Someone told me the other day that we live in strange times – we ask our watches to make calls and ask our phones to tell us the time. In a way, they were right.
It’s the twenty-first century, and you can do even more mind-blowing things like talk to computers, order pizza, or close the blinds by speaking with intelligent virtual assistants. Inevitably, the future is here.
In fact, the chatbot evolution started quite some time ago. More specifically, in 1966, Joseph Weizenbaum, an MIT professor, created the first conversational interface, Eliza. This computer program simulated a human psychiatrist by responding to user questions with pre-written responses.
Eliza was a simple rule-based conversational interface, but its creation laid the foundation for modern conversational AI technology. If you’re curious about how it developed and how you can use it in your business, read on.
What is conversational AI?
Conversational artificial intelligence (also called generative AI) is a technology that enables a computer to have a multi-turn dialogue with the user and answer their questions creatively.
Systems powered by conversational AI, such as AI chatbots, language models (e.g., ChatGPT), or voice assistants (e.g., Siri, Alexa), can communicate via text, voice, images, and videos. They incorporate advanced algorithms like natural language processing and machine learning that help them have a free-flowing, multi-sentence dialog with the user.
By going a step further and integrating conversational AI with other technologies, such as computer vision and natural language generation (NLG), conversational AI systems can accomplish more advanced tasks, such as recognizing images or mirroring human behavior.
Conversational AI tools aim to solve user problems and provide a human-like experience. They are used in various fields, including e-commerce, customer service, and healthcare.
The elements of conversational AI
Conversational AI tools use artificial intelligence algorithms that enable a computer to communicate in a human-like manner. Let's explore them to understand their role in the process.
Natural language processing (NLP) is the vast area of conversational AI that uses, among others, linguistics and data science methods to enable computers to comprehend human language and respond accordingly.
Simply put, systems that use NLP can analyze large amounts of unstructured data, including written or spoken words, phrases, and sentences, and structure them to interpret and understand their meaning.
Thanks to NLP, virtual assistants can understand complex user utterances and respond creatively in a way that feels natural to the recipient.
2. Machine learning
Machine learning (ML) is a part of artificial intelligence that enables language models to recognize patterns in human language. They can later use that knowledge to answer user questions autonomously.
By analyzing vast amounts of data, ML algorithms can learn how to solve specific problems, make predictions, and make decisions without being explicitly programmed. It means that conversational interfaces based on ML can improve their accuracy with each conversation they have with the user.
Systems based on NLU use structured data to analyze the grammar and context of the user input. Thanks to that, the computer can understand the relationships between words and phrases. Moreover, NLU allows the computer to distinguish homonyms in human speech or understand language nuances.
4. Natural language generation
Natural language generation (NLG) is an NLP component that empowers machines to write in a human language. It lets the computer convert text into a voice output when needed. NLG allows conversational interfaces to analyze complex text inputs and provide condensed summaries.
5. Automatic speech recognition
The last element on the list is automatic speech recognition (ASR). It's a technology that enables computers to understand and transcribe spoken language. ASR is used in voice assistants, dictation software, and other similar programs that require the ability to recognize speech.
How does conversational AI work?
You already have a brief understanding of technologies that let computers carry a human-like dialogue with the user. Now, you can learn how they empower AI assistants throughout the conversation.
The process starts with input generation. At this step, the user initiates the interaction. Depending on their technology, they can enter their query (keyword, phrase, question) via text or voice interface.
Next, the system conducts the input analysis. Once the user forms a question, the bot uses NLP and NLU to unjumble it and define its intended meaning.
The analysis is done – it’s time for the output generation. Thanks to NLG, the AI agent can formulate the appropriate response, translate it into a human language, and send it to the user via text or voice.
The last step isreinforcement learning. Machine learning allows the system to learn new things and patterns while interacting with each user. Then the computer can use that knowledge to improve its accuracy and responses over time.
Why do businesses need conversational AI?
How people shop and search for information has shifted communication to online messaging. To be successful, brands need to provide round-the-clock and multi-channel customer support. This can be challenging and costly to achieve, but conversational AI solutions can help.
Lower customer service costs
Offering 24/7 human support can help you meet rising customer expectations and get higher customer satisfaction rates. However, filling all the required customer service positions round-the-clock might be costly.
Maintaining a customer service team is an ongoing expense for businesses as well. The turnover among customer service teams is 45%, two times higher than in other departments.
According to the United States Bureau of Labor Statistics, the average tenure of a support agent is only 2.6 years or lower in most cases. Many agents find their work strenuous or stressful, leaving it for jobs requiring less repeatability. Companies that provide human customer support must spend more on recruitment processes and employee training.
Curiously enough, data shows that customers don’t necessarily need to contact a human while solving their problems. They’re content as long as brands let them submit their requests efficiently and solve their problems quickly. That’s where conversational AI can jump in.
AI-powered chatbot software can answer common user questions instantly and 24/7. Intelligent agents can work as the first customer touchpoint and answer information-seeking questions regarding payments, products, or orders.
What’s more, if artificial intelligence can't resolve the customer issue, it can route the person to an available human agent so they can provide more information. As a result, your agents can focus on more challenging cases and won’t get bored with repetitive tasks.
Incorporating conversational AI into your customer service strategy lets you slash costs while providing the service your customers expect and keeping your team happy.
Boost customer engagement
Over 50% of consumers want brands to provide a personalized customer experience. Conversational AI can carry on human-like interactions and let the customer feel understood.
Let's take website chatbots, for example. They can send proactive chat invitations that attract the user's attention. Once the bot connects with the visitor, it can support them through their shopping journey – provide information about products, and educate them about the payments process and delivery rules.
Moreover, apart from nurturing the website visitor by providing necessary shopping information, a chatbot can personalize the customer experience. It can use historical and real-time data like the user name, location, shopping preferences, or previous purchases to provide personalized recommendations and make the messages sound natural.
As AI interfaces can understand the context of the user question and catch the nuances in the human language, their answers are more likely to be witty and to the point, making users more engaged in the flow.
Besides, conversational AI can be a treasure trove of knowledge about your customers. By analyzing your past customer interactions, you can find trends in their questions, such as learning how they speak and the terms they use. That can help you better understand their needs and optimize your website communication for a better customer experience.
More companies are applying conversational AI to improve the accessibility of their products and websites.
Not sure what accessibility means?
In short, the term refers to the design of products, devices, services, or environments for users with visual, auditory, motor, or cognitive disabilities. However, in the broader sense of this word, accessibility refers to providing equal opportunities for every user.
It means considering the user's capabilities and other circumstances like their surroundings, the device they’re using, or the stability of their network connection. Needless to say, conversational AI can improve the accessibility of products or services, but for every user, it might be a different case.
For instance, you can connect a conversational assistant with your smart-home devices and use them to switch the lights, check the weather, order food, or block your credit card. The best thing? The only thing you have to do is to say a couple of voice commands.
But that's not all. Conversation AI also provides text-to-speech dictation and language translation. It can help users navigate websites or apps even when they can’t type or know the language you provide your services. Conversational AI has become a great convenience for various kinds of users.
Scale your services
Expanding your customer service while keeping it at a high level requires careful planning and effort. As you already know, conversational AI can help you connect with a broader audience while lowering costs. It can be integrated across various platforms allowing you to support your customer across multiple communication channels.
Secondly, AI bots can help you reduce the average wait time too. A website chatbot can work as a frontline of your customer service and help ensure every customer gets help immediately.
Plus, conversational interfaces can provide uninterrupted services no matter how many customers need assistance simultaneously. This functionality is beneficial when you experience spikes in queries or during the shopping season when your team is engulfed in questions.
Popular conversational AI use cases
Conversational AI has a wide range of applications where it can handle customer inquiries, provide personalized assistance, and improve your team’s efficiency. Let’s take a look at some of them.
AI assistants can enhance patient engagement and improve healthcare services. Analysts predict the healthcare chatbot market will be worth over USD 543 million by 2026.
Symptom checking and diagnosis
Patients often have pressing questions regarding their health. Although these questions might require fast answers, they only sometimes need human attention. In such a case, they can be answered by an intelligent agent.
Conversational AI solutions can provide early symptom assessment and triage. Their advantage is that patients don’t have to leave their homes and wait hours and days for preliminary diagnosis. This is especially helpful when the patient has complicated access to the healthcare system, lives in a rural area, or can’t leave their home independently.
An AI bot can not only pre-diagnose the patient. It can provide them with addresses of facilities they should visit or call in case their condition requires immediate medical help. By consulting an AI agent, the patient can better understand their health problem and take faster action.
As an added plus, clinics that use conversational AI for preliminary diagnosis can reduce the number of nonurgent calls and on-site visits. This way, they can devote more time to helping patients requiring immediate assistance.
Do you remember the last time you had to call your healthcare provider, but nobody answered? For many patients, managing medical appointments can be a frustrating task. However, conversational AI has emerged as a remedy for issues like scheduling.
A conversational AI system lets patients book, reschedule, or cancel their visits seamlessly without connecting with a human. Moreover, it can instruct the patient on what documents they should bring, how they should prepare themselves, or what their medical procedures will look like.
Mental health support
Only 50% of patients suffering from mental problems in the US get professional help. Conversational AI can bridge the gap between healthcare professionals and patients and supplement human therapists.
AI chatbots, accessed by patients through their phones, can create a safe space for them to communicate and express their feelings. Take, for example, Woebot, a bot based on Cognitive Behavioral Therapy. It engages the patient in therapeutic conversations. Woebot is used by clinicians to support their patients, monitor their mental health, and detect destructive behaviors.
Remembering that conversational AI can’t replace actual therapy would be best. However, it can surely help professionals increase the efficiency of their work.
Forty-five percent of consumers interact with their financial providers through online channels only. It means almost half of the bank’s users don’t need to connect with a human while managing their finances. They can connect with an AI agent instead.
Conversational AI tools offer a convenient way for clients to handle their issues quickly and independently. These tools can educate every user about their budget and spending. They can even schedule payments and update them on customers' credit scores.
Moreover, clients can use conversational AI tools to quickly block their credit cards with a simple command, which is especially useful when the client can’t find their card or thinks it has been stolen. Being available 24/7, AI assistants give the customer a sense of security.
Many bank clients who fall victim to payment fraud or online theft close their banking accounts. Conversational AI can help banks and financial institutions guard their clients' finances.
An AI assistant can monitor the customer’s banking activity and learn about the trends in their financial operations. Thanks to that, it can detect suspicious transactions on a client’s account and inform them about it, preventing theft.
Conversational AI can handle customer support requests. But businesses can also use it to assist customers in shopping activities to increase conversion rates.
With its ability to deliver a personalized customer experience through machine learning, a conversational agent can learn about customer preferences. It can then use gained insights to help customers find the product they’re looking for and discover options they might have missed.
An example of a brand that uses conversational AI in its customer service is Sephora. The brand has been using a chatbot to educate customers about its cosmetic products, offering tutorials, skincare advice, and online purchases.
Additionally, by implementing augmented reality (AR) technology in its assistant, Sephora lets customers virtually try makeup to see whether it suits them. This way, the brand takes its online customer experience to the next level.
While chatting with the customer, the AI assistant can gather plenty of information about your customers’ needs and preferences.
By analyzing your conversation archives, you can detect trends in customers' behavior and their intent. Having complex and up-to-date insights about your customers can optimize your store experience and create better communication.
Internet of things
The internet of things (IoT) concerns the network of devices with internet access that can communicate. Such devices include smart speakers like Google Home, autonomous cars, or wearable fitness trackers that monitor user performance and save data.
Let's focus on smart speakers now, as they can function as the interface for conversational AI. Some come with in-built assistants like Siri, Alexa, or Cortana, while others let you connect them with assistants available within your mobile device.
When connected to conversational AI, voice commands can activate smart speakers and help you complete various tasks. They can make a call when you can’t find your phone, play your favorite music on Spotify, and send you reminders about your child’s kindergarten performance.
Challenges of conversational AI
Like any other AI technology, conversational AI isn't without its challenges. Here are the common ones to take note of.
Languages evolve faster than you think. Globalization and the mixing of cultures influence how people speak, such as the choice of words and grammar, not to mention dialects or jargon. Let's not forget that speakers of one language can also speak differently depending on their generation, social background, or region.
Therefore, although conversational AI is getting sensationally good at understanding human languages, intelligent assistants still need a lot of human help to pick up language nuances, accents, and structural changes.
The human factor in the language input is another challenge, especially for voice assistants. When you speak, you not only say words but convey emotions such as sadness, fear, or disgust.
To fully understand the user intent and react accordingly, conversational agents must properly define the message within the context and consider the mood.
Privacy and security
Conversational AI needs to gather user data to respond to user inquiries. However, processing vast amounts of data entails security risks.
While creating and maintaining conversational AI apps, brands must focus on implementing security features and monitoring systems. This way, they can secure the user’s privacy and take a step to establish user trust.
Language models are as good as the data used to train them. Using biased data to train your conversational agent will significantly influence its outputs.
Because of that, AI agent creators need to ensure that the data used in the training process is unbiased and inclusive. That can take a lot of time and manual work and, therefore, might be time-consuming, especially while developing large language models.
The emergence of conversational interfaces like ChatGPT caused a massive interest in conversational AI. However, although users are eager to play with intelligent agents and language models, some are still quite apprehensive about using them to solve more severe problems.
To increase conversational AI adoption, companies need to work on its accuracy and reliability as it can help to increase user trust. What’s more, businesses need to educate their audience about the benefits and capabilities conversational AI provides.
In a nutshell
Conversational AI is experiencing its renaissance. It's transforming industries, jobs, and lives.
Although conversational AI can spare businesses a lot of effort, certain challenges are being introduced along the way. Therefore, conversational AI shouldn’t be treated as a one-size-fits-all solution but rather as a convenience that works best when connected with other solutions and combined with human expertise. Only then can it provide the best possible outcomes.
Artificial intelligence's responsible development and use are key to its long-term success. Learn more about AI ethics and best practices to shape the future of AI.
Capture key customer moments
Analyze, optimize, and scale sales conversations and improve sales performance with conversation intelligence software.
Daria is a product content writer at ChatBot. She’s passionate about conversation design and UX, and most of all, she’s a huge fan of user-friendly chatbots. She finds sheer pleasure in sharing her knowledge and insights about them with others.
Capture key customer moments
Analyze, optimize, and scale sales conversations and improve sales performance with conversation intelligence software.
What Is Conversational AI? How It Enhances Customer EngagementLearn what conversational AI is and how it works. Explore ways to use AI bots and intelligent assistants to grow your business faster and smarter.https://learn.g2.com/conversational-aihttps://learn.g2.com/hubfs/conversational%20AI.jpg2023-03-23 20:46:29Z
Daria ZabojDaria is a product content writer at ChatBot. She’s passionate about conversation design and UX, and most of all, she’s a huge fan of user-friendly chatbots. She finds sheer pleasure in sharing her knowledge and insights about them with others.https://learn.g2.com/author/daria-zabojhttps://learn.g2.com/hubfs/PXL_20230208_200651919%20(1).jpghttps://www.linkedin.com/in/dzaboj/
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