AI for the Rest of Us: Lessons from our “AI for Beginners” Staff Workshops

This article by Jenny McGarvey and Dr Lisa Harris reflects on a series of “AI for Beginners” workshops delivered to university staff, examining staff attitudes towards generative AI, identifying key training and support needs, and highlighting the importance of clear guidance, practical examples, and ongoing AI literacy development across the institution.

Over the past 18 months we have taken part in a number of GenAI-related developments, from teaching digital skills, to module assessment updates, to Community of Practice participation. While it’s been great to see the network and interest evolving, it became obvious that we were increasingly engaging with the same group of enthusiastic early adopters – leaving out a large proportion of university staff and students.

The idea behind our “AI for Beginners” staff workshops was to reach a different group of people who, for various reasons, had not yet experimented with GenAI tools, nor considered their broader implications. This might be because they lacked confidence, fearing they were already being left behind, or they considered it to be solely a “technical issue”, or perhaps they just hoped it would all go away. We wanted to encourage the growth of a community beyond the workshop itself, where people could meet up and try things out in a friendly and supportive environment.

A few numbers

From May to July 2026, we delivered six ‘AI for Beginners’ workshops, three in-person and three online, open to all staff. A total of 180 staff registered across all the workshops, with 84% registering for online sessions. 167 staff attended, showing a registrant-to-attendee ratio that we were exceptionally pleased with, and that also perhaps illustrates how keen certain staff are for this kind of training. Approximately 54% of attendees were in professional services roles, 24% academic roles, 12% researcher roles, and the remainder in roles that could not be obviously categorised.

Feedback from attendees

One of our key goals for the workshops was to assess the appetite for staff AI beginner training, and if there was one, what staff wanted beyond the initial workshop. We established this in two different ways:

1. A discussion section of the workshop on what excites and scares people about AI.

2. Post-workshop questionnaires.

Both revealed some common themes, which we’ve summarised below.

Workshop discussions

A workshop discussion based on what excites and scares colleagues about AI gave us lots of useful insights. While these conversations were insightful in both the online and in-person workshops, the discussions were particularly engaging in person. However, this contrasts with the preference for online sessions that was demonstrated by the vast majority of staff registering for online workshops.

There was a sense of uncertainty about what colleagues could and couldn’t do within the remit of the University’s AI policy, and where they could access relevant support. This is something that we have also identified amongst students, showing that staff and students share many common concerns. With this in mind, we considered inviting students to join the workshops to give the student perspective, but as the workshops took place in May and June, students were either busy with exams or preparing for other summer commitments.

This general feeling of uncertainty, paired with the knowledge that a lot of staff have not yet engaged with AI literacy training, speaks to the need to maintain up-to-date asynchronous resources to

provide support for staff at the time of need, rather than through timetabled workshops. Attendees also wanted specific examples of what staff had done with AI in their particular setting, so they could relate to realistic uses.

Post-workshop questionnaires

We have divided questionnaire findings into staff needs and wants.

· Needs:

•  To develop general AI literacy skills (including prompting, understanding AI’s limitations and capabilities, and using particular tools).
• Clarity around expectations – many colleagues had quite specific questions about:
• What was allowed/not allowed in terms of IP.
• Data sharing.
• The functionality of current tools within the Microsoft/Copilot environment (e.g. integrations into Word, Excel etc.).
• Using AI for productivity and saving time (including for administrative tasks and report generation.)
• Using AI in Excel, data analysis and reporting.
• Automation (including Power Automate training).

· Wants:

• 87% would like an AI training workshop once a month.
• To learn about content creation (including teaching resources, communications, social media content, project management, training materials and videos).
• Practical and more advanced examples (including AI for budget management, research support, student allocations and timetabling, CRM/database querying, and more department-specific use cases.
• Discussion around how other colleagues are using AI.

Our reflections and next steps

•  Participant preference for online meetings, although the in-person sessions felt more productive.
•  Lots of uncertainty around what university policy allowed/did not allow.
•  Lack of clarity around what support was currently available and from where.
•  Staff and students are facing many common issues, and while some individuals might feel uncomfortable in sharing workshops with their students/educators respectively, we feel there would be value to all parties in progressing collaborative sessions.
• There are still plenty of staff who have not engaged – we need up to date asynchronous resources and a helpline to provide support at the time of need. If partly carried out by an AI chatbot, the resource required for the helpline would be reduced, while also giving us the opportunity to “practice what we preach”.
•  Specific examples of what individual members of staff have done and what worked/did not work are important.
• We should be “tool agnostic” in our recommendations rather than commit to constant changes/updates or encourage people to purchase premium features.

We have reported back our findings to the various University-wide workstreams on staff AI training. Colleagues in these workstreams have appreciated the picture of staff needs and wants provided by our findings. We have also highlighted the need for tool-agnostic training that staff can apply to whichever tool they are using for their work. This is particularly important to address the diverse range of needs that understandably comes with belonging to such a large and diverse institution.

Some positive updates are being made to the clarity of staff guidance on AI. In particular, the Staff AI Catalogue and the accompanying Information Classification Scheme have been updated to provide clarity on what we can and can’t do with different types of information. These updates were underway at the time of our workshops, and will hopefully contribute to addressing some of the key concerns raised.

The Library have also created an AI Toolkit of resources to be used in teaching sessions with students to build student AI literacy. To find out more about this, visit the AI Toolkit homepage, or register for the next ‘Building Student AI Literacy: Introducing the AI Toolkit’ workshop on Thursday 29th October from 11:00 – 12:00 on MS Teams.

Most encouragingly, the conversations within and about our workshops have enabled us to surface a number of interesting projects that are underway in different areas of the university and to share them more widely. For example, Chidi Obeka who runs the AI and Student Services Community of Practice is developing a series of workshops on Power Automate and Agents, and Leif Isaksen from Digital Humanities is building a comprehensive resource admirably titled “A Hitchhiker’s Guide to AI in the Humanities”. We would be delighted to learn about and promote other initiatives that are underway, so if this applies to you, please get in touch.