AI maturity toolkit for tertiary education
AI is already having a significant impact on education. Across the UK's tertiary education sector, universities, colleges, and skills providers are experimenting with, adopting, and embedding AI technologies.
They are exploring how these technologies can enhance student experiences, improve learning outcomes, and increase staff efficiency.
Yet every organisation is different, and so understanding your college or university’s current AI maturity is crucial for setting your path for progression.
To help plan the AI journey for your organisation, we have developed an AI maturity model designed for tertiary education. By applying this model you will:
- understand where your college or university is on its AI journey – crucial for strategic decision making, allocating resources, mitigating risk.
- find the tools and resources most relevant to your circumstances to plan activities.
- become part of community within tertiary education with a shared language.
For each of the five stages in the model, we have developed an AI toolkit with a wide range of resources, all aligned with our responsible use of AI approach.
The tools at each stage are grouped into five themes to help you identify what will be most useful for your exact purpose:
- Strategic adoption of AI: explore how AI aligns with your institution’s vision and goals.
- Students and learners: enhance personalised learning experiences through AI-driven solutions.
- Supporting staff: empower educators and administrators with AI tools.
- Maintaining academic integrity: address ethical considerations and transparency.
- Safe and responsible use: navigate AI’s potential risks while maximising benefits.
The tertiary sector as a whole is moving along the maturity model. When we produced the first version, in 2021, most organisations were either thinking of starting their journey, or at the ‘approaching and understanding’ stage.
Today, at the time of writing, most organisations are well into the ‘experimenting and exploring’ stage, and in the process of making AI operational. As AI is changing rapidly, we are producing detail checklists for the most relevant stages.
First stage: approaching and understanding
The first stage involves understanding the foundational concepts of AI, recognising its benefits, and identifying challenges.