Conversational AI solutions are is in its next phase with the emergence of Generative AI. By combining conversational AI solution with generative AI, the conversation has become more contextual, intuitive and free-flowing, like a human conversation. They are now competent in much more than just automating repetitive conversation. More and more companies are adopting conversational AI-driven solutions in their business. As per the August 2022 Gartner’s report, Worldwide end-user spending on conversational AI solutions just within contact centres has reached $1.99 billion by 2022 alone. As a result, it has broadened automation’s use cases to a larger extent and is being used creatively worldwide.
Enhanced Performance in Conversational AI Powered by Core AI Technologies.
Core AI technology is the foundation of AI, and the performance of conversational AI completely depends on it. It enables AI systems to perform speech recognition, natural language understanding and generation, decision-making, etc. So let’s have a look at how the core AI technologies improve the performance of conversational AI.
NLP is a subfield of AI that instructs computers to understand and derive meaning from human language. It mimics the way humans converse. Moreover, the NLP can understand the intent, identify the message’s meaning, and offer relevant responses, thus leading to better customer engagement and satisfaction.
2. Machine Learning
Machine learning studies past data and experience and predicts output. That means it doesn’t need to get programmed; it learns through data training. It improves and evolves through trial and error processes, where it learns to make decisions based on feedback received from the environment.
Hence, it helps conversational AI make predictions and decisions based on data and algorithms.
3. Computer Vision
Computer vision is the ability of AI to recognise objects, scenes, and activities from digital images and derive meaningful information. It can have a wide range of applications, like face recognition features in Facebook; It helps computers detect product defects, helps doctors analyse images, and diagnose conditions more accurately. These technologies can also be used in gaming, education, etc.
4. Speech Recognition
Speech recognition enables AI to identify words spoken and convert them into readable text. The technology allows electronic devices to communicate with humans in natural language conventionally. It makes tasks like data entry and composing emails super fast for users without manually typing them out. Hence, Promotes the hand-free operation of devices.
Robotics are equipped with sophisticated AI algorithms which enable them to grasp and navigate their surroundings, make decisions, and prevent obstacles. Some of the very common examples are Self-driving cars and drones. The electrical components in these robots provide power and control to the machinery. The robot contains a computer program that determines what, when, and how to do a task.
How Will Conversational AI Evolve in the Future?
1. `Increased Personalisation
Since more than 80% of consumers seek personalised customer experience, conversational AI will be seen innovating continuously to meet the expectation at scale. With the help of a powerful recommendation engine, AI solutions will provide expert-like guidance, understand the user’s intent behind the purchase, and suggest relevant products at the right time. Enhancing the overall customer experience.
2. Low-Code Conversational AI Platforms
Simple platforms that do not require much technical effort are in today. Brands are interested in conversational platforms with simple drag-and-drop experiences that can easily implement the bot without building from scratch. Hence, we’ll encounter chatbot providers focusing on no-code platforms mire. And bringing improvements involved in building a bot solution.
3. Rise in AI Adoption in Social Media
Social media has become integral to any business. Reaching out to a vast customer base is possible via social media. Therefore, businesses are deploying AI solutions on these platforms to a great extent. It helps the business keep track of customers’ behaviour, like how long customers are active, which social media platform they prefer the most, why they use the particular platform the most, etc. The AI solutions help study customers’ behaviour and offer a seamless experience.
4. More Natural Conversation
Users will soon least prefer rule-based chatbots that respond based on keywords or phrases. AI chatbot with ML and NLP makes chatbot sound more natural. These chatbots use sentiment analytics, making the chatbot emotionally intelligent. They’ll be able to understand customers’ anger, frustration, and various emotions.
How Are These Technologies Increasing Human-Machine Touchpoints?
Customers can connect to your brand by sending a message to your customer service chatbot. They can contact you via omnichannel platforms like Facebook, Skype, Slack, etc. The 24/7 availability, personalisation and real-time response make the customer journey enjoyable.
2. Voice Assistants
Since improving customer experience is the top priority for many businesses, they are adding voice recognition capabilities to their existing application. Customers use voice assistants to play music, control electronic devices, read the news, check their balance, etc. With just a single voice command, Voice Assistants are designed in a way that they understand and respond to natural language commands. It makes the interaction human-like.
3. Predictive Analytics
Predictive analytics predicts future events or behaviour using data and statistical algorithms from various sources like social media, purchase history, browsing history, and machine learning tools. And help businesses tailor their offerings to individual customers. It anticipates customers’ needs and preferences and helps offer personalised experiences.
What Steps Should be Taken to Get the Best Out of Al Chatbot Technology
1. Define the Scope and Objectives
Depending on the end users, and the AI chatbot can be used for multiple purposes. Suppose you are a thrift shop owner and wish to make a chatbot to take customers’ orders while accepting cancellations.
A chatbot can be used to book tickets and hotels in the travel industry. This shows that the chatbot is a versatile tool to use. Keeping that in mind, list the things you want your chatbot to do. These will help you decide the capabilities of your bot and will give your bot a new direction.
2. Be Transparent
Don’t shy away from your limitations. Be open to the users when they head beyond the scope you’ve defined for your chatbot. let them know that your bot cannot handle something beyond a point. In general, users get a lot more annoyed and disappointed by an irrelevant or incorrect response than they will by a message saying, ” I’m just a bot. It’s hard for me”.
3. Handoff To A Human
Some interactions can be too complex for a bot to handle. Detect these, and pass on the queries to a human agent. It saves a lot of time and sends the queries directly to an agent that can help and would minimise customer effort and frustration.
And because your customers can get swift answers without navigating through multiple support agents, it leads to customer satisfaction.
The Road Ahead: Implications and Future Directions
With emerging AI technology and increased demand for more intelligent and personalised human-bot interaction, the future of AI looks promising. The automation will make chats with AI solutions more robust and rinse out all the automation challenges the business faces.
The architecture and design of AI agents will evolve to the point that interactive AI will be the mainstream for customer service. So, implementing a chatbot according to your customer’s needs and business requirements will significantly impact the customer experience and your business growth.