that their data is protected.

Predictions of AI Chatbots

Now that we have discussed all possible aspects of AI chatbots and AI chatbot development let us discuss the possible advancements and predictions of AI chatbots.

1. Improvement in sentimental analysis

Chatbots are going to focus on becoming more conversational for increasing communication efficiency, as this is the next step to improve user experience. This chatbot development would leverage sentiment analysis practices to train chatbots with more human-like capabilities. The focus of chatbots won’t be limited to providing effective response and understanding if the customer chat is going positive, neutral or negative and taking necessary corrective actions accordingly.

The sentimental analysis would help AI chatbots recognize –

• Record the entire customer chat/conversation and use sentimental analysis, which will help bots figure out if the users are happy or annoyed.
• Sentimental analysis can help chatbots modify their responses, so they adjust to the customers’ emotions.
• Chatbots would recognize angry customers that can be rerouted to an effective human team to deliver personalized and efficient customer support.

2. Chatbots will behave more in a human-like manner.

Global Market Insights has predicted the overall market size for chatbots worldwide to be over $1.3 billion by 2024. Hence, it is inevitable to avoid or ignore AI-driven chatbots for business communications in the coming years. Chatbots would better use NLP and sentiment analysis with predictive analysis to better understand the intent and conversations regarding the queries.

3. Voice bots will become more mainstream.

We already live in a world where people operate their phone using ‘Ok Google’ and ‘Hey Siri’ and asking the respective voice assistants questions like ‘what’s on my schedule today?’. Forbes conducted a study that predicted that 50 percent of all searches in the year 2021 would be voice-driven. Voice bots provide a seamless user experience which is important for business communications.

4. Using AI in contact centres

A study conducted by Chatbots Magazine concluded businesses could save upto 30% of customer service costs by developing and implementing a conversational chatbot. AI-powered bots can handle basic features like changing passwords, scheduling an appointment and requesting balance without any human intervention.

Thus employing AI chatbots can help businesses save up on human resource spending significantly and provide 24*7 customer service without it hampering the quality of their services which is extremely beneficial in customer-centric businesses.

Wrapping it up!

We learned about how AI chatbots revolutionise every business sphere and make our everyday tasks much simpler and convenient. There are many challenges to fully optimize this technology, but there are equal opportunities and scope. With the right kind of investment and research, AI chatbots can truly transform how we interact with the net and businesses.

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