Although powerful large language models (LLMs) like GPT can power a chatbot with abilities to interpret and generate response to user input, they do not really teach the chatbot how to carry out an effective and pleasant dialog with a user. Additionally, AI is far from perfect and there are always cases where AI cannot handle or handles wrong. Hence the role of a conversational AI designer is critical as they put their wisdom and creativity into an AI chatbot and ensure effective dialogs between AI and its users.
Recently, we have heard more people, especially top technology experts, talk about creating "proactive" AI agents with agentic workflows (e.g. see a recent video by Andrew Ng). Designing a proactive AI agent requires skills. In this article, we present 5 design tips for conversational AI designers to make effective proactive AI agents. In each design tip, we use concrete examples to explain the desired AI agent behavior and show the corresponding Juji features you can use to enable such a behavior.
In my previous blog, I talked about what it takes to build a chatbot using GPT-4, including the engineering efforts required and a rough cost and time estimate. Although it is non-trivial to build a practical chatbot solution for real-world applications, with the right tools, one can build a custom chatbot solution quickly to take full advantage of the state-of-the-art large language models (LLMs) like GPT-4.
As indicated by this post, 84% consumers want to be treated as a unique individual not just a number, while 95% of companies saw 3X ROI from their personalization efforts. Now with the rise of conversational commerce, chatbots become a natural and private channel for brands to engage with users and offer personalized services in one-on-one conversations. In such a conversation, a chatbot can naturally elicit users' needs and wants and then provide personalized help or guidance based on the gathered information.
The Chatbot Tsunami has brought us a flood of chatbots to help automate various business functions, including customer service chatbots that automate customer Q&A, marketing research chatbots that automate customer interviews, and HR chatbots that automate job interviews. Although a chatbot is often made to serve one purpose, users expect the chatbot to perform multiple related functions while serving the main purpose.
As indicated by this Forbes article, 76% of customers contact businesses to make inquiries and get support via text messaging. Now with the required social distancing during the COVID-19 pandemic, more and more consumers choose to interact with brands online.
One of the most intuitive uses of chatbots is perhaps to automate customer service, where a chatbot automatically answers user questions, 24x7. In fact, in almost every chatbot application, a chatbot's ability to answer user questions, especially free-text questions, is always desirable.
