How an AI Chatbot Works
In 2020, US-based eCommerce experienced a 30% growth, and accelerated the shift in physical to digital shopping by nearly two years. As a result, one of the biggest challenges companies must navigate is rising customer demands. But what’s the best way to meet people’s needs and ensure a smooth shopping experience?
According to a recent survey, 90% of consumers rated an “immediate response as important or very important” for their customer service expectations. Meanwhile, 75% of people expect help within five minutes.
One tool to help address customer expectations is conversational artificial intelligence (AI), which can help relieve stress on call centers. The idea is to automate redundant, repetitive tasks while freeing up human brainpower to address more complex challenges. Businesses of all sizes can benefit from using a bot or AI chatbot platform to streamline customer service requests. But the decision to use AI requires careful consideration across a number of dimensions related to your business’s use case, technology accuracy, and ethics.
Here’s how an AI chatbot works and how to choose the right type of technology for your business.
What is artificial intelligence?
Put short, artificial intelligence (AI) is the practice of using technology to emulate human behavior. AI can be a robot voice assistant, such as Apple’s Siri or Amazon’s Alexa; but it can also be software in the form of a chatbot.
AI is already everywhere, integrated into our everyday lives. When you drive your car, for instance, the GPS in your vehicle relies on a network of AI algorithms to calculate directions and traffic patterns, while traffic lights use AI to ensure safe coordination between vehicles and pedestrians. If you use a smartphone to make calls or listen to music, AI is what translates computer data into sound waves that human ears and minds can interpret.
Here’s a short, five minute video to walk you through what artificial intelligence is and how it works:
Artificial intelligence uses engineering and data science concepts to build high-performing technology. Important terminology to know includes:
Data is known to be one of the most valuable assets in the world. But it’s tough to translate raw information into meaningful, actionable insights. This challenge has given rise to data science as a profession and field. Data scientists are responsible for connecting data points into valuable business intelligence and narratives.
AI platforms use networks of statistical concepts and algorithms to find patterns in data such as numbers, words, images, or clicks. This practice is known as machine learning.
Deep learning is a more robust form of machine learning that computers use to find subtle or small patterns that are otherwise challenging to detect. The outcome of deep learning is a unified prediction based on input data.
Inspired by the mechanics of the human brain, neural networks are algorithms that recognize relationships in data. The idea is to use technology to replicate how the mind forms connections and makes decisions.
To be effective, however, AI needs to go through a process of learning. During supervised learning, data is labeled so computers know exactly what patterns to seek out. With unsupervised learning, data remains unlabeled and machines have free range to uncover patterns.
To learn more about these concepts, check out this resource from MIT Technology Review.
Types of AI
One of the most important discussions on the use of AI is around ethics.
“Experts say the rise of artificial intelligence will make most people better off over the next decade, but many have concerns about how advances in AI will affect what it means to be human, to be productive, and to exercise free will,” wrote Janna Anderson, Lee Rainie, and Alex Luchsinger for the Pew Research Center.
The pace of automation is happening faster than companies can create new jobs, with women’s careers being disproportionately affected and resulting in a lack of diversity in the field. These issues have led to some bias and skepticism towards AI, and how algorithms process information. It’s important to remember, however, that in this current moment computers don’t create AI — humans do.
For these reasons, especially given recent pressures consumers are putting on brands to act with integrity, it’s important to have careful consideration when choosing this kind of technology for your business.
How will AI impact your core business? What will be the consequences? The key is to choose technology that brings added value to the customer experience.
Here is a breakdown of the types of artificial intelligence systems and its accompanying technology operating behind the scenes.
Natural language processing (NLP)
This field sits at the intersection of computer science, linguistics, and artificial intelligence, and focuses on training algorithms to interpret natural language. The idea is that a computer can listen to or read what a person is saying and then translate that information as insight. NLP is particularly important in conversational settings, such as when a person engages with an AI chatbot or voice assistant. The technology varies widely in its sophistication.
AI is capable of recognizing people. Facial recognition is an AI application that’s relevant to use cases such as surveillance, personal identification, and market research. Some AI bots are so sophisticated that they can perform sentiment analysis based on a person’s facial expression.
In addition to recognizing faces, AI can identify patterns between photos. If you’ve ever needed to fill out a captcha form, you’ve likely seen this idea in action.
Artificial general intelligence
Currently, AI can’t perform many of the tasks people can. Even though machines have some ability to think and respond like humans, they cannot feel empathy or emotions., although there is some academic debate as to whether artificial general intelligence is possible.
With regards to chatbot AI, solutions have a range of “thinking” capabilities, though some platforms are more advanced than others. It’s important to keep in mind that “smarter” AI isn’t necessarily better AI, and the best approach is to choose the right solution and capabilities for your business needs.
Limited memory AI
Also known as a limited memory machine, limited memory AI learns from historical data in order to make decisions. The majority of artificial intelligence systems fall within this group. For instance, image recognition and NLP algorithms can make decisions on the fly by remembering stored information.
A reactive machine is basic AI that does not store information in its memory, and makes decisions based on what it observes in the moment. Unlike other types of machine learning, its goal is not to identify patterns or predict future actions, but rather complete immediate tasks.
Tying it all together
Not all of these AI types are relevant or necessary for your business. Choosing the right solution means understanding your needs by identifying exactly what tasks require humans or machines. One shortcut to start this process is to take inventory of repetitive tasks that consume the most amount of time in a person’s day.
In addition, keep in mind that the types of AI listed above aren’t set in stone, nor is it an official categorization from a designated source. To date, there are no unified, regulatory bodies for setting AI standards, which leaves room for immense opportunity in the industry.
Many AIs weave together a range of technologies into defined solutions for specific goals. Choosing what’s right for your company means getting focused on your customer experience objectives.
See chatbot AI in action
Seeing AI in action, and experiencing it as an end user, can help you determine the right technology for your business. Whether you’re a small business owner or team leader in a large corporation, you’re likely facing customer experience pressures, especially since 80% of US consumers expect better service even during the pandemic.
Here are three examples of how an AI chatbot can fit into your business.
The coronavirus has overwhelmed health care systems to such an extent that there aren’t enough resources to treat everyone needing medical attention.
During this time of crisis, chatbots have provided an added level of support. UCLA Mattel Children’s Hospital, for instance, launched an emotional learning robot named Robin to engage with immunocompromised kids.
Robin is a cartoon-like robot with a plastic body that moves around and uses facial recognition to understand a child’s emotions, and builds responses by replicating patterns from previous experiences and memories. With its collection of human interactions and emotions, the AI can respond to a child’s needs situationally through conversation or singing songs.
Robin is the subject of a research study seeking to understand the use of robots in helping children recover from illnesses. The bot is currently focused on helping kids who are in medical isolation due to autoimmune challenges.
Some of the most effective chatbots are ones that simply route people to the information they need to make a decision. For instance, institutions like the Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO) have been using conversational chatbot technology to support public health measures.
One example is Clara, a symptom self-checker bot that helps people determine whether they should get tested for COVID-19. By using very simple data science techniques, the chatbot helps people figure out what actions to take based on their symptoms.
The rule-based chatbot uses established guidelines for symptom management with users simply clicking buttons rather than inputting natural language.
A natural language processing chatbot can help streamline important, but time consuming, operations in your business.
These days, many solopreneurs and independent business owners are struggling to stay afloat. They’re cutting staff, wondering how to keep their doors open, and figuring out how to keep customers safe. One approach companies are taking, for instance, is to limit the number of customers entering retail locations.
Chatbots can help time-strapped business owners address shoppers’ questions while also managing the customer experience with things like taking online reservations.
Simple natural language processing technology allows this type of bot to interpret customers’ answers to basic questions. If you’d like to try building a chatbot for appointment bookings, download this chatbot template from ManyChat.
You don’t need a technical background to get started with chatbot AI, and there are many available tools that can help bring your ideas to life. Here are a few resources to you get started:
- This guide discusses how to create a basic customer service bot.
- This roundup of the 15 best chatbots of 2021 can equip you with additional ideas or inspiration.
- This collection of example bots features downloadable templates you can try yourself.
There are a number of efficiencies you can build into your business without the use of sophisticated tech. Save time, free up brainpower, and give your customers a wonderful experience. With the right intentions and use, AI has the potential to be a force of good for both businesses and humanity.
Level up your brand communications with a chatbot. Sign up for a free trial with ManyChat.