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.
With the launch of ChatGPT plus, more and more organizations started to build their own chatbots. While ChatGPT Plus provides a natural language interface for almost anyone to build a chatbot, it is inadequate for building a chatbot in a business context.
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.
Juji an Artificial Intelligence (AI) company that specializes in powering cognitive AI assistants in the form of chatbots,released a case study, highlighting how a Juji AI chatbot helped the University of Illinois online MBA program (iMBA) to scale out student recruitment.
Juji announced the launch of its new generative AI tool that enables any organization to rapidly generate custom AI chatbots with no code or additional IT resources. These AI chatbots are powered with cognitive intelligence—advanced human soft skills like active listening and reading between the lines, and can be used to scale human teams and automate high-touch, high-stakes engagements 24x7.
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.
Humanity’s shiny new toy, generative AI like ChatGPT, has shown to be very powerful at interpreting users’ natural language expressions to quickly produce a wide range of text responses, from copy-editing text to summarizing a dialog. While AI responses sound quite confident, we have gradually discovered the flaws in those responses. For example, I asked ChatGPT, “Who invented IBM System U and later known as IBM Personality Insights?” It gave me the following response with names of two people, who may or may not even exist. This phenomenon is referred to as “AI hallucination.”
On August 10, 2023, the AI For All Podcast hosted a riveting episode featuring Dr. Michelle Zhou, Co-Founder and CEO of Juji, who joined Ryan Chacon and Neil Sahota to delve into the fascinating world of Cognitive AI.
