Somewhere inside every organisation there is a line. On one side sits the work that intelligent systems now do better, faster and more consistently than we ever managed by hand. On the other sits the work that collapses the moment you automate it. Most conferences debate where that line should sit. We ask you to stand on it and find out for yourself. You’ll take a role, step inside a live system and follow a professional relationship from its first moment through to its last.
Along the way you’ll watch AI do the things it is genuinely good at. And then, when what’s needed is no longer information but a person, you’ll watch it stop. What happens in the space it leaves behind is the whole point of the session. We use mentoring as the setting because mentoring strips the question back to something you can feel. We close by handing the room over to people who do this for real, so you can hold the experience you have just lived against the thing it was modelled on.
Objectives
- Explore the boundary between human and AI contribution, examining where AI can add value and where human judgement, trust, empathy, and connection remain essential.
- Experience a Human-Led, AI-Amplified approach in practice by participating in a live, hands-on mentoring journey supported by AI.
- Connect academic perspectives on human–AI collaboration with industry practice, using mentoring as a practical setting for considering implications across different contexts.
Outcomes
- Apply the Human-Led, AI-Amplified principle when considering the design or adoption of AI enabled practices within your own organisational or professional context.
- Translate insights from the experience to your broader workplace settings, recognising where automation creates value and where human involvement should be preserved.
- Build your connections across academia and industry around the responsible and human centred application of AI in professional practice.
Workshop Information
Limited to 12 academics and researchers interested in the application of AI in business.
Limited to 12 industry professionals in leadership roles navigating the use of AI in the workplace.