The two terms “chatbot” and “conversational AI” are frequently used interchangeably, but the entity to which each term refers is similar but not identical to the other entity. In this blog post, Raffle explains 5 differences between the chatbot and conversational AI.
1. Broadness of Definition
The term “chatbot” is a narrow one that refers to a type of computer program that simulates human conversations in a very structured manner; as its wording implies, a “chatbot” is more of a bot than anything close to real artificial intelligence (AI). The term “conversational AI” is a broad one that refers to AI-driven communication technology, such as chatbots and digital/virtual assistants, and the entities that come under its scope of reference can vary greatly in their extent of closeness to real AI. Generally speaking, the closer to real AI a conversational AI is, the better it is at seeming human to real humans when responding to user queries — yes, even when responding to queries about topics on which it lacks (training) data.
2. Rigidity of Response
Chatbots are robotic entities that cannot think outside the box. A chatbot functions strictly within its programmed rules, detecting answerable questions based on keywords, and delivering available answers based on pre-written scripts. In contrast, today’s conversational AI, at least the types that are not mere chatbots, can answer questions flexibly like a human. Such advanced AI chat can provide elaborative and organic answers that address multiple variations of the same inquiry — thanks to technologies and/or methods such as deep learning, large language models (LLMs), natural language processing (NLP), and natural language understanding (NLU). Strictly speaking (see the “Chinese room” argument), today’s conversational AI cannot think outside the box as well, but they give the impression of being able to do so much better than their chatbot brethren.
3. Complexity of Processing
A chatbot functions strictly within the confines of its programming and preset linguistic data; it is top-down AI with intensive micromanagement from human masters. As such, its conversational processing capability is basic, and its textual output heavily relies on the human masters’ own complexity of thought. This limits chatbots’ ability to handle complex user queries, textual variations, and linguistic ambiguities without human intervention. With conversational AI, however, the more advanced types mimic human intelligence convincingly: they are bottom-up AI with less micromanagement from human masters. Thus, their conversational processing capability is cutting-edge, and their textual output is much less reliant on the human masters’ own complexity of thought. The human masters only really control the tiniest details at the foundational level: for example, which training datasets to use on the LLM at the heart of the conversational AI.
Conversational AI is therefore closer to real AI than traditional chatbots because it appears to have the human cerebral complexity for comprehending natural language, and interpreting user intent and linguistic context accurately to generate relevant answers to user questions.
4. Liveliness of Knowledge
Chatbots have a stagnant pool of knowledge while (the more advanced types of) conversational AI have a flowing river of knowledge. This difference can also be traced back to the top-down construction of chatbots, and the contrasting bottom-up construction of conversational AI. Chatbots are like people who graduated from university because their parents told them to, and stopped pursuing new knowledge thereafter; conversational AI are like willing university graduates who never rest on their laurels by constantly learning new things to become ever more productive members of society. Specifically, conversational AI are regularly fed by their human masters with large volumes of training data to become increasingly better at recognizing patterns and interpreting meaning, so as to match users’ search intent better via responding with natural and contextual answers (or search results).
Like generative AI, a broader category of AI, conversational AI essentially learn from new data input constantly to make progressively better predictions (i.e. better data output) according to the detected user intent and preferences.
5. Degree of Personalization
The biggest potential turnoff for any human receiver of a message is whether or not said message is robotic. This is a known problem with chatbots: their cookie-cutter responses to questions have virtually zero personalization for the human user behind every question. Chatbots are basic, so if customer experience (CX) is not a priority, they are economical solutions that companies can use for handling simple and repetitive customer inquiries. If CX is a priority, however, then advanced types of conversational AI are better solutions for responding to any customer inquiry—from simple queries to sophisticated questions—in a manner that melds machine efficiency with human soul. One such solution is Raffle Chat, an AI chat powered by a search optimization engine.
Raffle Chat processes human text input to generate human-like text output (with links to corresponding data sources) for relevant answers to any type of question, thus empowering your customers and employees to self-serve as never before. The conversational AI experience is designed to be insightful and cordial to fit the mood of serious searches for accurate answers, and if/when it is appropriate, the Raffle AI can be configured to have a more personal touch to its responses.
Helping your customers or employees find the answers they seek, no matter how they phrase their questions, while your business operations can continue with minimal disruption and your customer support agents can focus on more productive tasks? These priceless benefits shall be yours at modest prices.
Learn more about Raffle Chat and how conversational AI software can enable human-like knowledge retrieval for your customers, thus enabling self-service automation that enhances your customer support function. Book a demo of Raffle Chat now to see our AI chat in action, and explore our customer success stories.