If you’ve ever asked a virtual assistant like Siri or Alexa for a weather forecast or checked an order status using a chatbot or a messaging app, you’ve experienced the power of conversational AI. This artificial intelligence tool uses natural language processing (NLP) to understand and respond to human language.
But conversational AI involves much more than just virtual assistants and chatbots. It’s a rapidly evolving field with a wide range of applications and great potential for innovation.
According to a report by Grand View Research, the global conversational AI market size was valued at USD $12.9 billion in 2020 and is expected to grow at a compound annual growth rate (CAGR) of 37.3 percent from 2023 to 2030. This exponential growth reflects the increasing importance of conversational AI in businesses and industries worldwide.
Let’s look at the future of conversational AI and explore seven key conversational AI trends that will shape the field in 2023 and beyond.
Conversational AI: Where it's headed
Conversational AI has come a long way in recent years, and it’s continuing to evolve at a dizzying pace. As we move into 2023, a few conversational AI trends will likely take center stage in improving the customer experience.
1. Conversational AI-powered search
One of the most significant trends in conversational AI is the use of conversational search engines. Conversational search engines allow users to interact with the search engine in a conversational way, using natural language. This means that users can ask questions like they would ask a person, and the search engine will understand and provide relevant results.
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The rise of conversational search engines is changing how people interact with technology. Rather than typing in keywords and phrases, users can have a natural conversation with their devices. This trend will likely continue to grow as more people become comfortable with voice-based search and expect a more conversational experience.
2. AI chatbots to deliver personalization
AI chatbots have been around for a while but are becoming more sophisticated and personalized. Chatbots are no longer just for answering simple questions or providing basic information. Here are some ways chatbots can deliver personalization:
- Natural language processing: Chatbots can use natural language processing (NLP) to understand user intent and provide personalized responses.
- Customized responses: Chatbots can customize responses based on the user’s previous interactions with the bot.
- Tailored content: Chatbots can offer tailored content such as articles, videos, or products based on the user’s interests or search history.
The key to the success of AI chatbots is their ability to understand the context of a conversation and provide relevant responses. As chatbots become more advanced, they will better understand what a user is saying and why they are saying it. This will allow them to provide even more personalized responses tailored to users' needs and preferences.
3. Voice assistants
Voice assistants like Amazon’s Alexa, Google Assistant, and Apple’s Siri have become ubiquitous. These devices enable users to control their smart homes, play music, and get information simply by speaking. As these voice assistants become more advanced with better speech data, they will become even more integrated into our daily lives.
Voice assistants are already being used in a variety of industries, including:
- Media and entertainment
They can be used to schedule appointments, order prescriptions, and even book hotel rooms. As voice assistants become even more ubiquitous, they will become even more powerful tools for businesses to engage with customers.
4. Conversational AI for the Metaverse
The Metaverse is a virtual world that is becoming more popular, especially among younger generations.
A significant number of global executives – 71 percent, to be exact – are optimistic about the positive impact of the Metaverse on their organizations, with several brands already jumping on the bandwagon.
Facebook/Meta invests heavily in developing advanced conversational AI technologies, which can add a human touch to every aspect and facilitate natural conversations in diverse scenarios.
As the Metaverse grows, we can expect to see more businesses using conversational AI to engage with customers in this new environment.
5. AI chatbots with high emotional intelligence
One of the most exciting trends in conversational AI is the development of chatbots with high emotional intelligence. These chatbots are designed to recognize and respond to human emotions, making them even more effective at engaging with customers.
Although emotional AI is in its infancy, it holds immense potential to transform how we engage with technology. Chatbots with emotional intelligence can be used to:
- Provide emotional support
- Help customers deal with difficult situations
- Even detect when a customer is unhappy and offer solutions to address their concerns
AI chatbots can leverage AI and machine learning algorithms to analyze large human interactions and emotional datasets. A chatbot’s model can learn to recognize and respond to various emotional states through training data, enhancing the technology’s ability to provide a personalized and empathetic customer experience.
6. Proactive customer service
Conversational AI can also improve customer experience by providing proactive support.
For example, chatbots can monitor a customer’s activity on a website or app and offer assistance or recommendations before the customer asks for help. This can save the customer time and effort and make them feel more valued and cared for.
Furthermore, conversational AI can analyze customer data to identify patterns and trends. It will allow businesses to anticipate and address customer needs before they even arise. This can help reduce customer frustration and improve overall satisfaction.
7. Collecting AI training data
Collecting data for training voice assistants can be time-consuming and challenging. To effectively collect data, it is important to use sources such as:
- Recordings of real-world conversations and transcriptions of spoken utterances
- Annotating data is crucial and should include speaker identification, intonation, and emotion
- A balanced dataset with different speakers, genders, accents, and emotions should be collected
- Clean data that removes background noise, errors, and outliers are also essential
If history is any indication, then it’s likely that the development of conversational AI will continue to be a fruitful avenue of computer science.
The next five years will bring more streamlined AI experiences, security features that enhance those interactions, and more. Conversational AI trends in the next few years will be brighter and more accessible than ever before.
[ Check out our primer on 10 key artificial intelligence terms for IT and business leaders: Cheat sheet: AI glossary. ]