About the Programme

Purpose

Artificial intelligence is changing how we teach, research and work. The AI Mentorship Programme creates structured, supportive partnerships between colleagues so that expertise is shared rather than duplicated. Mentors offer their experience; mentees bring questions, curiosity and their own disciplinary insight. Both partners learn.

Who can take part

XJTLU academic staff across all campuses, schools, academies and departments are welcome to apply. You do not need advanced technical knowledge to join as a mentee, and you do not need to be an AI specialist to volunteer as a mentor. If you have practical experience using AI in learning and teaching that colleagues could benefit from, we encourage you to take part.

Focus areas

• AI Agent Development and Implementation

  Designing, building and trialling agents that support teaching, research or professional workflows.

• AI-Enhanced Curriculum Redesign

  Rethinking modules, learning activities and assessment in light of generative AI.

• AI-Enhanced Programme Redesign

  Working at programme level on graduate attributes, progression and coherent AI literacy.

• Pedagogical Research and Publication About AI

  Turning classroom practice into evidence, scholarship and publishable pedagogical research.

What to expect

• Monthly meetings. Pairs meet roughly once a month between October and May, face-to-face or online.
• Community of Practice sessions. Two whole-programme sessions bring all participants together to share progress.
• A reflective portfolio. Participants keep brief meeting logs and a short reflection on what changed in their practice.
• Recognition. The programme closes with a celebration and awards event in June 2027.

How matching works

When registration closes, the programme team reviews every profile. Suggested pairings are generated by comparing the expertise a mentor offers against the development areas a mentee has asked for, alongside shared AI interests, the type of support requested, experience levels and disciplinary preference. Every suggestion is reviewed and confirmed by the Educational Development Unit before either participant is notified — the system never finalises a pairing on its own.