In the rapidly evolving landscape of higher education, academic advising stands as a critical component in fostering student success. However, advisors often face numerous challenges, from managing large caseloads to providing personalized support. This blog delves into the transformative potential of AI in this domain. Below we first discuss three key challenges in academic advising and how AI can provide innovative solutions. Then we offer a practical guide on applying the NACADA Academic Advising Core Competencies Model to building effective AI Advising Assistants. Join us as we uncover how AI can revolutionize academic advising, making it more efficient, personalized, and impactful for students and advisors alike.
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.
Are you considering an AI chatbot for your business? A simple Google search will present you with hundreds if not thousands of AI chatbot platforms! Almost all of them claim that they are powered by generative AI and all seem to offer similar features, giving the first impression that any of them would do the job.
With generative AI becoming a hot topic (again), CXOs started adding AI projects, especially implementing an AI chatbot like ChatGPT for business, on their to-do list. While a chatbot powered by generative AI may be a game-changer for business, investing in a chatbot is not cheap nor trivial. So it is worth asking first: does your business really need an AI chatbot? We suggest that business leaders answer the 3 questions below to quickly determine whether it is worth investing in a chatbot for a line of business.
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.
What is "conversational"? By the Merriam-Webster dictionary, conversation is defined as an "oral exchange of sentiments, observations, opinions, or ideas". Because of the exchange, one-on-one conversations are often considered the most effective way for humans to engage with one another.
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.
With the popularity of ChatGPT and more recently AutoGPT, more and more organizations (or individuals) are considering the adoption of a chatbot for their website or proprietary applications (e.g., a learning program website or a mobile healthcare application). The pressing question is: should I build or buy one?
Companies around the world are constantly evaluating how to best reach and/or serve their customers, exploring ways to better connect with customers, while always keeping a keen eye on the resources needed to do so. Higher education is no different. It too needs to cut through the clutter and create a connection with potential students, and continue to build the relationship even after those students are part of their university environment.
