AI in higher education

Last changed: 12 December 2023

The launch of Open AI's ChatGPT in the autumn of 2022 has given us new opportunities/challenges and yet another new digital competence for us to handle.

Today, there are several chatbots that can answer advanced questions and quickly create texts, images, etc. based on various requests. The position of Chat GPT, possibly the most known chatbot, is being challenged by, among others, Amazon's Bedrock and Bard from Google. In addition, generative AI is currently being integrated into Office 365, Microsoft Bing and Google's search tools.

Below are some abbreviations that may be useful to know!


Artificial intelligence (AI) is the ability of computer programs to mimic the natural intelligence of humans.

Generative AI is a branch of artificial intelligence (AI) that focuses on creating new content based on training data

for example text, images, sound, video, music, etc.


Large Language Models (LLM)
(ChatGPT is based on GPT* )
LLM is the machinery that allows today's AI services to generate text

*GPT = Generative Pre-Trained Transformer.


Multimodal LLM (MLLM) is an AI model that can process and generate multiple types of data, such as text and images.


AI is developing rapidly and is affecting us in higher education to an ever-increasing degree. AI support will be part of everyone's everyday life and there are many opportunities but also challenges and risks.

Until the autumn of 2023, much of the universities' focus has been on how we can manage the risks with AI and Cheating, but now we need to talk about how AI will affect all the "pieces of the pie" in the picture on the right.

Read more about AI support in the headings below.

AI and cheating

AI support for teachers

AI support for students

AI support for accessibility and Funka

AI support for PhD students

AI support for administrators

Important to know

If you test new AI services, don't forget:

  • Currently you often need to create private accounts to explore many of the new AI services on the market (and several cost money).

  • Critical Thinking: Be aware of that AI-generated material may contain inaccuracies, distortions, bias, and copyrighted material.

  • Security awareness: Pay attention to security aspects when testing AI systems.

  • Privacy Protection: Be careful about what information you share with AI to prevent the spread of sensitive and proprietary information.